mirror of https://github.com/ArduPilot/ardupilot
AP_NavEKF2: split EKF control and output get functions from state specific libs
This commit is contained in:
Siddharth Bharat Purohit
Randy Mackay
parent
2e388fb2f9
commit
1ce3276d74
|
|
@ -18,32 +18,6 @@
|
|||
|
||||
extern const AP_HAL::HAL& hal;
|
||||
|
||||
// Check basic filter health metrics and return a consolidated health status
|
||||
bool NavEKF2_core::healthy(void) const
|
||||
{
|
||||
uint8_t faultInt;
|
||||
getFilterFaults(faultInt);
|
||||
if (faultInt > 0) {
|
||||
return false;
|
||||
}
|
||||
if (velTestRatio > 1 && posTestRatio > 1 && hgtTestRatio > 1) {
|
||||
// all three metrics being above 1 means the filter is
|
||||
// extremely unhealthy.
|
||||
return false;
|
||||
}
|
||||
// Give the filter a second to settle before use
|
||||
if ((imuSampleTime_ms - ekfStartTime_ms) < 1000 ) {
|
||||
return false;
|
||||
}
|
||||
// barometer and position innovations must be within limits when on-ground
|
||||
float horizErrSq = sq(innovVelPos[3]) + sq(innovVelPos[4]);
|
||||
if (onGround && (fabsf(innovVelPos[5]) > 1.0f || horizErrSq > 1.0f)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// all OK
|
||||
return true;
|
||||
}
|
||||
|
||||
// Control filter mode transitions
|
||||
void NavEKF2_core::controlFilterModes()
|
||||
|
|
@ -249,174 +223,4 @@ bool NavEKF2_core::assume_zero_sideslip(void) const
|
|||
return _ahrs->get_fly_forward() && _ahrs->get_vehicle_class() != AHRS_VEHICLE_GROUND;
|
||||
}
|
||||
|
||||
// return the innovations for the NED Pos, NED Vel, XYZ Mag and Vtas measurements
|
||||
void NavEKF2_core::getInnovations(Vector3f &velInnov, Vector3f &posInnov, Vector3f &magInnov, float &tasInnov, float &yawInnov) const
|
||||
{
|
||||
velInnov.x = innovVelPos[0];
|
||||
velInnov.y = innovVelPos[1];
|
||||
velInnov.z = innovVelPos[2];
|
||||
posInnov.x = innovVelPos[3];
|
||||
posInnov.y = innovVelPos[4];
|
||||
posInnov.z = innovVelPos[5];
|
||||
magInnov.x = 1e3f*innovMag[0]; // Convert back to sensor units
|
||||
magInnov.y = 1e3f*innovMag[1]; // Convert back to sensor units
|
||||
magInnov.z = 1e3f*innovMag[2]; // Convert back to sensor units
|
||||
tasInnov = innovVtas;
|
||||
yawInnov = innovYaw;
|
||||
}
|
||||
|
||||
// return the innovation consistency test ratios for the velocity, position, magnetometer and true airspeed measurements
|
||||
// this indicates the amount of margin available when tuning the various error traps
|
||||
// also return the current offsets applied to the GPS position measurements
|
||||
void NavEKF2_core::getVariances(float &velVar, float &posVar, float &hgtVar, Vector3f &magVar, float &tasVar, Vector2f &offset) const
|
||||
{
|
||||
velVar = sqrtf(velTestRatio);
|
||||
posVar = sqrtf(posTestRatio);
|
||||
hgtVar = sqrtf(hgtTestRatio);
|
||||
magVar.x = sqrtf(magTestRatio.x);
|
||||
magVar.y = sqrtf(magTestRatio.y);
|
||||
magVar.z = sqrtf(magTestRatio.z);
|
||||
tasVar = sqrtf(tasTestRatio);
|
||||
offset = gpsPosGlitchOffsetNE;
|
||||
}
|
||||
|
||||
|
||||
/*
|
||||
return the filter fault status as a bitmasked integer
|
||||
0 = quaternions are NaN
|
||||
1 = velocities are NaN
|
||||
2 = badly conditioned X magnetometer fusion
|
||||
3 = badly conditioned Y magnetometer fusion
|
||||
5 = badly conditioned Z magnetometer fusion
|
||||
6 = badly conditioned airspeed fusion
|
||||
7 = badly conditioned synthetic sideslip fusion
|
||||
7 = filter is not initialised
|
||||
*/
|
||||
void NavEKF2_core::getFilterFaults(uint8_t &faults) const
|
||||
{
|
||||
faults = (stateStruct.quat.is_nan()<<0 |
|
||||
stateStruct.velocity.is_nan()<<1 |
|
||||
faultStatus.bad_xmag<<2 |
|
||||
faultStatus.bad_ymag<<3 |
|
||||
faultStatus.bad_zmag<<4 |
|
||||
faultStatus.bad_airspeed<<5 |
|
||||
faultStatus.bad_sideslip<<6 |
|
||||
!statesInitialised<<7);
|
||||
}
|
||||
|
||||
/*
|
||||
return filter timeout status as a bitmasked integer
|
||||
0 = position measurement timeout
|
||||
1 = velocity measurement timeout
|
||||
2 = height measurement timeout
|
||||
3 = magnetometer measurement timeout
|
||||
4 = true airspeed measurement timeout
|
||||
5 = unassigned
|
||||
6 = unassigned
|
||||
7 = unassigned
|
||||
*/
|
||||
void NavEKF2_core::getFilterTimeouts(uint8_t &timeouts) const
|
||||
{
|
||||
timeouts = (posTimeout<<0 |
|
||||
velTimeout<<1 |
|
||||
hgtTimeout<<2 |
|
||||
magTimeout<<3 |
|
||||
tasTimeout<<4);
|
||||
}
|
||||
|
||||
/*
|
||||
return filter function status as a bitmasked integer
|
||||
0 = attitude estimate valid
|
||||
1 = horizontal velocity estimate valid
|
||||
2 = vertical velocity estimate valid
|
||||
3 = relative horizontal position estimate valid
|
||||
4 = absolute horizontal position estimate valid
|
||||
5 = vertical position estimate valid
|
||||
6 = terrain height estimate valid
|
||||
7 = constant position mode
|
||||
*/
|
||||
void NavEKF2_core::getFilterStatus(nav_filter_status &status) const
|
||||
{
|
||||
// init return value
|
||||
status.value = 0;
|
||||
|
||||
bool doingFlowNav = (PV_AidingMode == AID_RELATIVE) && flowDataValid;
|
||||
bool doingWindRelNav = !tasTimeout && assume_zero_sideslip();
|
||||
bool doingNormalGpsNav = !posTimeout && (PV_AidingMode == AID_ABSOLUTE);
|
||||
bool notDeadReckoning = (PV_AidingMode == AID_ABSOLUTE);
|
||||
bool someVertRefData = (!velTimeout && useGpsVertVel) || !hgtTimeout;
|
||||
bool someHorizRefData = !(velTimeout && posTimeout && tasTimeout) || doingFlowNav;
|
||||
bool optFlowNavPossible = flowDataValid && (frontend._fusionModeGPS == 3);
|
||||
bool gpsNavPossible = !gpsNotAvailable && (frontend._fusionModeGPS <= 2);
|
||||
bool filterHealthy = healthy() && tiltAlignComplete && yawAlignComplete;
|
||||
|
||||
// set individual flags
|
||||
status.flags.attitude = !stateStruct.quat.is_nan() && filterHealthy; // attitude valid (we need a better check)
|
||||
status.flags.horiz_vel = someHorizRefData && notDeadReckoning && filterHealthy; // horizontal velocity estimate valid
|
||||
status.flags.vert_vel = someVertRefData && filterHealthy; // vertical velocity estimate valid
|
||||
status.flags.horiz_pos_rel = ((doingFlowNav && gndOffsetValid) || doingWindRelNav || doingNormalGpsNav) && notDeadReckoning && filterHealthy; // relative horizontal position estimate valid
|
||||
status.flags.horiz_pos_abs = doingNormalGpsNav && notDeadReckoning && filterHealthy; // absolute horizontal position estimate valid
|
||||
status.flags.vert_pos = !hgtTimeout && filterHealthy; // vertical position estimate valid
|
||||
status.flags.terrain_alt = gndOffsetValid && filterHealthy; // terrain height estimate valid
|
||||
status.flags.const_pos_mode = (PV_AidingMode == AID_NONE) && filterHealthy; // constant position mode
|
||||
status.flags.pred_horiz_pos_rel = (optFlowNavPossible || gpsNavPossible) && filterHealthy; // we should be able to estimate a relative position when we enter flight mode
|
||||
status.flags.pred_horiz_pos_abs = gpsNavPossible && filterHealthy; // we should be able to estimate an absolute position when we enter flight mode
|
||||
status.flags.takeoff_detected = takeOffDetected; // takeoff for optical flow navigation has been detected
|
||||
status.flags.takeoff = expectGndEffectTakeoff; // The EKF has been told to expect takeoff and is in a ground effect mitigation mode
|
||||
status.flags.touchdown = expectGndEffectTouchdown; // The EKF has been told to detect touchdown and is in a ground effect mitigation mode
|
||||
status.flags.using_gps = (imuSampleTime_ms - lastPosPassTime_ms) < 4000;
|
||||
}
|
||||
|
||||
// send an EKF_STATUS message to GCS
|
||||
void NavEKF2_core::send_status_report(mavlink_channel_t chan)
|
||||
{
|
||||
// get filter status
|
||||
nav_filter_status filt_state;
|
||||
getFilterStatus(filt_state);
|
||||
|
||||
// prepare flags
|
||||
uint16_t flags = 0;
|
||||
if (filt_state.flags.attitude) {
|
||||
flags |= EKF_ATTITUDE;
|
||||
}
|
||||
if (filt_state.flags.horiz_vel) {
|
||||
flags |= EKF_VELOCITY_HORIZ;
|
||||
}
|
||||
if (filt_state.flags.vert_vel) {
|
||||
flags |= EKF_VELOCITY_VERT;
|
||||
}
|
||||
if (filt_state.flags.horiz_pos_rel) {
|
||||
flags |= EKF_POS_HORIZ_REL;
|
||||
}
|
||||
if (filt_state.flags.horiz_pos_abs) {
|
||||
flags |= EKF_POS_HORIZ_ABS;
|
||||
}
|
||||
if (filt_state.flags.vert_pos) {
|
||||
flags |= EKF_POS_VERT_ABS;
|
||||
}
|
||||
if (filt_state.flags.terrain_alt) {
|
||||
flags |= EKF_POS_VERT_AGL;
|
||||
}
|
||||
if (filt_state.flags.const_pos_mode) {
|
||||
flags |= EKF_CONST_POS_MODE;
|
||||
}
|
||||
if (filt_state.flags.pred_horiz_pos_rel) {
|
||||
flags |= EKF_PRED_POS_HORIZ_REL;
|
||||
}
|
||||
if (filt_state.flags.pred_horiz_pos_abs) {
|
||||
flags |= EKF_PRED_POS_HORIZ_ABS;
|
||||
}
|
||||
|
||||
// get variances
|
||||
float velVar, posVar, hgtVar, tasVar;
|
||||
Vector3f magVar;
|
||||
Vector2f offset;
|
||||
getVariances(velVar, posVar, hgtVar, magVar, tasVar, offset);
|
||||
|
||||
// send message
|
||||
mavlink_msg_ekf_status_report_send(chan, flags, velVar, posVar, hgtVar, magVar.length(), tasVar);
|
||||
|
||||
}
|
||||
|
||||
|
||||
#endif // HAL_CPU_CLASS
|
||||
|
|
@ -0,0 +1,413 @@
|
|||
/// -*- tab-width: 4; Mode: C++; c-basic-offset: 4; indent-tabs-mode: nil -*-
|
||||
|
||||
#include <AP_HAL/AP_HAL.h>
|
||||
|
||||
#if HAL_CPU_CLASS >= HAL_CPU_CLASS_150
|
||||
|
||||
/*
|
||||
optionally turn down optimisation for debugging
|
||||
*/
|
||||
// #pragma GCC optimize("O0")
|
||||
|
||||
#include "AP_NavEKF2.h"
|
||||
#include "AP_NavEKF2_core.h"
|
||||
#include <AP_AHRS/AP_AHRS.h>
|
||||
#include <AP_Vehicle/AP_Vehicle.h>
|
||||
|
||||
#include <stdio.h>
|
||||
|
||||
extern const AP_HAL::HAL& hal;
|
||||
|
||||
|
||||
// Check basic filter health metrics and return a consolidated health status
|
||||
bool NavEKF2_core::healthy(void) const
|
||||
{
|
||||
uint8_t faultInt;
|
||||
getFilterFaults(faultInt);
|
||||
if (faultInt > 0) {
|
||||
return false;
|
||||
}
|
||||
if (velTestRatio > 1 && posTestRatio > 1 && hgtTestRatio > 1) {
|
||||
// all three metrics being above 1 means the filter is
|
||||
// extremely unhealthy.
|
||||
return false;
|
||||
}
|
||||
// Give the filter a second to settle before use
|
||||
if ((imuSampleTime_ms - ekfStartTime_ms) < 1000 ) {
|
||||
return false;
|
||||
}
|
||||
// barometer and position innovations must be within limits when on-ground
|
||||
float horizErrSq = sq(innovVelPos[3]) + sq(innovVelPos[4]);
|
||||
if (onGround && (fabsf(innovVelPos[5]) > 1.0f || horizErrSq > 1.0f)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// all OK
|
||||
return true;
|
||||
}
|
||||
|
||||
// return data for debugging optical flow fusion
|
||||
void NavEKF2_core::getFlowDebug(float &varFlow, float &gndOffset, float &flowInnovX, float &flowInnovY, float &auxInnov, float &HAGL, float &rngInnov, float &range, float &gndOffsetErr) const
|
||||
{
|
||||
varFlow = max(flowTestRatio[0],flowTestRatio[1]);
|
||||
gndOffset = terrainState;
|
||||
flowInnovX = innovOptFlow[0];
|
||||
flowInnovY = innovOptFlow[1];
|
||||
auxInnov = auxFlowObsInnov;
|
||||
HAGL = terrainState - stateStruct.position.z;
|
||||
rngInnov = innovRng;
|
||||
range = rngMea;
|
||||
gndOffsetErr = sqrtf(Popt); // note Popt is constrained to be non-negative in EstimateTerrainOffset()
|
||||
}
|
||||
|
||||
// provides the height limit to be observed by the control loops
|
||||
// returns false if no height limiting is required
|
||||
// this is needed to ensure the vehicle does not fly too high when using optical flow navigation
|
||||
bool NavEKF2_core::getHeightControlLimit(float &height) const
|
||||
{
|
||||
// only ask for limiting if we are doing optical flow navigation
|
||||
if (frontend._fusionModeGPS == 3) {
|
||||
// If are doing optical flow nav, ensure the height above ground is within range finder limits after accounting for vehicle tilt and control errors
|
||||
height = max(float(_rng.max_distance_cm()) * 0.007f - 1.0f, 1.0f);
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// return the transformation matrix from XYZ (body) to NED axes
|
||||
void NavEKF2_core::getRotationBodyToNED(Matrix3f &mat) const
|
||||
{
|
||||
Vector3f trim = _ahrs->get_trim();
|
||||
outputDataNew.quat.rotation_matrix(mat);
|
||||
mat.rotateXYinv(trim);
|
||||
}
|
||||
|
||||
// return the quaternions defining the rotation from NED to XYZ (body) axes
|
||||
void NavEKF2_core::getQuaternion(Quaternion& ret) const
|
||||
{
|
||||
ret = outputDataNew.quat;
|
||||
}
|
||||
|
||||
// return the amount of yaw angle change due to the last yaw angle reset in radians
|
||||
// returns the time of the last yaw angle reset or 0 if no reset has ever occurred
|
||||
uint32_t NavEKF2_core::getLastYawResetAngle(float &yawAng)
|
||||
{
|
||||
yawAng = yawResetAngle;
|
||||
return lastYawReset_ms;
|
||||
}
|
||||
|
||||
// return the NED wind speed estimates in m/s (positive is air moving in the direction of the axis)
|
||||
void NavEKF2_core::getWind(Vector3f &wind) const
|
||||
{
|
||||
wind.x = stateStruct.wind_vel.x;
|
||||
wind.y = stateStruct.wind_vel.y;
|
||||
wind.z = 0.0f; // currently don't estimate this
|
||||
}
|
||||
|
||||
|
||||
// return NED velocity in m/s
|
||||
//
|
||||
void NavEKF2_core::getVelNED(Vector3f &vel) const
|
||||
{
|
||||
vel = outputDataNew.velocity;
|
||||
}
|
||||
|
||||
// This returns the specific forces in the NED frame
|
||||
void NavEKF2_core::getAccelNED(Vector3f &accelNED) const {
|
||||
accelNED = velDotNED;
|
||||
accelNED.z -= GRAVITY_MSS;
|
||||
}
|
||||
|
||||
// return the Z-accel bias estimate in m/s^2
|
||||
void NavEKF2_core::getAccelZBias(float &zbias) const {
|
||||
if (dtIMUavg > 0) {
|
||||
zbias = stateStruct.accel_zbias / dtIMUavg;
|
||||
} else {
|
||||
zbias = 0;
|
||||
}
|
||||
}
|
||||
|
||||
// Return the last calculated NED position relative to the reference point (m).
|
||||
// if a calculated solution is not available, use the best available data and return false
|
||||
bool NavEKF2_core::getPosNED(Vector3f &pos) const
|
||||
{
|
||||
// The EKF always has a height estimate regardless of mode of operation
|
||||
pos.z = outputDataNew.position.z;
|
||||
// There are three modes of operation, absolute position (GPS fusion), relative position (optical flow fusion) and constant position (no position estimate available)
|
||||
nav_filter_status status;
|
||||
getFilterStatus(status);
|
||||
if (status.flags.horiz_pos_abs || status.flags.horiz_pos_rel) {
|
||||
// This is the normal mode of operation where we can use the EKF position states
|
||||
pos.x = outputDataNew.position.x;
|
||||
pos.y = outputDataNew.position.y;
|
||||
return true;
|
||||
} else {
|
||||
// In constant position mode the EKF position states are at the origin, so we cannot use them as a position estimate
|
||||
if(validOrigin) {
|
||||
if ((_ahrs->get_gps().status() >= AP_GPS::GPS_OK_FIX_2D)) {
|
||||
// If the origin has been set and we have GPS, then return the GPS position relative to the origin
|
||||
const struct Location &gpsloc = _ahrs->get_gps().location();
|
||||
Vector2f tempPosNE = location_diff(EKF_origin, gpsloc);
|
||||
pos.x = tempPosNE.x;
|
||||
pos.y = tempPosNE.y;
|
||||
return false;
|
||||
} else {
|
||||
// If no GPS fix is available, all we can do is provide the last known position
|
||||
pos.x = outputDataNew.position.x;
|
||||
pos.y = outputDataNew.position.y;
|
||||
return false;
|
||||
}
|
||||
} else {
|
||||
// If the origin has not been set, then we have no means of providing a relative position
|
||||
pos.x = 0.0f;
|
||||
pos.y = 0.0f;
|
||||
return false;
|
||||
}
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
// return the estimated height above ground level
|
||||
bool NavEKF2_core::getHAGL(float &HAGL) const
|
||||
{
|
||||
HAGL = terrainState - outputDataNew.position.z;
|
||||
// If we know the terrain offset and altitude, then we have a valid height above ground estimate
|
||||
return !hgtTimeout && gndOffsetValid && healthy();
|
||||
}
|
||||
|
||||
|
||||
// Return the last calculated latitude, longitude and height in WGS-84
|
||||
// If a calculated location isn't available, return a raw GPS measurement
|
||||
// The status will return true if a calculation or raw measurement is available
|
||||
// The getFilterStatus() function provides a more detailed description of data health and must be checked if data is to be used for flight control
|
||||
bool NavEKF2_core::getLLH(struct Location &loc) const
|
||||
{
|
||||
if(validOrigin) {
|
||||
// Altitude returned is an absolute altitude relative to the WGS-84 spherioid
|
||||
loc.alt = EKF_origin.alt - outputDataNew.position.z*100;
|
||||
loc.flags.relative_alt = 0;
|
||||
loc.flags.terrain_alt = 0;
|
||||
|
||||
// there are three modes of operation, absolute position (GPS fusion), relative position (optical flow fusion) and constant position (no aiding)
|
||||
nav_filter_status status;
|
||||
getFilterStatus(status);
|
||||
if (status.flags.horiz_pos_abs || status.flags.horiz_pos_rel) {
|
||||
loc.lat = EKF_origin.lat;
|
||||
loc.lng = EKF_origin.lng;
|
||||
location_offset(loc, outputDataNew.position.x, outputDataNew.position.y);
|
||||
return true;
|
||||
} else {
|
||||
// we could be in constant position mode becasue the vehicle has taken off without GPS, or has lost GPS
|
||||
// in this mode we cannot use the EKF states to estimate position so will return the best available data
|
||||
if ((_ahrs->get_gps().status() >= AP_GPS::GPS_OK_FIX_2D)) {
|
||||
// we have a GPS position fix to return
|
||||
const struct Location &gpsloc = _ahrs->get_gps().location();
|
||||
loc.lat = gpsloc.lat;
|
||||
loc.lng = gpsloc.lng;
|
||||
return true;
|
||||
} else {
|
||||
// if no GPS fix, provide last known position before entering the mode
|
||||
location_offset(loc, lastKnownPositionNE.x, lastKnownPositionNE.y);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// If no origin has been defined for the EKF, then we cannot use its position states so return a raw
|
||||
// GPS reading if available and return false
|
||||
if ((_ahrs->get_gps().status() >= AP_GPS::GPS_OK_FIX_3D)) {
|
||||
const struct Location &gpsloc = _ahrs->get_gps().location();
|
||||
loc = gpsloc;
|
||||
loc.flags.relative_alt = 0;
|
||||
loc.flags.terrain_alt = 0;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// return earth magnetic field estimates in measurement units / 1000
|
||||
void NavEKF2_core::getMagNED(Vector3f &magNED) const
|
||||
{
|
||||
magNED = stateStruct.earth_magfield * 1000.0f;
|
||||
}
|
||||
|
||||
// return body magnetic field estimates in measurement units / 1000
|
||||
void NavEKF2_core::getMagXYZ(Vector3f &magXYZ) const
|
||||
{
|
||||
magXYZ = stateStruct.body_magfield*1000.0f;
|
||||
}
|
||||
|
||||
|
||||
// return the innovations for the NED Pos, NED Vel, XYZ Mag and Vtas measurements
|
||||
void NavEKF2_core::getInnovations(Vector3f &velInnov, Vector3f &posInnov, Vector3f &magInnov, float &tasInnov, float &yawInnov) const
|
||||
{
|
||||
velInnov.x = innovVelPos[0];
|
||||
velInnov.y = innovVelPos[1];
|
||||
velInnov.z = innovVelPos[2];
|
||||
posInnov.x = innovVelPos[3];
|
||||
posInnov.y = innovVelPos[4];
|
||||
posInnov.z = innovVelPos[5];
|
||||
magInnov.x = 1e3f*innovMag[0]; // Convert back to sensor units
|
||||
magInnov.y = 1e3f*innovMag[1]; // Convert back to sensor units
|
||||
magInnov.z = 1e3f*innovMag[2]; // Convert back to sensor units
|
||||
tasInnov = innovVtas;
|
||||
yawInnov = innovYaw;
|
||||
}
|
||||
|
||||
// return the innovation consistency test ratios for the velocity, position, magnetometer and true airspeed measurements
|
||||
// this indicates the amount of margin available when tuning the various error traps
|
||||
// also return the current offsets applied to the GPS position measurements
|
||||
void NavEKF2_core::getVariances(float &velVar, float &posVar, float &hgtVar, Vector3f &magVar, float &tasVar, Vector2f &offset) const
|
||||
{
|
||||
velVar = sqrtf(velTestRatio);
|
||||
posVar = sqrtf(posTestRatio);
|
||||
hgtVar = sqrtf(hgtTestRatio);
|
||||
magVar.x = sqrtf(magTestRatio.x);
|
||||
magVar.y = sqrtf(magTestRatio.y);
|
||||
magVar.z = sqrtf(magTestRatio.z);
|
||||
tasVar = sqrtf(tasTestRatio);
|
||||
offset = gpsPosGlitchOffsetNE;
|
||||
}
|
||||
|
||||
|
||||
/*
|
||||
return the filter fault status as a bitmasked integer
|
||||
0 = quaternions are NaN
|
||||
1 = velocities are NaN
|
||||
2 = badly conditioned X magnetometer fusion
|
||||
3 = badly conditioned Y magnetometer fusion
|
||||
5 = badly conditioned Z magnetometer fusion
|
||||
6 = badly conditioned airspeed fusion
|
||||
7 = badly conditioned synthetic sideslip fusion
|
||||
7 = filter is not initialised
|
||||
*/
|
||||
void NavEKF2_core::getFilterFaults(uint8_t &faults) const
|
||||
{
|
||||
faults = (stateStruct.quat.is_nan()<<0 |
|
||||
stateStruct.velocity.is_nan()<<1 |
|
||||
faultStatus.bad_xmag<<2 |
|
||||
faultStatus.bad_ymag<<3 |
|
||||
faultStatus.bad_zmag<<4 |
|
||||
faultStatus.bad_airspeed<<5 |
|
||||
faultStatus.bad_sideslip<<6 |
|
||||
!statesInitialised<<7);
|
||||
}
|
||||
|
||||
/*
|
||||
return filter timeout status as a bitmasked integer
|
||||
0 = position measurement timeout
|
||||
1 = velocity measurement timeout
|
||||
2 = height measurement timeout
|
||||
3 = magnetometer measurement timeout
|
||||
4 = true airspeed measurement timeout
|
||||
5 = unassigned
|
||||
6 = unassigned
|
||||
7 = unassigned
|
||||
*/
|
||||
void NavEKF2_core::getFilterTimeouts(uint8_t &timeouts) const
|
||||
{
|
||||
timeouts = (posTimeout<<0 |
|
||||
velTimeout<<1 |
|
||||
hgtTimeout<<2 |
|
||||
magTimeout<<3 |
|
||||
tasTimeout<<4);
|
||||
}
|
||||
|
||||
/*
|
||||
return filter function status as a bitmasked integer
|
||||
0 = attitude estimate valid
|
||||
1 = horizontal velocity estimate valid
|
||||
2 = vertical velocity estimate valid
|
||||
3 = relative horizontal position estimate valid
|
||||
4 = absolute horizontal position estimate valid
|
||||
5 = vertical position estimate valid
|
||||
6 = terrain height estimate valid
|
||||
7 = constant position mode
|
||||
*/
|
||||
void NavEKF2_core::getFilterStatus(nav_filter_status &status) const
|
||||
{
|
||||
// init return value
|
||||
status.value = 0;
|
||||
|
||||
bool doingFlowNav = (PV_AidingMode == AID_RELATIVE) && flowDataValid;
|
||||
bool doingWindRelNav = !tasTimeout && assume_zero_sideslip();
|
||||
bool doingNormalGpsNav = !posTimeout && (PV_AidingMode == AID_ABSOLUTE);
|
||||
bool notDeadReckoning = (PV_AidingMode == AID_ABSOLUTE);
|
||||
bool someVertRefData = (!velTimeout && useGpsVertVel) || !hgtTimeout;
|
||||
bool someHorizRefData = !(velTimeout && posTimeout && tasTimeout) || doingFlowNav;
|
||||
bool optFlowNavPossible = flowDataValid && (frontend._fusionModeGPS == 3);
|
||||
bool gpsNavPossible = !gpsNotAvailable && (frontend._fusionModeGPS <= 2);
|
||||
bool filterHealthy = healthy() && tiltAlignComplete && yawAlignComplete;
|
||||
|
||||
// set individual flags
|
||||
status.flags.attitude = !stateStruct.quat.is_nan() && filterHealthy; // attitude valid (we need a better check)
|
||||
status.flags.horiz_vel = someHorizRefData && notDeadReckoning && filterHealthy; // horizontal velocity estimate valid
|
||||
status.flags.vert_vel = someVertRefData && filterHealthy; // vertical velocity estimate valid
|
||||
status.flags.horiz_pos_rel = ((doingFlowNav && gndOffsetValid) || doingWindRelNav || doingNormalGpsNav) && notDeadReckoning && filterHealthy; // relative horizontal position estimate valid
|
||||
status.flags.horiz_pos_abs = doingNormalGpsNav && notDeadReckoning && filterHealthy; // absolute horizontal position estimate valid
|
||||
status.flags.vert_pos = !hgtTimeout && filterHealthy; // vertical position estimate valid
|
||||
status.flags.terrain_alt = gndOffsetValid && filterHealthy; // terrain height estimate valid
|
||||
status.flags.const_pos_mode = (PV_AidingMode == AID_NONE) && filterHealthy; // constant position mode
|
||||
status.flags.pred_horiz_pos_rel = (optFlowNavPossible || gpsNavPossible) && filterHealthy; // we should be able to estimate a relative position when we enter flight mode
|
||||
status.flags.pred_horiz_pos_abs = gpsNavPossible && filterHealthy; // we should be able to estimate an absolute position when we enter flight mode
|
||||
status.flags.takeoff_detected = takeOffDetected; // takeoff for optical flow navigation has been detected
|
||||
status.flags.takeoff = expectGndEffectTakeoff; // The EKF has been told to expect takeoff and is in a ground effect mitigation mode
|
||||
status.flags.touchdown = expectGndEffectTouchdown; // The EKF has been told to detect touchdown and is in a ground effect mitigation mode
|
||||
status.flags.using_gps = (imuSampleTime_ms - lastPosPassTime_ms) < 4000;
|
||||
}
|
||||
|
||||
// send an EKF_STATUS message to GCS
|
||||
void NavEKF2_core::send_status_report(mavlink_channel_t chan)
|
||||
{
|
||||
// get filter status
|
||||
nav_filter_status filt_state;
|
||||
getFilterStatus(filt_state);
|
||||
|
||||
// prepare flags
|
||||
uint16_t flags = 0;
|
||||
if (filt_state.flags.attitude) {
|
||||
flags |= EKF_ATTITUDE;
|
||||
}
|
||||
if (filt_state.flags.horiz_vel) {
|
||||
flags |= EKF_VELOCITY_HORIZ;
|
||||
}
|
||||
if (filt_state.flags.vert_vel) {
|
||||
flags |= EKF_VELOCITY_VERT;
|
||||
}
|
||||
if (filt_state.flags.horiz_pos_rel) {
|
||||
flags |= EKF_POS_HORIZ_REL;
|
||||
}
|
||||
if (filt_state.flags.horiz_pos_abs) {
|
||||
flags |= EKF_POS_HORIZ_ABS;
|
||||
}
|
||||
if (filt_state.flags.vert_pos) {
|
||||
flags |= EKF_POS_VERT_ABS;
|
||||
}
|
||||
if (filt_state.flags.terrain_alt) {
|
||||
flags |= EKF_POS_VERT_AGL;
|
||||
}
|
||||
if (filt_state.flags.const_pos_mode) {
|
||||
flags |= EKF_CONST_POS_MODE;
|
||||
}
|
||||
if (filt_state.flags.pred_horiz_pos_rel) {
|
||||
flags |= EKF_PRED_POS_HORIZ_REL;
|
||||
}
|
||||
if (filt_state.flags.pred_horiz_pos_abs) {
|
||||
flags |= EKF_PRED_POS_HORIZ_ABS;
|
||||
}
|
||||
|
||||
// get variances
|
||||
float velVar, posVar, hgtVar, tasVar;
|
||||
Vector3f magVar;
|
||||
Vector2f offset;
|
||||
getVariances(velVar, posVar, hgtVar, magVar, tasVar, offset);
|
||||
|
||||
// send message
|
||||
mavlink_msg_ekf_status_report_send(chan, flags, velVar, posVar, hgtVar, magVar.length(), tasVar);
|
||||
|
||||
}
|
||||
|
||||
#endif // HAL_CPU_CLASS
|
||||
|
|
@ -104,115 +104,6 @@ void NavEKF2_core::alignYawGPS()
|
|||
}
|
||||
}
|
||||
|
||||
/********************************************************
|
||||
* GET STATES/PARAMS FUNCTIONS *
|
||||
********************************************************/
|
||||
|
||||
// return earth magnetic field estimates in measurement units / 1000
|
||||
void NavEKF2_core::getMagNED(Vector3f &magNED) const
|
||||
{
|
||||
magNED = stateStruct.earth_magfield * 1000.0f;
|
||||
}
|
||||
|
||||
// return body magnetic field estimates in measurement units / 1000
|
||||
void NavEKF2_core::getMagXYZ(Vector3f &magXYZ) const
|
||||
{
|
||||
magXYZ = stateStruct.body_magfield*1000.0f;
|
||||
}
|
||||
/********************************************************
|
||||
* SET STATES/PARAMS FUNCTIONS *
|
||||
********************************************************/
|
||||
|
||||
|
||||
/********************************************************
|
||||
* READ SENSORS *
|
||||
********************************************************/
|
||||
// return magnetometer offsets
|
||||
// return true if offsets are valid
|
||||
bool NavEKF2_core::getMagOffsets(Vector3f &magOffsets) const
|
||||
{
|
||||
// compass offsets are valid if we have finalised magnetic field initialisation and magnetic field learning is not prohibited and primary compass is valid
|
||||
if (secondMagYawInit && (frontend._magCal != 2) && _ahrs->get_compass()->healthy(0)) {
|
||||
magOffsets = _ahrs->get_compass()->get_offsets(0) - stateStruct.body_magfield*1000.0f;
|
||||
return true;
|
||||
} else {
|
||||
magOffsets = _ahrs->get_compass()->get_offsets(0);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// check for new magnetometer data and update store measurements if available
|
||||
void NavEKF2_core::readMagData()
|
||||
{
|
||||
if (use_compass() && _ahrs->get_compass()->last_update_usec() != lastMagUpdate_ms) {
|
||||
// store time of last measurement update
|
||||
lastMagUpdate_ms = _ahrs->get_compass()->last_update_usec();
|
||||
|
||||
// estimate of time magnetometer measurement was taken, allowing for delays
|
||||
magMeasTime_ms = imuSampleTime_ms - frontend.magDelay_ms;
|
||||
|
||||
// read compass data and scale to improve numerical conditioning
|
||||
magDataNew.mag = _ahrs->get_compass()->get_field() * 0.001f;
|
||||
|
||||
// check for consistent data between magnetometers
|
||||
consistentMagData = _ahrs->get_compass()->consistent();
|
||||
|
||||
// check if compass offsets have been changed and adjust EKF bias states to maintain consistent innovations
|
||||
if (_ahrs->get_compass()->healthy(0)) {
|
||||
Vector3f nowMagOffsets = _ahrs->get_compass()->get_offsets(0);
|
||||
bool changeDetected = (!is_equal(nowMagOffsets.x,lastMagOffsets.x) || !is_equal(nowMagOffsets.y,lastMagOffsets.y) || !is_equal(nowMagOffsets.z,lastMagOffsets.z));
|
||||
// Ignore bias changes before final mag field and yaw initialisation, as there may have been a compass calibration
|
||||
if (changeDetected && secondMagYawInit) {
|
||||
stateStruct.body_magfield.x += (nowMagOffsets.x - lastMagOffsets.x) * 0.001f;
|
||||
stateStruct.body_magfield.y += (nowMagOffsets.y - lastMagOffsets.y) * 0.001f;
|
||||
stateStruct.body_magfield.z += (nowMagOffsets.z - lastMagOffsets.z) * 0.001f;
|
||||
}
|
||||
lastMagOffsets = nowMagOffsets;
|
||||
}
|
||||
|
||||
// save magnetometer measurement to buffer to be fused later
|
||||
magDataNew.time_ms = magMeasTime_ms;
|
||||
StoreMag();
|
||||
}
|
||||
}
|
||||
// store magnetometer data in a history array
|
||||
void NavEKF2_core::StoreMag()
|
||||
{
|
||||
if (magStoreIndex >= OBS_BUFFER_LENGTH) {
|
||||
magStoreIndex = 0;
|
||||
}
|
||||
storedMag[magStoreIndex] = magDataNew;
|
||||
magStoreIndex += 1;
|
||||
}
|
||||
|
||||
// return newest un-used magnetometer data that has fallen behind the fusion time horizon
|
||||
// if no un-used data is available behind the fusion horizon, return false
|
||||
bool NavEKF2_core::RecallMag()
|
||||
{
|
||||
mag_elements dataTemp;
|
||||
mag_elements dataTempZero;
|
||||
dataTempZero.time_ms = 0;
|
||||
uint32_t temp_ms = 0;
|
||||
for (uint8_t i=0; i<OBS_BUFFER_LENGTH; i++) {
|
||||
dataTemp = storedMag[i];
|
||||
// find a measurement older than the fusion time horizon that we haven't checked before
|
||||
if (dataTemp.time_ms != 0 && dataTemp.time_ms <= imuDataDelayed.time_ms) {
|
||||
// zero the time stamp so we won't use it again
|
||||
storedMag[i]=dataTempZero;
|
||||
// Find the most recent non-stale measurement that meets the time horizon criteria
|
||||
if (((imuDataDelayed.time_ms - dataTemp.time_ms) < 500) && dataTemp.time_ms > temp_ms) {
|
||||
magDataDelayed = dataTemp;
|
||||
temp_ms = dataTemp.time_ms;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (temp_ms != 0) {
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/********************************************************
|
||||
* FUSE MEASURED_DATA *
|
||||
********************************************************/
|
||||
|
|
|
|||
|
|
@ -0,0 +1,703 @@
|
|||
/// -*- tab-width: 4; Mode: C++; c-basic-offset: 4; indent-tabs-mode: nil -*-
|
||||
|
||||
#include <AP_HAL/AP_HAL.h>
|
||||
|
||||
#if HAL_CPU_CLASS >= HAL_CPU_CLASS_150
|
||||
|
||||
/*
|
||||
optionally turn down optimisation for debugging
|
||||
*/
|
||||
// #pragma GCC optimize("O0")
|
||||
|
||||
#include "AP_NavEKF2.h"
|
||||
#include "AP_NavEKF2_core.h"
|
||||
#include <AP_AHRS/AP_AHRS.h>
|
||||
#include <AP_Vehicle/AP_Vehicle.h>
|
||||
|
||||
#include <stdio.h>
|
||||
|
||||
extern const AP_HAL::HAL& hal;
|
||||
|
||||
|
||||
/********************************************************
|
||||
* OPT FLOW AND RANGE FINDER *
|
||||
********************************************************/
|
||||
|
||||
// Read the range finder and take new measurements if available
|
||||
// Read at 20Hz and apply a median filter
|
||||
void NavEKF2_core::readRangeFinder(void)
|
||||
{
|
||||
uint8_t midIndex;
|
||||
uint8_t maxIndex;
|
||||
uint8_t minIndex;
|
||||
// get theoretical correct range when the vehicle is on the ground
|
||||
rngOnGnd = _rng.ground_clearance_cm() * 0.01f;
|
||||
if (_rng.status() == RangeFinder::RangeFinder_Good && (imuSampleTime_ms - lastRngMeasTime_ms) > 50) {
|
||||
// store samples and sample time into a ring buffer
|
||||
rngMeasIndex ++;
|
||||
if (rngMeasIndex > 2) {
|
||||
rngMeasIndex = 0;
|
||||
}
|
||||
storedRngMeasTime_ms[rngMeasIndex] = imuSampleTime_ms;
|
||||
storedRngMeas[rngMeasIndex] = _rng.distance_cm() * 0.01f;
|
||||
// check for three fresh samples and take median
|
||||
bool sampleFresh[3];
|
||||
for (uint8_t index = 0; index <= 2; index++) {
|
||||
sampleFresh[index] = (imuSampleTime_ms - storedRngMeasTime_ms[index]) < 500;
|
||||
}
|
||||
if (sampleFresh[0] && sampleFresh[1] && sampleFresh[2]) {
|
||||
if (storedRngMeas[0] > storedRngMeas[1]) {
|
||||
minIndex = 1;
|
||||
maxIndex = 0;
|
||||
} else {
|
||||
maxIndex = 0;
|
||||
minIndex = 1;
|
||||
}
|
||||
if (storedRngMeas[2] > storedRngMeas[maxIndex]) {
|
||||
midIndex = maxIndex;
|
||||
} else if (storedRngMeas[2] < storedRngMeas[minIndex]) {
|
||||
midIndex = minIndex;
|
||||
} else {
|
||||
midIndex = 2;
|
||||
}
|
||||
rngMea = max(storedRngMeas[midIndex],rngOnGnd);
|
||||
newDataRng = true;
|
||||
rngValidMeaTime_ms = imuSampleTime_ms;
|
||||
} else if (onGround) {
|
||||
// if on ground and no return, we assume on ground range
|
||||
rngMea = rngOnGnd;
|
||||
newDataRng = true;
|
||||
rngValidMeaTime_ms = imuSampleTime_ms;
|
||||
} else {
|
||||
newDataRng = false;
|
||||
}
|
||||
lastRngMeasTime_ms = imuSampleTime_ms;
|
||||
}
|
||||
}
|
||||
|
||||
// write the raw optical flow measurements
|
||||
// this needs to be called externally.
|
||||
void NavEKF2_core::writeOptFlowMeas(uint8_t &rawFlowQuality, Vector2f &rawFlowRates, Vector2f &rawGyroRates, uint32_t &msecFlowMeas)
|
||||
{
|
||||
// The raw measurements need to be optical flow rates in radians/second averaged across the time since the last update
|
||||
// The PX4Flow sensor outputs flow rates with the following axis and sign conventions:
|
||||
// A positive X rate is produced by a positive sensor rotation about the X axis
|
||||
// A positive Y rate is produced by a positive sensor rotation about the Y axis
|
||||
// This filter uses a different definition of optical flow rates to the sensor with a positive optical flow rate produced by a
|
||||
// negative rotation about that axis. For example a positive rotation of the flight vehicle about its X (roll) axis would produce a negative X flow rate
|
||||
flowMeaTime_ms = imuSampleTime_ms;
|
||||
// calculate bias errors on flow sensor gyro rates, but protect against spikes in data
|
||||
// reset the accumulated body delta angle and time
|
||||
// don't do the calculation if not enough time lapsed for a reliable body rate measurement
|
||||
if (delTimeOF > 0.01f) {
|
||||
flowGyroBias.x = 0.99f * flowGyroBias.x + 0.01f * constrain_float((rawGyroRates.x - delAngBodyOF.x/delTimeOF),-0.1f,0.1f);
|
||||
flowGyroBias.y = 0.99f * flowGyroBias.y + 0.01f * constrain_float((rawGyroRates.y - delAngBodyOF.y/delTimeOF),-0.1f,0.1f);
|
||||
delAngBodyOF.zero();
|
||||
delTimeOF = 0.0f;
|
||||
}
|
||||
// check for takeoff if relying on optical flow and zero measurements until takeoff detected
|
||||
// if we haven't taken off - constrain position and velocity states
|
||||
if (frontend._fusionModeGPS == 3) {
|
||||
detectOptFlowTakeoff();
|
||||
}
|
||||
// calculate rotation matrices at mid sample time for flow observations
|
||||
stateStruct.quat.rotation_matrix(Tbn_flow);
|
||||
Tnb_flow = Tbn_flow.transposed();
|
||||
// don't use data with a low quality indicator or extreme rates (helps catch corrupt sensor data)
|
||||
if ((rawFlowQuality > 0) && rawFlowRates.length() < 4.2f && rawGyroRates.length() < 4.2f) {
|
||||
// correct flow sensor rates for bias
|
||||
omegaAcrossFlowTime.x = rawGyroRates.x - flowGyroBias.x;
|
||||
omegaAcrossFlowTime.y = rawGyroRates.y - flowGyroBias.y;
|
||||
// write uncorrected flow rate measurements that will be used by the focal length scale factor estimator
|
||||
// note correction for different axis and sign conventions used by the px4flow sensor
|
||||
ofDataNew.flowRadXY = - rawFlowRates; // raw (non motion compensated) optical flow angular rate about the X axis (rad/sec)
|
||||
// write flow rate measurements corrected for body rates
|
||||
ofDataNew.flowRadXYcomp.x = ofDataNew.flowRadXY.x + omegaAcrossFlowTime.x;
|
||||
ofDataNew.flowRadXYcomp.y = ofDataNew.flowRadXY.y + omegaAcrossFlowTime.y;
|
||||
// record time last observation was received so we can detect loss of data elsewhere
|
||||
flowValidMeaTime_ms = imuSampleTime_ms;
|
||||
// estimate sample time of the measurement
|
||||
ofDataNew.time_ms = imuSampleTime_ms - frontend._flowDelay_ms - frontend.flowTimeDeltaAvg_ms/2;
|
||||
// Save data to buffer
|
||||
StoreOF();
|
||||
// Check for data at the fusion time horizon
|
||||
newDataFlow = RecallOF();
|
||||
}
|
||||
}
|
||||
|
||||
// store OF data in a history array
|
||||
void NavEKF2_core::StoreOF()
|
||||
{
|
||||
if (ofStoreIndex >= OBS_BUFFER_LENGTH) {
|
||||
ofStoreIndex = 0;
|
||||
}
|
||||
storedOF[ofStoreIndex] = ofDataNew;
|
||||
ofStoreIndex += 1;
|
||||
}
|
||||
|
||||
// return newest un-used optical flow data that has fallen behind the fusion time horizon
|
||||
// if no un-used data is available behind the fusion horizon, return false
|
||||
bool NavEKF2_core::RecallOF()
|
||||
{
|
||||
of_elements dataTemp;
|
||||
of_elements dataTempZero;
|
||||
dataTempZero.time_ms = 0;
|
||||
uint32_t temp_ms = 0;
|
||||
for (uint8_t i=0; i<OBS_BUFFER_LENGTH; i++) {
|
||||
dataTemp = storedOF[i];
|
||||
// find a measurement older than the fusion time horizon that we haven't checked before
|
||||
if (dataTemp.time_ms != 0 && dataTemp.time_ms <= imuDataDelayed.time_ms) {
|
||||
// zero the time stamp so we won't use it again
|
||||
storedOF[i]=dataTempZero;
|
||||
// Find the most recent non-stale measurement that meets the time horizon criteria
|
||||
if (((imuDataDelayed.time_ms - dataTemp.time_ms) < 500) && dataTemp.time_ms > temp_ms) {
|
||||
ofDataDelayed = dataTemp;
|
||||
temp_ms = dataTemp.time_ms;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (temp_ms != 0) {
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
/********************************************************
|
||||
* MAGNETOMETER *
|
||||
********************************************************/
|
||||
|
||||
// return magnetometer offsets
|
||||
// return true if offsets are valid
|
||||
bool NavEKF2_core::getMagOffsets(Vector3f &magOffsets) const
|
||||
{
|
||||
// compass offsets are valid if we have finalised magnetic field initialisation and magnetic field learning is not prohibited and primary compass is valid
|
||||
if (secondMagYawInit && (frontend._magCal != 2) && _ahrs->get_compass()->healthy(0)) {
|
||||
magOffsets = _ahrs->get_compass()->get_offsets(0) - stateStruct.body_magfield*1000.0f;
|
||||
return true;
|
||||
} else {
|
||||
magOffsets = _ahrs->get_compass()->get_offsets(0);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// check for new magnetometer data and update store measurements if available
|
||||
void NavEKF2_core::readMagData()
|
||||
{
|
||||
if (use_compass() && _ahrs->get_compass()->last_update_usec() != lastMagUpdate_ms) {
|
||||
// store time of last measurement update
|
||||
lastMagUpdate_ms = _ahrs->get_compass()->last_update_usec();
|
||||
|
||||
// estimate of time magnetometer measurement was taken, allowing for delays
|
||||
magMeasTime_ms = imuSampleTime_ms - frontend.magDelay_ms;
|
||||
|
||||
// read compass data and scale to improve numerical conditioning
|
||||
magDataNew.mag = _ahrs->get_compass()->get_field() * 0.001f;
|
||||
|
||||
// check for consistent data between magnetometers
|
||||
consistentMagData = _ahrs->get_compass()->consistent();
|
||||
|
||||
// check if compass offsets have been changed and adjust EKF bias states to maintain consistent innovations
|
||||
if (_ahrs->get_compass()->healthy(0)) {
|
||||
Vector3f nowMagOffsets = _ahrs->get_compass()->get_offsets(0);
|
||||
bool changeDetected = (!is_equal(nowMagOffsets.x,lastMagOffsets.x) || !is_equal(nowMagOffsets.y,lastMagOffsets.y) || !is_equal(nowMagOffsets.z,lastMagOffsets.z));
|
||||
// Ignore bias changes before final mag field and yaw initialisation, as there may have been a compass calibration
|
||||
if (changeDetected && secondMagYawInit) {
|
||||
stateStruct.body_magfield.x += (nowMagOffsets.x - lastMagOffsets.x) * 0.001f;
|
||||
stateStruct.body_magfield.y += (nowMagOffsets.y - lastMagOffsets.y) * 0.001f;
|
||||
stateStruct.body_magfield.z += (nowMagOffsets.z - lastMagOffsets.z) * 0.001f;
|
||||
}
|
||||
lastMagOffsets = nowMagOffsets;
|
||||
}
|
||||
|
||||
// save magnetometer measurement to buffer to be fused later
|
||||
magDataNew.time_ms = magMeasTime_ms;
|
||||
StoreMag();
|
||||
}
|
||||
}
|
||||
// store magnetometer data in a history array
|
||||
void NavEKF2_core::StoreMag()
|
||||
{
|
||||
if (magStoreIndex >= OBS_BUFFER_LENGTH) {
|
||||
magStoreIndex = 0;
|
||||
}
|
||||
storedMag[magStoreIndex] = magDataNew;
|
||||
magStoreIndex += 1;
|
||||
}
|
||||
|
||||
// return newest un-used magnetometer data that has fallen behind the fusion time horizon
|
||||
// if no un-used data is available behind the fusion horizon, return false
|
||||
bool NavEKF2_core::RecallMag()
|
||||
{
|
||||
mag_elements dataTemp;
|
||||
mag_elements dataTempZero;
|
||||
dataTempZero.time_ms = 0;
|
||||
uint32_t temp_ms = 0;
|
||||
for (uint8_t i=0; i<OBS_BUFFER_LENGTH; i++) {
|
||||
dataTemp = storedMag[i];
|
||||
// find a measurement older than the fusion time horizon that we haven't checked before
|
||||
if (dataTemp.time_ms != 0 && dataTemp.time_ms <= imuDataDelayed.time_ms) {
|
||||
// zero the time stamp so we won't use it again
|
||||
storedMag[i]=dataTempZero;
|
||||
// Find the most recent non-stale measurement that meets the time horizon criteria
|
||||
if (((imuDataDelayed.time_ms - dataTemp.time_ms) < 500) && dataTemp.time_ms > temp_ms) {
|
||||
magDataDelayed = dataTemp;
|
||||
temp_ms = dataTemp.time_ms;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (temp_ms != 0) {
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
/********************************************************
|
||||
* Inertial Measurements *
|
||||
********************************************************/
|
||||
|
||||
// update IMU delta angle and delta velocity measurements
|
||||
void NavEKF2_core::readIMUData()
|
||||
{
|
||||
const AP_InertialSensor &ins = _ahrs->get_ins();
|
||||
|
||||
// average IMU sampling rate
|
||||
dtIMUavg = 1.0f/ins.get_sample_rate();
|
||||
|
||||
// the imu sample time is used as a common time reference throughout the filter
|
||||
imuSampleTime_ms = hal.scheduler->millis();
|
||||
|
||||
// Get delta velocity data
|
||||
readDeltaVelocity(ins.get_primary_accel(), imuDataNew.delVel, imuDataNew.delVelDT);
|
||||
|
||||
// Get delta angle data
|
||||
readDeltaAngle(ins.get_primary_gyro(), imuDataNew.delAng);
|
||||
imuDataNew.delAngDT = max(ins.get_delta_time(),1.0e-4f);
|
||||
|
||||
// get current time stamp
|
||||
imuDataNew.time_ms = imuSampleTime_ms;
|
||||
|
||||
// save data in the FIFO buffer
|
||||
StoreIMU();
|
||||
|
||||
// extract the oldest available data from the FIFO buffer
|
||||
imuDataDelayed = storedIMU[fifoIndexDelayed];
|
||||
|
||||
}
|
||||
|
||||
// store imu in the FIFO
|
||||
void NavEKF2_core::StoreIMU()
|
||||
{
|
||||
fifoIndexDelayed = fifoIndexNow;
|
||||
fifoIndexNow = fifoIndexNow + 1;
|
||||
if (fifoIndexNow >= IMU_BUFFER_LENGTH) {
|
||||
fifoIndexNow = 0;
|
||||
}
|
||||
storedIMU[fifoIndexNow] = imuDataNew;
|
||||
}
|
||||
|
||||
// reset the stored imu history and store the current value
|
||||
void NavEKF2_core::StoreIMU_reset()
|
||||
{
|
||||
// write current measurement to entire table
|
||||
for (uint8_t i=0; i<IMU_BUFFER_LENGTH; i++) {
|
||||
storedIMU[i] = imuDataNew;
|
||||
}
|
||||
imuDataDelayed = imuDataNew;
|
||||
fifoIndexDelayed = fifoIndexNow+1;
|
||||
if (fifoIndexDelayed >= IMU_BUFFER_LENGTH) {
|
||||
fifoIndexDelayed = 0;
|
||||
}
|
||||
}
|
||||
|
||||
// recall IMU data from the FIFO
|
||||
void NavEKF2_core::RecallIMU()
|
||||
{
|
||||
imuDataDelayed = storedIMU[fifoIndexDelayed];
|
||||
}
|
||||
bool NavEKF2_core::readDeltaVelocity(uint8_t ins_index, Vector3f &dVel, float &dVel_dt) {
|
||||
const AP_InertialSensor &ins = _ahrs->get_ins();
|
||||
|
||||
if (ins_index < ins.get_accel_count()) {
|
||||
ins.get_delta_velocity(ins_index,dVel);
|
||||
dVel_dt = max(ins.get_delta_velocity_dt(ins_index),1.0e-4f);
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
/********************************************************
|
||||
* Global Position Measurement *
|
||||
********************************************************/
|
||||
|
||||
// check for new valid GPS data and update stored measurement if available
|
||||
void NavEKF2_core::readGpsData()
|
||||
{
|
||||
// check for new GPS data
|
||||
if ((_ahrs->get_gps().last_message_time_ms() != lastTimeGpsReceived_ms) &&
|
||||
(_ahrs->get_gps().status() >= AP_GPS::GPS_OK_FIX_3D))
|
||||
{
|
||||
// store fix time from previous read
|
||||
secondLastGpsTime_ms = lastTimeGpsReceived_ms;
|
||||
|
||||
// get current fix time
|
||||
lastTimeGpsReceived_ms = _ahrs->get_gps().last_message_time_ms();
|
||||
|
||||
// estimate when the GPS fix was valid, allowing for GPS processing and other delays
|
||||
// ideally we should be using a timing signal from the GPS receiver to set this time
|
||||
gpsDataNew.time_ms = lastTimeGpsReceived_ms - frontend._gpsDelay_ms;
|
||||
|
||||
// read the NED velocity from the GPS
|
||||
gpsDataNew.vel = _ahrs->get_gps().velocity();
|
||||
|
||||
// Use the speed accuracy from the GPS if available, otherwise set it to zero.
|
||||
// Apply a decaying envelope filter with a 5 second time constant to the raw speed accuracy data
|
||||
float alpha = constrain_float(0.0002f * (lastTimeGpsReceived_ms - secondLastGpsTime_ms),0.0f,1.0f);
|
||||
gpsSpdAccuracy *= (1.0f - alpha);
|
||||
float gpsSpdAccRaw;
|
||||
if (!_ahrs->get_gps().speed_accuracy(gpsSpdAccRaw)) {
|
||||
gpsSpdAccuracy = 0.0f;
|
||||
} else {
|
||||
gpsSpdAccuracy = max(gpsSpdAccuracy,gpsSpdAccRaw);
|
||||
}
|
||||
|
||||
// check if we have enough GPS satellites and increase the gps noise scaler if we don't
|
||||
if (_ahrs->get_gps().num_sats() >= 6 && (PV_AidingMode == AID_ABSOLUTE)) {
|
||||
gpsNoiseScaler = 1.0f;
|
||||
} else if (_ahrs->get_gps().num_sats() == 5 && (PV_AidingMode == AID_ABSOLUTE)) {
|
||||
gpsNoiseScaler = 1.4f;
|
||||
} else { // <= 4 satellites or in constant position mode
|
||||
gpsNoiseScaler = 2.0f;
|
||||
}
|
||||
|
||||
// Check if GPS can output vertical velocity and set GPS fusion mode accordingly
|
||||
if (_ahrs->get_gps().have_vertical_velocity() && frontend._fusionModeGPS == 0) {
|
||||
useGpsVertVel = true;
|
||||
} else {
|
||||
useGpsVertVel = false;
|
||||
}
|
||||
|
||||
// Monitor quality of the GPS velocity data for alignment
|
||||
if (PV_AidingMode != AID_ABSOLUTE) {
|
||||
gpsQualGood = calcGpsGoodToAlign();
|
||||
}
|
||||
|
||||
// read latitutde and longitude from GPS and convert to local NE position relative to the stored origin
|
||||
// If we don't have an origin, then set it to the current GPS coordinates
|
||||
const struct Location &gpsloc = _ahrs->get_gps().location();
|
||||
if (validOrigin) {
|
||||
gpsDataNew.pos = location_diff(EKF_origin, gpsloc);
|
||||
} else if (gpsQualGood) {
|
||||
// Set the NE origin to the current GPS position
|
||||
setOrigin();
|
||||
// Now we know the location we have an estimate for the magnetic field declination and adjust the earth field accordingly
|
||||
alignMagStateDeclination();
|
||||
// Set the height of the NED origin to ‘height of baro height datum relative to GPS height datum'
|
||||
EKF_origin.alt = gpsloc.alt - baroDataNew.hgt;
|
||||
// We are by definition at the origin at the instant of alignment so set NE position to zero
|
||||
gpsDataNew.pos.zero();
|
||||
// If GPS useage isn't explicitly prohibited, we switch to absolute position mode
|
||||
if (isAiding && frontend._fusionModeGPS != 3) {
|
||||
PV_AidingMode = AID_ABSOLUTE;
|
||||
// Initialise EKF position and velocity states
|
||||
ResetPosition();
|
||||
ResetVelocity();
|
||||
}
|
||||
}
|
||||
|
||||
// calculate a position offset which is applied to NE position and velocity wherever it is used throughout code to allow GPS position jumps to be accommodated gradually
|
||||
decayGpsOffset();
|
||||
|
||||
// save measurement to buffer to be fused later
|
||||
StoreGPS();
|
||||
|
||||
// declare GPS available for use
|
||||
gpsNotAvailable = false;
|
||||
}
|
||||
|
||||
// We need to handle the case where GPS is lost for a period of time that is too long to dead-reckon
|
||||
// If that happens we need to put the filter into a constant position mode, reset the velocity states to zero
|
||||
// and use the last estimated position as a synthetic GPS position
|
||||
|
||||
// check if we can use opticalflow as a backup
|
||||
bool optFlowBackupAvailable = (flowDataValid && !hgtTimeout);
|
||||
|
||||
// Set GPS time-out threshold depending on whether we have an airspeed sensor to constrain drift
|
||||
uint16_t gpsRetryTimeout_ms = useAirspeed() ? frontend.gpsRetryTimeUseTAS_ms : frontend.gpsRetryTimeNoTAS_ms;
|
||||
|
||||
// Set the time that copters will fly without a GPS lock before failing the GPS and switching to a non GPS mode
|
||||
uint16_t gpsFailTimeout_ms = optFlowBackupAvailable ? frontend.gpsFailTimeWithFlow_ms : gpsRetryTimeout_ms;
|
||||
|
||||
// If we haven't received GPS data for a while and we are using it for aiding, then declare the position and velocity data as being timed out
|
||||
if (imuSampleTime_ms - lastTimeGpsReceived_ms > gpsFailTimeout_ms) {
|
||||
|
||||
// Let other processes know that GPS i snota vailable and that a timeout has occurred
|
||||
posTimeout = true;
|
||||
velTimeout = true;
|
||||
gpsNotAvailable = true;
|
||||
|
||||
// If we are currently reliying on GPS for navigation, then we need to switch to a non-GPS mode of operation
|
||||
if (PV_AidingMode == AID_ABSOLUTE) {
|
||||
|
||||
// If we don't have airspeed or sideslip assumption or optical flow to constrain drift, then go into constant position mode.
|
||||
// If we can do optical flow nav (valid flow data and height above ground estimate), then go into flow nav mode.
|
||||
if (!useAirspeed() && !assume_zero_sideslip()) {
|
||||
if (optFlowBackupAvailable) {
|
||||
// we can do optical flow only nav
|
||||
frontend._fusionModeGPS = 3;
|
||||
PV_AidingMode = AID_RELATIVE;
|
||||
} else {
|
||||
// store the current position
|
||||
lastKnownPositionNE.x = stateStruct.position.x;
|
||||
lastKnownPositionNE.y = stateStruct.position.y;
|
||||
|
||||
// put the filter into constant position mode
|
||||
PV_AidingMode = AID_NONE;
|
||||
|
||||
// reset all glitch states
|
||||
gpsPosGlitchOffsetNE.zero();
|
||||
gpsVelGlitchOffset.zero();
|
||||
|
||||
// Reset the velocity and position states
|
||||
ResetVelocity();
|
||||
ResetPosition();
|
||||
|
||||
// Reset the normalised innovation to avoid false failing the bad position fusion test
|
||||
velTestRatio = 0.0f;
|
||||
posTestRatio = 0.0f;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If not aiding we synthesise the GPS measurements at the last known position
|
||||
if (PV_AidingMode == AID_NONE) {
|
||||
if (imuSampleTime_ms - gpsDataNew.time_ms > 200) {
|
||||
gpsDataNew.pos.x = lastKnownPositionNE.x;
|
||||
gpsDataNew.pos.y = lastKnownPositionNE.y;
|
||||
gpsDataNew.time_ms = imuSampleTime_ms-frontend._gpsDelay_ms;
|
||||
// save measurement to buffer to be fused later
|
||||
StoreGPS();
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
||||
// store GPS data in a history array
|
||||
void NavEKF2_core::StoreGPS()
|
||||
{
|
||||
if (gpsStoreIndex >= OBS_BUFFER_LENGTH) {
|
||||
gpsStoreIndex = 0;
|
||||
}
|
||||
storedGPS[gpsStoreIndex] = gpsDataNew;
|
||||
gpsStoreIndex += 1;
|
||||
}
|
||||
|
||||
// return newest un-used GPS data that has fallen behind the fusion time horizon
|
||||
// if no un-used data is available behind the fusion horizon, return false
|
||||
bool NavEKF2_core::RecallGPS()
|
||||
{
|
||||
gps_elements dataTemp;
|
||||
gps_elements dataTempZero;
|
||||
dataTempZero.time_ms = 0;
|
||||
uint32_t temp_ms = 0;
|
||||
for (uint8_t i=0; i<OBS_BUFFER_LENGTH; i++) {
|
||||
dataTemp = storedGPS[i];
|
||||
// find a measurement older than the fusion time horizon that we haven't checked before
|
||||
if (dataTemp.time_ms != 0 && dataTemp.time_ms <= imuDataDelayed.time_ms) {
|
||||
// zero the time stamp so we won't use it again
|
||||
storedGPS[i]=dataTempZero;
|
||||
// Find the most recent non-stale measurement that meets the time horizon criteria
|
||||
if (((imuDataDelayed.time_ms - dataTemp.time_ms) < 500) && dataTemp.time_ms > temp_ms) {
|
||||
gpsDataDelayed = dataTemp;
|
||||
temp_ms = dataTemp.time_ms;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (temp_ms != 0) {
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// return the Euler roll, pitch and yaw angle in radians
|
||||
void NavEKF2_core::getEulerAngles(Vector3f &euler) const
|
||||
{
|
||||
outputDataNew.quat.to_euler(euler.x, euler.y, euler.z);
|
||||
euler = euler - _ahrs->get_trim();
|
||||
}
|
||||
|
||||
// return body axis gyro bias estimates in rad/sec
|
||||
void NavEKF2_core::getGyroBias(Vector3f &gyroBias) const
|
||||
{
|
||||
if (dtIMUavg < 1e-6f) {
|
||||
gyroBias.zero();
|
||||
return;
|
||||
}
|
||||
gyroBias = stateStruct.gyro_bias / dtIMUavg;
|
||||
}
|
||||
|
||||
// return body axis gyro scale factor error as a percentage
|
||||
void NavEKF2_core::getGyroScaleErrorPercentage(Vector3f &gyroScale) const
|
||||
{
|
||||
if (!statesInitialised) {
|
||||
gyroScale.x = gyroScale.y = gyroScale.z = 0;
|
||||
return;
|
||||
}
|
||||
gyroScale.x = 100.0f/stateStruct.gyro_scale.x - 100.0f;
|
||||
gyroScale.y = 100.0f/stateStruct.gyro_scale.y - 100.0f;
|
||||
gyroScale.z = 100.0f/stateStruct.gyro_scale.z - 100.0f;
|
||||
}
|
||||
|
||||
// return tilt error convergence metric
|
||||
void NavEKF2_core::getTiltError(float &ang) const
|
||||
{
|
||||
ang = tiltErrFilt;
|
||||
}
|
||||
|
||||
bool NavEKF2_core::readDeltaAngle(uint8_t ins_index, Vector3f &dAng) {
|
||||
const AP_InertialSensor &ins = _ahrs->get_ins();
|
||||
|
||||
if (ins_index < ins.get_gyro_count()) {
|
||||
ins.get_delta_angle(ins_index,dAng);
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
/********************************************************
|
||||
* Height Measurements *
|
||||
********************************************************/
|
||||
|
||||
// check for new altitude measurement data and update stored measurement if available
|
||||
void NavEKF2_core::readHgtData()
|
||||
{
|
||||
// check to see if baro measurement has changed so we know if a new measurement has arrived
|
||||
if (_baro.get_last_update() != lastHgtReceived_ms) {
|
||||
// Don't use Baro height if operating in optical flow mode as we use range finder instead
|
||||
if (frontend._fusionModeGPS == 3 && frontend._altSource == 1) {
|
||||
if ((imuSampleTime_ms - rngValidMeaTime_ms) < 2000) {
|
||||
// adjust range finder measurement to allow for effect of vehicle tilt and height of sensor
|
||||
baroDataNew.hgt = max(rngMea * Tnb_flow.c.z, rngOnGnd);
|
||||
// calculate offset to baro data that enables baro to be used as a backup
|
||||
// filter offset to reduce effect of baro noise and other transient errors on estimate
|
||||
baroHgtOffset = 0.1f * (_baro.get_altitude() + stateStruct.position.z) + 0.9f * baroHgtOffset;
|
||||
} else if (isAiding && takeOffDetected) {
|
||||
// use baro measurement and correct for baro offset - failsafe use only as baro will drift
|
||||
baroDataNew.hgt = max(_baro.get_altitude() - baroHgtOffset, rngOnGnd);
|
||||
} else {
|
||||
// If we are on ground and have no range finder reading, assume the nominal on-ground height
|
||||
baroDataNew.hgt = rngOnGnd;
|
||||
// calculate offset to baro data that enables baro to be used as a backup
|
||||
// filter offset to reduce effect of baro noise and other transient errors on estimate
|
||||
baroHgtOffset = 0.1f * (_baro.get_altitude() + stateStruct.position.z) + 0.9f * baroHgtOffset;
|
||||
}
|
||||
} else {
|
||||
// use baro measurement and correct for baro offset
|
||||
baroDataNew.hgt = _baro.get_altitude();
|
||||
}
|
||||
|
||||
// filtered baro data used to provide a reference for takeoff
|
||||
// it is is reset to last height measurement on disarming in performArmingChecks()
|
||||
if (!getTakeoffExpected()) {
|
||||
const float gndHgtFiltTC = 0.5f;
|
||||
const float dtBaro = frontend.hgtAvg_ms*1.0e-3f;
|
||||
float alpha = constrain_float(dtBaro / (dtBaro+gndHgtFiltTC),0.0f,1.0f);
|
||||
meaHgtAtTakeOff += (baroDataDelayed.hgt-meaHgtAtTakeOff)*alpha;
|
||||
} else if (isAiding && getTakeoffExpected()) {
|
||||
// If we are in takeoff mode, the height measurement is limited to be no less than the measurement at start of takeoff
|
||||
// This prevents negative baro disturbances due to copter downwash corrupting the EKF altitude during initial ascent
|
||||
baroDataNew.hgt = max(baroDataNew.hgt, meaHgtAtTakeOff);
|
||||
}
|
||||
|
||||
// time stamp used to check for new measurement
|
||||
lastHgtReceived_ms = _baro.get_last_update();
|
||||
|
||||
// estimate of time height measurement was taken, allowing for delays
|
||||
hgtMeasTime_ms = lastHgtReceived_ms - frontend._hgtDelay_ms;
|
||||
|
||||
// save baro measurement to buffer to be fused later
|
||||
baroDataNew.time_ms = hgtMeasTime_ms;
|
||||
StoreBaro();
|
||||
}
|
||||
}
|
||||
|
||||
// store baro in a history array
|
||||
void NavEKF2_core::StoreBaro()
|
||||
{
|
||||
if (baroStoreIndex >= OBS_BUFFER_LENGTH) {
|
||||
baroStoreIndex = 0;
|
||||
}
|
||||
storedBaro[baroStoreIndex] = baroDataNew;
|
||||
baroStoreIndex += 1;
|
||||
}
|
||||
|
||||
// return newest un-used baro data that has fallen behind the fusion time horizon
|
||||
// if no un-used data is available behind the fusion horizon, return false
|
||||
bool NavEKF2_core::RecallBaro()
|
||||
{
|
||||
baro_elements dataTemp;
|
||||
baro_elements dataTempZero;
|
||||
dataTempZero.time_ms = 0;
|
||||
uint32_t temp_ms = 0;
|
||||
for (uint8_t i=0; i<OBS_BUFFER_LENGTH; i++) {
|
||||
dataTemp = storedBaro[i];
|
||||
// find a measurement older than the fusion time horizon that we haven't checked before
|
||||
if (dataTemp.time_ms != 0 && dataTemp.time_ms <= imuDataDelayed.time_ms) {
|
||||
// zero the time stamp so we won't use it again
|
||||
storedBaro[i]=dataTempZero;
|
||||
// Find the most recent non-stale measurement that meets the time horizon criteria
|
||||
if (((imuDataDelayed.time_ms - dataTemp.time_ms) < 500) && dataTemp.time_ms > temp_ms) {
|
||||
baroDataDelayed = dataTemp;
|
||||
temp_ms = dataTemp.time_ms;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (temp_ms != 0) {
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
/********************************************************
|
||||
* Air Speed Measurements *
|
||||
********************************************************/
|
||||
|
||||
// check for new airspeed data and update stored measurements if available
|
||||
void NavEKF2_core::readAirSpdData()
|
||||
{
|
||||
// if airspeed reading is valid and is set by the user to be used and has been updated then
|
||||
// we take a new reading, convert from EAS to TAS and set the flag letting other functions
|
||||
// know a new measurement is available
|
||||
const AP_Airspeed *aspeed = _ahrs->get_airspeed();
|
||||
if (aspeed &&
|
||||
aspeed->use() &&
|
||||
aspeed->last_update_ms() != timeTasReceived_ms) {
|
||||
tasDataNew.tas = aspeed->get_airspeed() * aspeed->get_EAS2TAS();
|
||||
timeTasReceived_ms = aspeed->last_update_ms();
|
||||
tasDataNew.time_ms = timeTasReceived_ms - frontend.tasDelay_ms;
|
||||
newDataTas = true;
|
||||
StoreTAS();
|
||||
RecallTAS();
|
||||
} else {
|
||||
newDataTas = false;
|
||||
}
|
||||
}
|
||||
|
||||
#endif // HAL_CPU_CLASS
|
||||
|
|
@ -18,177 +18,6 @@
|
|||
|
||||
extern const AP_HAL::HAL& hal;
|
||||
|
||||
// return data for debugging optical flow fusion
|
||||
void NavEKF2_core::getFlowDebug(float &varFlow, float &gndOffset, float &flowInnovX, float &flowInnovY, float &auxInnov, float &HAGL, float &rngInnov, float &range, float &gndOffsetErr) const
|
||||
{
|
||||
varFlow = max(flowTestRatio[0],flowTestRatio[1]);
|
||||
gndOffset = terrainState;
|
||||
flowInnovX = innovOptFlow[0];
|
||||
flowInnovY = innovOptFlow[1];
|
||||
auxInnov = auxFlowObsInnov;
|
||||
HAGL = terrainState - stateStruct.position.z;
|
||||
rngInnov = innovRng;
|
||||
range = rngMea;
|
||||
gndOffsetErr = sqrtf(Popt); // note Popt is constrained to be non-negative in EstimateTerrainOffset()
|
||||
}
|
||||
|
||||
// provides the height limit to be observed by the control loops
|
||||
// returns false if no height limiting is required
|
||||
// this is needed to ensure the vehicle does not fly too high when using optical flow navigation
|
||||
bool NavEKF2_core::getHeightControlLimit(float &height) const
|
||||
{
|
||||
// only ask for limiting if we are doing optical flow navigation
|
||||
if (frontend._fusionModeGPS == 3) {
|
||||
// If are doing optical flow nav, ensure the height above ground is within range finder limits after accounting for vehicle tilt and control errors
|
||||
height = max(float(_rng.max_distance_cm()) * 0.007f - 1.0f, 1.0f);
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// Read the range finder and take new measurements if available
|
||||
// Read at 20Hz and apply a median filter
|
||||
void NavEKF2_core::readRangeFinder(void)
|
||||
{
|
||||
uint8_t midIndex;
|
||||
uint8_t maxIndex;
|
||||
uint8_t minIndex;
|
||||
// get theoretical correct range when the vehicle is on the ground
|
||||
rngOnGnd = _rng.ground_clearance_cm() * 0.01f;
|
||||
if (_rng.status() == RangeFinder::RangeFinder_Good && (imuSampleTime_ms - lastRngMeasTime_ms) > 50) {
|
||||
// store samples and sample time into a ring buffer
|
||||
rngMeasIndex ++;
|
||||
if (rngMeasIndex > 2) {
|
||||
rngMeasIndex = 0;
|
||||
}
|
||||
storedRngMeasTime_ms[rngMeasIndex] = imuSampleTime_ms;
|
||||
storedRngMeas[rngMeasIndex] = _rng.distance_cm() * 0.01f;
|
||||
// check for three fresh samples and take median
|
||||
bool sampleFresh[3];
|
||||
for (uint8_t index = 0; index <= 2; index++) {
|
||||
sampleFresh[index] = (imuSampleTime_ms - storedRngMeasTime_ms[index]) < 500;
|
||||
}
|
||||
if (sampleFresh[0] && sampleFresh[1] && sampleFresh[2]) {
|
||||
if (storedRngMeas[0] > storedRngMeas[1]) {
|
||||
minIndex = 1;
|
||||
maxIndex = 0;
|
||||
} else {
|
||||
maxIndex = 0;
|
||||
minIndex = 1;
|
||||
}
|
||||
if (storedRngMeas[2] > storedRngMeas[maxIndex]) {
|
||||
midIndex = maxIndex;
|
||||
} else if (storedRngMeas[2] < storedRngMeas[minIndex]) {
|
||||
midIndex = minIndex;
|
||||
} else {
|
||||
midIndex = 2;
|
||||
}
|
||||
rngMea = max(storedRngMeas[midIndex],rngOnGnd);
|
||||
newDataRng = true;
|
||||
rngValidMeaTime_ms = imuSampleTime_ms;
|
||||
} else if (onGround) {
|
||||
// if on ground and no return, we assume on ground range
|
||||
rngMea = rngOnGnd;
|
||||
newDataRng = true;
|
||||
rngValidMeaTime_ms = imuSampleTime_ms;
|
||||
} else {
|
||||
newDataRng = false;
|
||||
}
|
||||
lastRngMeasTime_ms = imuSampleTime_ms;
|
||||
}
|
||||
}
|
||||
|
||||
// write the raw optical flow measurements
|
||||
// this needs to be called externally.
|
||||
void NavEKF2_core::writeOptFlowMeas(uint8_t &rawFlowQuality, Vector2f &rawFlowRates, Vector2f &rawGyroRates, uint32_t &msecFlowMeas)
|
||||
{
|
||||
// The raw measurements need to be optical flow rates in radians/second averaged across the time since the last update
|
||||
// The PX4Flow sensor outputs flow rates with the following axis and sign conventions:
|
||||
// A positive X rate is produced by a positive sensor rotation about the X axis
|
||||
// A positive Y rate is produced by a positive sensor rotation about the Y axis
|
||||
// This filter uses a different definition of optical flow rates to the sensor with a positive optical flow rate produced by a
|
||||
// negative rotation about that axis. For example a positive rotation of the flight vehicle about its X (roll) axis would produce a negative X flow rate
|
||||
flowMeaTime_ms = imuSampleTime_ms;
|
||||
// calculate bias errors on flow sensor gyro rates, but protect against spikes in data
|
||||
// reset the accumulated body delta angle and time
|
||||
// don't do the calculation if not enough time lapsed for a reliable body rate measurement
|
||||
if (delTimeOF > 0.01f) {
|
||||
flowGyroBias.x = 0.99f * flowGyroBias.x + 0.01f * constrain_float((rawGyroRates.x - delAngBodyOF.x/delTimeOF),-0.1f,0.1f);
|
||||
flowGyroBias.y = 0.99f * flowGyroBias.y + 0.01f * constrain_float((rawGyroRates.y - delAngBodyOF.y/delTimeOF),-0.1f,0.1f);
|
||||
delAngBodyOF.zero();
|
||||
delTimeOF = 0.0f;
|
||||
}
|
||||
// check for takeoff if relying on optical flow and zero measurements until takeoff detected
|
||||
// if we haven't taken off - constrain position and velocity states
|
||||
if (frontend._fusionModeGPS == 3) {
|
||||
detectOptFlowTakeoff();
|
||||
}
|
||||
// calculate rotation matrices at mid sample time for flow observations
|
||||
stateStruct.quat.rotation_matrix(Tbn_flow);
|
||||
Tnb_flow = Tbn_flow.transposed();
|
||||
// don't use data with a low quality indicator or extreme rates (helps catch corrupt sensor data)
|
||||
if ((rawFlowQuality > 0) && rawFlowRates.length() < 4.2f && rawGyroRates.length() < 4.2f) {
|
||||
// correct flow sensor rates for bias
|
||||
omegaAcrossFlowTime.x = rawGyroRates.x - flowGyroBias.x;
|
||||
omegaAcrossFlowTime.y = rawGyroRates.y - flowGyroBias.y;
|
||||
// write uncorrected flow rate measurements that will be used by the focal length scale factor estimator
|
||||
// note correction for different axis and sign conventions used by the px4flow sensor
|
||||
ofDataNew.flowRadXY = - rawFlowRates; // raw (non motion compensated) optical flow angular rate about the X axis (rad/sec)
|
||||
// write flow rate measurements corrected for body rates
|
||||
ofDataNew.flowRadXYcomp.x = ofDataNew.flowRadXY.x + omegaAcrossFlowTime.x;
|
||||
ofDataNew.flowRadXYcomp.y = ofDataNew.flowRadXY.y + omegaAcrossFlowTime.y;
|
||||
// record time last observation was received so we can detect loss of data elsewhere
|
||||
flowValidMeaTime_ms = imuSampleTime_ms;
|
||||
// estimate sample time of the measurement
|
||||
ofDataNew.time_ms = imuSampleTime_ms - frontend._flowDelay_ms - frontend.flowTimeDeltaAvg_ms/2;
|
||||
// Save data to buffer
|
||||
StoreOF();
|
||||
// Check for data at the fusion time horizon
|
||||
newDataFlow = RecallOF();
|
||||
}
|
||||
}
|
||||
|
||||
// store OF data in a history array
|
||||
void NavEKF2_core::StoreOF()
|
||||
{
|
||||
if (ofStoreIndex >= OBS_BUFFER_LENGTH) {
|
||||
ofStoreIndex = 0;
|
||||
}
|
||||
storedOF[ofStoreIndex] = ofDataNew;
|
||||
ofStoreIndex += 1;
|
||||
}
|
||||
|
||||
// return newest un-used optical flow data that has fallen behind the fusion time horizon
|
||||
// if no un-used data is available behind the fusion horizon, return false
|
||||
bool NavEKF2_core::RecallOF()
|
||||
{
|
||||
of_elements dataTemp;
|
||||
of_elements dataTempZero;
|
||||
dataTempZero.time_ms = 0;
|
||||
uint32_t temp_ms = 0;
|
||||
for (uint8_t i=0; i<OBS_BUFFER_LENGTH; i++) {
|
||||
dataTemp = storedOF[i];
|
||||
// find a measurement older than the fusion time horizon that we haven't checked before
|
||||
if (dataTemp.time_ms != 0 && dataTemp.time_ms <= imuDataDelayed.time_ms) {
|
||||
// zero the time stamp so we won't use it again
|
||||
storedOF[i]=dataTempZero;
|
||||
// Find the most recent non-stale measurement that meets the time horizon criteria
|
||||
if (((imuDataDelayed.time_ms - dataTemp.time_ms) < 500) && dataTemp.time_ms > temp_ms) {
|
||||
ofDataDelayed = dataTemp;
|
||||
temp_ms = dataTemp.time_ms;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (temp_ms != 0) {
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// select fusion of optical flow measurements
|
||||
void NavEKF2_core::SelectFlowFusion()
|
||||
{
|
||||
|
|
|
|||
|
|
@ -108,71 +108,9 @@ bool NavEKF2_core::resetHeightDatum(void)
|
|||
|
||||
|
||||
/********************************************************
|
||||
* GET STATES/PARAMS FUNCTIONS *
|
||||
* GET PARAMS FUNCTIONS *
|
||||
********************************************************/
|
||||
|
||||
// return NED velocity in m/s
|
||||
//
|
||||
void NavEKF2_core::getVelNED(Vector3f &vel) const
|
||||
{
|
||||
vel = outputDataNew.velocity;
|
||||
}
|
||||
|
||||
// This returns the specific forces in the NED frame
|
||||
void NavEKF2_core::getAccelNED(Vector3f &accelNED) const {
|
||||
accelNED = velDotNED;
|
||||
accelNED.z -= GRAVITY_MSS;
|
||||
}
|
||||
|
||||
// return the Z-accel bias estimate in m/s^2
|
||||
void NavEKF2_core::getAccelZBias(float &zbias) const {
|
||||
if (dtIMUavg > 0) {
|
||||
zbias = stateStruct.accel_zbias / dtIMUavg;
|
||||
} else {
|
||||
zbias = 0;
|
||||
}
|
||||
}
|
||||
|
||||
// Return the last calculated NED position relative to the reference point (m).
|
||||
// if a calculated solution is not available, use the best available data and return false
|
||||
bool NavEKF2_core::getPosNED(Vector3f &pos) const
|
||||
{
|
||||
// The EKF always has a height estimate regardless of mode of operation
|
||||
pos.z = outputDataNew.position.z;
|
||||
// There are three modes of operation, absolute position (GPS fusion), relative position (optical flow fusion) and constant position (no position estimate available)
|
||||
nav_filter_status status;
|
||||
getFilterStatus(status);
|
||||
if (status.flags.horiz_pos_abs || status.flags.horiz_pos_rel) {
|
||||
// This is the normal mode of operation where we can use the EKF position states
|
||||
pos.x = outputDataNew.position.x;
|
||||
pos.y = outputDataNew.position.y;
|
||||
return true;
|
||||
} else {
|
||||
// In constant position mode the EKF position states are at the origin, so we cannot use them as a position estimate
|
||||
if(validOrigin) {
|
||||
if ((_ahrs->get_gps().status() >= AP_GPS::GPS_OK_FIX_2D)) {
|
||||
// If the origin has been set and we have GPS, then return the GPS position relative to the origin
|
||||
const struct Location &gpsloc = _ahrs->get_gps().location();
|
||||
Vector2f tempPosNE = location_diff(EKF_origin, gpsloc);
|
||||
pos.x = tempPosNE.x;
|
||||
pos.y = tempPosNE.y;
|
||||
return false;
|
||||
} else {
|
||||
// If no GPS fix is available, all we can do is provide the last known position
|
||||
pos.x = outputDataNew.position.x;
|
||||
pos.y = outputDataNew.position.y;
|
||||
return false;
|
||||
}
|
||||
} else {
|
||||
// If the origin has not been set, then we have no means of providing a relative position
|
||||
pos.x = 0.0f;
|
||||
pos.y = 0.0f;
|
||||
return false;
|
||||
}
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
// return the horizontal speed limit in m/s set by optical flow sensor limits
|
||||
// return the scale factor to be applied to navigation velocity gains to compensate for increase in velocity noise with height when using optical flow
|
||||
void NavEKF2_core::getEkfControlLimits(float &ekfGndSpdLimit, float &ekfNavVelGainScaler) const
|
||||
|
|
@ -188,53 +126,6 @@ void NavEKF2_core::getEkfControlLimits(float &ekfGndSpdLimit, float &ekfNavVelGa
|
|||
}
|
||||
}
|
||||
|
||||
// Return the last calculated latitude, longitude and height in WGS-84
|
||||
// If a calculated location isn't available, return a raw GPS measurement
|
||||
// The status will return true if a calculation or raw measurement is available
|
||||
// The getFilterStatus() function provides a more detailed description of data health and must be checked if data is to be used for flight control
|
||||
bool NavEKF2_core::getLLH(struct Location &loc) const
|
||||
{
|
||||
if(validOrigin) {
|
||||
// Altitude returned is an absolute altitude relative to the WGS-84 spherioid
|
||||
loc.alt = EKF_origin.alt - outputDataNew.position.z*100;
|
||||
loc.flags.relative_alt = 0;
|
||||
loc.flags.terrain_alt = 0;
|
||||
|
||||
// there are three modes of operation, absolute position (GPS fusion), relative position (optical flow fusion) and constant position (no aiding)
|
||||
nav_filter_status status;
|
||||
getFilterStatus(status);
|
||||
if (status.flags.horiz_pos_abs || status.flags.horiz_pos_rel) {
|
||||
loc.lat = EKF_origin.lat;
|
||||
loc.lng = EKF_origin.lng;
|
||||
location_offset(loc, outputDataNew.position.x, outputDataNew.position.y);
|
||||
return true;
|
||||
} else {
|
||||
// we could be in constant position mode becasue the vehicle has taken off without GPS, or has lost GPS
|
||||
// in this mode we cannot use the EKF states to estimate position so will return the best available data
|
||||
if ((_ahrs->get_gps().status() >= AP_GPS::GPS_OK_FIX_2D)) {
|
||||
// we have a GPS position fix to return
|
||||
const struct Location &gpsloc = _ahrs->get_gps().location();
|
||||
loc.lat = gpsloc.lat;
|
||||
loc.lng = gpsloc.lng;
|
||||
return true;
|
||||
} else {
|
||||
// if no GPS fix, provide last known position before entering the mode
|
||||
location_offset(loc, lastKnownPositionNE.x, lastKnownPositionNE.y);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// If no origin has been defined for the EKF, then we cannot use its position states so return a raw
|
||||
// GPS reading if available and return false
|
||||
if ((_ahrs->get_gps().status() >= AP_GPS::GPS_OK_FIX_3D)) {
|
||||
const struct Location &gpsloc = _ahrs->get_gps().location();
|
||||
loc = gpsloc;
|
||||
loc.flags.relative_alt = 0;
|
||||
loc.flags.terrain_alt = 0;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// return the LLH location of the filters NED origin
|
||||
bool NavEKF2_core::getOriginLLH(struct Location &loc) const
|
||||
|
|
@ -245,14 +136,6 @@ bool NavEKF2_core::getOriginLLH(struct Location &loc) const
|
|||
return validOrigin;
|
||||
}
|
||||
|
||||
// return the estimated height above ground level
|
||||
bool NavEKF2_core::getHAGL(float &HAGL) const
|
||||
{
|
||||
HAGL = terrainState - outputDataNew.position.z;
|
||||
// If we know the terrain offset and altitude, then we have a valid height above ground estimate
|
||||
return !hgtTimeout && gndOffsetValid && healthy();
|
||||
}
|
||||
|
||||
/********************************************************
|
||||
* SET STATES/PARAMS FUNCTIONS *
|
||||
********************************************************/
|
||||
|
|
@ -299,305 +182,6 @@ uint8_t NavEKF2_core::setInhibitGPS(void)
|
|||
}
|
||||
}
|
||||
|
||||
|
||||
/********************************************************
|
||||
* READ SENSORS *
|
||||
********************************************************/
|
||||
|
||||
bool NavEKF2_core::readDeltaVelocity(uint8_t ins_index, Vector3f &dVel, float &dVel_dt) {
|
||||
const AP_InertialSensor &ins = _ahrs->get_ins();
|
||||
|
||||
if (ins_index < ins.get_accel_count()) {
|
||||
ins.get_delta_velocity(ins_index,dVel);
|
||||
dVel_dt = max(ins.get_delta_velocity_dt(ins_index),1.0e-4f);
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
// check for new valid GPS data and update stored measurement if available
|
||||
void NavEKF2_core::readGpsData()
|
||||
{
|
||||
// check for new GPS data
|
||||
if ((_ahrs->get_gps().last_message_time_ms() != lastTimeGpsReceived_ms) &&
|
||||
(_ahrs->get_gps().status() >= AP_GPS::GPS_OK_FIX_3D))
|
||||
{
|
||||
// store fix time from previous read
|
||||
secondLastGpsTime_ms = lastTimeGpsReceived_ms;
|
||||
|
||||
// get current fix time
|
||||
lastTimeGpsReceived_ms = _ahrs->get_gps().last_message_time_ms();
|
||||
|
||||
// estimate when the GPS fix was valid, allowing for GPS processing and other delays
|
||||
// ideally we should be using a timing signal from the GPS receiver to set this time
|
||||
gpsDataNew.time_ms = lastTimeGpsReceived_ms - frontend._gpsDelay_ms;
|
||||
|
||||
// read the NED velocity from the GPS
|
||||
gpsDataNew.vel = _ahrs->get_gps().velocity();
|
||||
|
||||
// Use the speed accuracy from the GPS if available, otherwise set it to zero.
|
||||
// Apply a decaying envelope filter with a 5 second time constant to the raw speed accuracy data
|
||||
float alpha = constrain_float(0.0002f * (lastTimeGpsReceived_ms - secondLastGpsTime_ms),0.0f,1.0f);
|
||||
gpsSpdAccuracy *= (1.0f - alpha);
|
||||
float gpsSpdAccRaw;
|
||||
if (!_ahrs->get_gps().speed_accuracy(gpsSpdAccRaw)) {
|
||||
gpsSpdAccuracy = 0.0f;
|
||||
} else {
|
||||
gpsSpdAccuracy = max(gpsSpdAccuracy,gpsSpdAccRaw);
|
||||
}
|
||||
|
||||
// check if we have enough GPS satellites and increase the gps noise scaler if we don't
|
||||
if (_ahrs->get_gps().num_sats() >= 6 && (PV_AidingMode == AID_ABSOLUTE)) {
|
||||
gpsNoiseScaler = 1.0f;
|
||||
} else if (_ahrs->get_gps().num_sats() == 5 && (PV_AidingMode == AID_ABSOLUTE)) {
|
||||
gpsNoiseScaler = 1.4f;
|
||||
} else { // <= 4 satellites or in constant position mode
|
||||
gpsNoiseScaler = 2.0f;
|
||||
}
|
||||
|
||||
// Check if GPS can output vertical velocity and set GPS fusion mode accordingly
|
||||
if (_ahrs->get_gps().have_vertical_velocity() && frontend._fusionModeGPS == 0) {
|
||||
useGpsVertVel = true;
|
||||
} else {
|
||||
useGpsVertVel = false;
|
||||
}
|
||||
|
||||
// Monitor quality of the GPS velocity data for alignment
|
||||
if (PV_AidingMode != AID_ABSOLUTE) {
|
||||
gpsQualGood = calcGpsGoodToAlign();
|
||||
}
|
||||
|
||||
// read latitutde and longitude from GPS and convert to local NE position relative to the stored origin
|
||||
// If we don't have an origin, then set it to the current GPS coordinates
|
||||
const struct Location &gpsloc = _ahrs->get_gps().location();
|
||||
if (validOrigin) {
|
||||
gpsDataNew.pos = location_diff(EKF_origin, gpsloc);
|
||||
} else if (gpsQualGood) {
|
||||
// Set the NE origin to the current GPS position
|
||||
setOrigin();
|
||||
// Now we know the location we have an estimate for the magnetic field declination and adjust the earth field accordingly
|
||||
alignMagStateDeclination();
|
||||
// Set the height of the NED origin to ‘height of baro height datum relative to GPS height datum'
|
||||
EKF_origin.alt = gpsloc.alt - baroDataNew.hgt;
|
||||
// We are by definition at the origin at the instant of alignment so set NE position to zero
|
||||
gpsDataNew.pos.zero();
|
||||
// If GPS useage isn't explicitly prohibited, we switch to absolute position mode
|
||||
if (isAiding && frontend._fusionModeGPS != 3) {
|
||||
PV_AidingMode = AID_ABSOLUTE;
|
||||
// Initialise EKF position and velocity states
|
||||
ResetPosition();
|
||||
ResetVelocity();
|
||||
}
|
||||
}
|
||||
|
||||
// calculate a position offset which is applied to NE position and velocity wherever it is used throughout code to allow GPS position jumps to be accommodated gradually
|
||||
decayGpsOffset();
|
||||
|
||||
// save measurement to buffer to be fused later
|
||||
StoreGPS();
|
||||
|
||||
// declare GPS available for use
|
||||
gpsNotAvailable = false;
|
||||
}
|
||||
|
||||
// We need to handle the case where GPS is lost for a period of time that is too long to dead-reckon
|
||||
// If that happens we need to put the filter into a constant position mode, reset the velocity states to zero
|
||||
// and use the last estimated position as a synthetic GPS position
|
||||
|
||||
// check if we can use opticalflow as a backup
|
||||
bool optFlowBackupAvailable = (flowDataValid && !hgtTimeout);
|
||||
|
||||
// Set GPS time-out threshold depending on whether we have an airspeed sensor to constrain drift
|
||||
uint16_t gpsRetryTimeout_ms = useAirspeed() ? frontend.gpsRetryTimeUseTAS_ms : frontend.gpsRetryTimeNoTAS_ms;
|
||||
|
||||
// Set the time that copters will fly without a GPS lock before failing the GPS and switching to a non GPS mode
|
||||
uint16_t gpsFailTimeout_ms = optFlowBackupAvailable ? frontend.gpsFailTimeWithFlow_ms : gpsRetryTimeout_ms;
|
||||
|
||||
// If we haven't received GPS data for a while and we are using it for aiding, then declare the position and velocity data as being timed out
|
||||
if (imuSampleTime_ms - lastTimeGpsReceived_ms > gpsFailTimeout_ms) {
|
||||
|
||||
// Let other processes know that GPS i snota vailable and that a timeout has occurred
|
||||
posTimeout = true;
|
||||
velTimeout = true;
|
||||
gpsNotAvailable = true;
|
||||
|
||||
// If we are currently reliying on GPS for navigation, then we need to switch to a non-GPS mode of operation
|
||||
if (PV_AidingMode == AID_ABSOLUTE) {
|
||||
|
||||
// If we don't have airspeed or sideslip assumption or optical flow to constrain drift, then go into constant position mode.
|
||||
// If we can do optical flow nav (valid flow data and height above ground estimate), then go into flow nav mode.
|
||||
if (!useAirspeed() && !assume_zero_sideslip()) {
|
||||
if (optFlowBackupAvailable) {
|
||||
// we can do optical flow only nav
|
||||
frontend._fusionModeGPS = 3;
|
||||
PV_AidingMode = AID_RELATIVE;
|
||||
} else {
|
||||
// store the current position
|
||||
lastKnownPositionNE.x = stateStruct.position.x;
|
||||
lastKnownPositionNE.y = stateStruct.position.y;
|
||||
|
||||
// put the filter into constant position mode
|
||||
PV_AidingMode = AID_NONE;
|
||||
|
||||
// reset all glitch states
|
||||
gpsPosGlitchOffsetNE.zero();
|
||||
gpsVelGlitchOffset.zero();
|
||||
|
||||
// Reset the velocity and position states
|
||||
ResetVelocity();
|
||||
ResetPosition();
|
||||
|
||||
// Reset the normalised innovation to avoid false failing the bad position fusion test
|
||||
velTestRatio = 0.0f;
|
||||
posTestRatio = 0.0f;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If not aiding we synthesise the GPS measurements at the last known position
|
||||
if (PV_AidingMode == AID_NONE) {
|
||||
if (imuSampleTime_ms - gpsDataNew.time_ms > 200) {
|
||||
gpsDataNew.pos.x = lastKnownPositionNE.x;
|
||||
gpsDataNew.pos.y = lastKnownPositionNE.y;
|
||||
gpsDataNew.time_ms = imuSampleTime_ms-frontend._gpsDelay_ms;
|
||||
// save measurement to buffer to be fused later
|
||||
StoreGPS();
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
||||
// store GPS data in a history array
|
||||
void NavEKF2_core::StoreGPS()
|
||||
{
|
||||
if (gpsStoreIndex >= OBS_BUFFER_LENGTH) {
|
||||
gpsStoreIndex = 0;
|
||||
}
|
||||
storedGPS[gpsStoreIndex] = gpsDataNew;
|
||||
gpsStoreIndex += 1;
|
||||
}
|
||||
|
||||
// return newest un-used GPS data that has fallen behind the fusion time horizon
|
||||
// if no un-used data is available behind the fusion horizon, return false
|
||||
bool NavEKF2_core::RecallGPS()
|
||||
{
|
||||
gps_elements dataTemp;
|
||||
gps_elements dataTempZero;
|
||||
dataTempZero.time_ms = 0;
|
||||
uint32_t temp_ms = 0;
|
||||
for (uint8_t i=0; i<OBS_BUFFER_LENGTH; i++) {
|
||||
dataTemp = storedGPS[i];
|
||||
// find a measurement older than the fusion time horizon that we haven't checked before
|
||||
if (dataTemp.time_ms != 0 && dataTemp.time_ms <= imuDataDelayed.time_ms) {
|
||||
// zero the time stamp so we won't use it again
|
||||
storedGPS[i]=dataTempZero;
|
||||
// Find the most recent non-stale measurement that meets the time horizon criteria
|
||||
if (((imuDataDelayed.time_ms - dataTemp.time_ms) < 500) && dataTemp.time_ms > temp_ms) {
|
||||
gpsDataDelayed = dataTemp;
|
||||
temp_ms = dataTemp.time_ms;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (temp_ms != 0) {
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// check for new altitude measurement data and update stored measurement if available
|
||||
void NavEKF2_core::readHgtData()
|
||||
{
|
||||
// check to see if baro measurement has changed so we know if a new measurement has arrived
|
||||
if (_baro.get_last_update() != lastHgtReceived_ms) {
|
||||
// Don't use Baro height if operating in optical flow mode as we use range finder instead
|
||||
if (frontend._fusionModeGPS == 3 && frontend._altSource == 1) {
|
||||
if ((imuSampleTime_ms - rngValidMeaTime_ms) < 2000) {
|
||||
// adjust range finder measurement to allow for effect of vehicle tilt and height of sensor
|
||||
baroDataNew.hgt = max(rngMea * Tnb_flow.c.z, rngOnGnd);
|
||||
// calculate offset to baro data that enables baro to be used as a backup
|
||||
// filter offset to reduce effect of baro noise and other transient errors on estimate
|
||||
baroHgtOffset = 0.1f * (_baro.get_altitude() + stateStruct.position.z) + 0.9f * baroHgtOffset;
|
||||
} else if (isAiding && takeOffDetected) {
|
||||
// use baro measurement and correct for baro offset - failsafe use only as baro will drift
|
||||
baroDataNew.hgt = max(_baro.get_altitude() - baroHgtOffset, rngOnGnd);
|
||||
} else {
|
||||
// If we are on ground and have no range finder reading, assume the nominal on-ground height
|
||||
baroDataNew.hgt = rngOnGnd;
|
||||
// calculate offset to baro data that enables baro to be used as a backup
|
||||
// filter offset to reduce effect of baro noise and other transient errors on estimate
|
||||
baroHgtOffset = 0.1f * (_baro.get_altitude() + stateStruct.position.z) + 0.9f * baroHgtOffset;
|
||||
}
|
||||
} else {
|
||||
// use baro measurement and correct for baro offset
|
||||
baroDataNew.hgt = _baro.get_altitude();
|
||||
}
|
||||
|
||||
// filtered baro data used to provide a reference for takeoff
|
||||
// it is is reset to last height measurement on disarming in performArmingChecks()
|
||||
if (!getTakeoffExpected()) {
|
||||
const float gndHgtFiltTC = 0.5f;
|
||||
const float dtBaro = frontend.hgtAvg_ms*1.0e-3f;
|
||||
float alpha = constrain_float(dtBaro / (dtBaro+gndHgtFiltTC),0.0f,1.0f);
|
||||
meaHgtAtTakeOff += (baroDataDelayed.hgt-meaHgtAtTakeOff)*alpha;
|
||||
} else if (isAiding && getTakeoffExpected()) {
|
||||
// If we are in takeoff mode, the height measurement is limited to be no less than the measurement at start of takeoff
|
||||
// This prevents negative baro disturbances due to copter downwash corrupting the EKF altitude during initial ascent
|
||||
baroDataNew.hgt = max(baroDataNew.hgt, meaHgtAtTakeOff);
|
||||
}
|
||||
|
||||
// time stamp used to check for new measurement
|
||||
lastHgtReceived_ms = _baro.get_last_update();
|
||||
|
||||
// estimate of time height measurement was taken, allowing for delays
|
||||
hgtMeasTime_ms = lastHgtReceived_ms - frontend._hgtDelay_ms;
|
||||
|
||||
// save baro measurement to buffer to be fused later
|
||||
baroDataNew.time_ms = hgtMeasTime_ms;
|
||||
StoreBaro();
|
||||
}
|
||||
}
|
||||
|
||||
// store baro in a history array
|
||||
void NavEKF2_core::StoreBaro()
|
||||
{
|
||||
if (baroStoreIndex >= OBS_BUFFER_LENGTH) {
|
||||
baroStoreIndex = 0;
|
||||
}
|
||||
storedBaro[baroStoreIndex] = baroDataNew;
|
||||
baroStoreIndex += 1;
|
||||
}
|
||||
|
||||
// return newest un-used baro data that has fallen behind the fusion time horizon
|
||||
// if no un-used data is available behind the fusion horizon, return false
|
||||
bool NavEKF2_core::RecallBaro()
|
||||
{
|
||||
baro_elements dataTemp;
|
||||
baro_elements dataTempZero;
|
||||
dataTempZero.time_ms = 0;
|
||||
uint32_t temp_ms = 0;
|
||||
for (uint8_t i=0; i<OBS_BUFFER_LENGTH; i++) {
|
||||
dataTemp = storedBaro[i];
|
||||
// find a measurement older than the fusion time horizon that we haven't checked before
|
||||
if (dataTemp.time_ms != 0 && dataTemp.time_ms <= imuDataDelayed.time_ms) {
|
||||
// zero the time stamp so we won't use it again
|
||||
storedBaro[i]=dataTempZero;
|
||||
// Find the most recent non-stale measurement that meets the time horizon criteria
|
||||
if (((imuDataDelayed.time_ms - dataTemp.time_ms) < 500) && dataTemp.time_ms > temp_ms) {
|
||||
baroDataDelayed = dataTemp;
|
||||
temp_ms = dataTemp.time_ms;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (temp_ms != 0) {
|
||||
return true;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/********************************************************
|
||||
* FUSE MEASURED_DATA *
|
||||
********************************************************/
|
||||
|
|
|
|||
|
|
@ -22,49 +22,6 @@ extern const AP_HAL::HAL& hal;
|
|||
* RESET FUNCTIONS *
|
||||
********************************************************/
|
||||
|
||||
|
||||
|
||||
/********************************************************
|
||||
* GET STATES/PARAMS FUNCTIONS *
|
||||
********************************************************/
|
||||
|
||||
// return the NED wind speed estimates in m/s (positive is air moving in the direction of the axis)
|
||||
void NavEKF2_core::getWind(Vector3f &wind) const
|
||||
{
|
||||
wind.x = stateStruct.wind_vel.x;
|
||||
wind.y = stateStruct.wind_vel.y;
|
||||
wind.z = 0.0f; // currently don't estimate this
|
||||
}
|
||||
|
||||
/********************************************************
|
||||
* SET STATES/PARAMS FUNCTIONS *
|
||||
********************************************************/
|
||||
|
||||
/********************************************************
|
||||
* READ SENSORS *
|
||||
********************************************************/
|
||||
|
||||
// check for new airspeed data and update stored measurements if available
|
||||
void NavEKF2_core::readAirSpdData()
|
||||
{
|
||||
// if airspeed reading is valid and is set by the user to be used and has been updated then
|
||||
// we take a new reading, convert from EAS to TAS and set the flag letting other functions
|
||||
// know a new measurement is available
|
||||
const AP_Airspeed *aspeed = _ahrs->get_airspeed();
|
||||
if (aspeed &&
|
||||
aspeed->use() &&
|
||||
aspeed->last_update_ms() != timeTasReceived_ms) {
|
||||
tasDataNew.tas = aspeed->get_airspeed() * aspeed->get_EAS2TAS();
|
||||
timeTasReceived_ms = aspeed->last_update_ms();
|
||||
tasDataNew.time_ms = timeTasReceived_ms - frontend.tasDelay_ms;
|
||||
newDataTas = true;
|
||||
StoreTAS();
|
||||
RecallTAS();
|
||||
} else {
|
||||
newDataTas = false;
|
||||
}
|
||||
}
|
||||
|
||||
/********************************************************
|
||||
* FUSE MEASURED_DATA *
|
||||
********************************************************/
|
||||
|
|
|
|||
|
|
@ -1107,65 +1107,6 @@ void NavEKF2_core::CovariancePrediction()
|
|||
}
|
||||
|
||||
|
||||
// update IMU delta angle and delta velocity measurements
|
||||
void NavEKF2_core::readIMUData()
|
||||
{
|
||||
const AP_InertialSensor &ins = _ahrs->get_ins();
|
||||
|
||||
// average IMU sampling rate
|
||||
dtIMUavg = 1.0f/ins.get_sample_rate();
|
||||
|
||||
// the imu sample time is used as a common time reference throughout the filter
|
||||
imuSampleTime_ms = hal.scheduler->millis();
|
||||
|
||||
// Get delta velocity data
|
||||
readDeltaVelocity(ins.get_primary_accel(), imuDataNew.delVel, imuDataNew.delVelDT);
|
||||
|
||||
// Get delta angle data
|
||||
readDeltaAngle(ins.get_primary_gyro(), imuDataNew.delAng);
|
||||
imuDataNew.delAngDT = max(ins.get_delta_time(),1.0e-4f);
|
||||
|
||||
// get current time stamp
|
||||
imuDataNew.time_ms = imuSampleTime_ms;
|
||||
|
||||
// save data in the FIFO buffer
|
||||
StoreIMU();
|
||||
|
||||
// extract the oldest available data from the FIFO buffer
|
||||
imuDataDelayed = storedIMU[fifoIndexDelayed];
|
||||
|
||||
}
|
||||
|
||||
// store imu in the FIFO
|
||||
void NavEKF2_core::StoreIMU()
|
||||
{
|
||||
fifoIndexDelayed = fifoIndexNow;
|
||||
fifoIndexNow = fifoIndexNow + 1;
|
||||
if (fifoIndexNow >= IMU_BUFFER_LENGTH) {
|
||||
fifoIndexNow = 0;
|
||||
}
|
||||
storedIMU[fifoIndexNow] = imuDataNew;
|
||||
}
|
||||
|
||||
// reset the stored imu history and store the current value
|
||||
void NavEKF2_core::StoreIMU_reset()
|
||||
{
|
||||
// write current measurement to entire table
|
||||
for (uint8_t i=0; i<IMU_BUFFER_LENGTH; i++) {
|
||||
storedIMU[i] = imuDataNew;
|
||||
}
|
||||
imuDataDelayed = imuDataNew;
|
||||
fifoIndexDelayed = fifoIndexNow+1;
|
||||
if (fifoIndexDelayed >= IMU_BUFFER_LENGTH) {
|
||||
fifoIndexDelayed = 0;
|
||||
}
|
||||
}
|
||||
|
||||
// recall IMU data from the FIFO
|
||||
void NavEKF2_core::RecallIMU()
|
||||
{
|
||||
imuDataDelayed = storedIMU[fifoIndexDelayed];
|
||||
}
|
||||
|
||||
// zero specified range of rows in the state covariance matrix
|
||||
void NavEKF2_core::zeroRows(Matrix24 &covMat, uint8_t first, uint8_t last)
|
||||
|
|
@ -1373,26 +1314,4 @@ Quaternion NavEKF2_core::calcQuatAndFieldStates(float roll, float pitch)
|
|||
return initQuat;
|
||||
}
|
||||
|
||||
// return the transformation matrix from XYZ (body) to NED axes
|
||||
void NavEKF2_core::getRotationBodyToNED(Matrix3f &mat) const
|
||||
{
|
||||
Vector3f trim = _ahrs->get_trim();
|
||||
outputDataNew.quat.rotation_matrix(mat);
|
||||
mat.rotateXYinv(trim);
|
||||
}
|
||||
|
||||
// return the quaternions defining the rotation from NED to XYZ (body) axes
|
||||
void NavEKF2_core::getQuaternion(Quaternion& ret) const
|
||||
{
|
||||
ret = outputDataNew.quat;
|
||||
}
|
||||
|
||||
// return the amount of yaw angle change due to the last yaw angle reset in radians
|
||||
// returns the time of the last yaw angle reset or 0 if no reset has ever occurred
|
||||
uint32_t NavEKF2_core::getLastYawResetAngle(float &yawAng)
|
||||
{
|
||||
yawAng = yawResetAngle;
|
||||
return lastYawReset_ms;
|
||||
}
|
||||
|
||||
#endif // HAL_CPU_CLASS
|
||||
|
|
|
|||
|
|
@ -18,42 +18,6 @@
|
|||
|
||||
extern const AP_HAL::HAL& hal;
|
||||
|
||||
|
||||
// return the Euler roll, pitch and yaw angle in radians
|
||||
void NavEKF2_core::getEulerAngles(Vector3f &euler) const
|
||||
{
|
||||
outputDataNew.quat.to_euler(euler.x, euler.y, euler.z);
|
||||
euler = euler - _ahrs->get_trim();
|
||||
}
|
||||
|
||||
// return body axis gyro bias estimates in rad/sec
|
||||
void NavEKF2_core::getGyroBias(Vector3f &gyroBias) const
|
||||
{
|
||||
if (dtIMUavg < 1e-6f) {
|
||||
gyroBias.zero();
|
||||
return;
|
||||
}
|
||||
gyroBias = stateStruct.gyro_bias / dtIMUavg;
|
||||
}
|
||||
|
||||
// return body axis gyro scale factor error as a percentage
|
||||
void NavEKF2_core::getGyroScaleErrorPercentage(Vector3f &gyroScale) const
|
||||
{
|
||||
if (!statesInitialised) {
|
||||
gyroScale.x = gyroScale.y = gyroScale.z = 0;
|
||||
return;
|
||||
}
|
||||
gyroScale.x = 100.0f/stateStruct.gyro_scale.x - 100.0f;
|
||||
gyroScale.y = 100.0f/stateStruct.gyro_scale.y - 100.0f;
|
||||
gyroScale.z = 100.0f/stateStruct.gyro_scale.z - 100.0f;
|
||||
}
|
||||
|
||||
// return tilt error convergence metric
|
||||
void NavEKF2_core::getTiltError(float &ang) const
|
||||
{
|
||||
ang = tiltErrFilt;
|
||||
}
|
||||
|
||||
// reset the body axis gyro bias states to zero and re-initialise the corresponding covariances
|
||||
void NavEKF2_core::resetGyroBias(void)
|
||||
{
|
||||
|
|
@ -73,15 +37,5 @@ float NavEKF2_core::InitialGyroBiasUncertainty(void) const
|
|||
return 5.0f;
|
||||
}
|
||||
|
||||
bool NavEKF2_core::readDeltaAngle(uint8_t ins_index, Vector3f &dAng) {
|
||||
const AP_InertialSensor &ins = _ahrs->get_ins();
|
||||
|
||||
if (ins_index < ins.get_gyro_count()) {
|
||||
ins.get_delta_angle(ins_index,dAng);
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
#endif // HAL_CPU_CLASS
|
||||
Loading…
Reference in New Issue