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ardupilot/libraries/AP_NavEKF2/AP_NavEKF2_PosVelFusion.cpp

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#include <AP_HAL/AP_HAL.h>
#include "AP_NavEKF2.h"
#include "AP_NavEKF2_core.h"
#include <AP_AHRS/AP_AHRS.h>
#include <AP_Vehicle/AP_Vehicle.h>
#include <AP_RangeFinder/AP_RangeFinder.h>
#include <AP_RangeFinder/AP_RangeFinder_Backend.h>
#include <AP_GPS/AP_GPS.h>
#include <AP_Baro/AP_Baro.h>
#include <stdio.h>
extern const AP_HAL::HAL& hal;
/********************************************************
* RESET FUNCTIONS *
********************************************************/
// Reset velocity states to last GPS measurement if available or to zero if in constant position mode or if PV aiding is not absolute
// Do not reset vertical velocity using GPS as there is baro alt available to constrain drift
void NavEKF2_core::ResetVelocity(void)
{
// Store the position before the reset so that we can record the reset delta
velResetNE.x = stateStruct.velocity.x;
velResetNE.y = stateStruct.velocity.y;
// reset the corresponding covariances
zeroRows(P,3,4);
zeroCols(P,3,4);
gps_elements gps_corrected = gpsDataNew;
CorrectGPSForAntennaOffset(gps_corrected);
if (PV_AidingMode != AID_ABSOLUTE) {
stateStruct.velocity.zero();
// set the variances using the measurement noise parameter
P[4][4] = P[3][3] = sq(frontend->_gpsHorizVelNoise);
} else {
// reset horizontal velocity states to the GPS velocity if available
if (imuSampleTime_ms - lastTimeGpsReceived_ms < 250) {
stateStruct.velocity.x = gps_corrected.vel.x;
stateStruct.velocity.y = gps_corrected.vel.y;
// set the variances using the reported GPS speed accuracy
P[4][4] = P[3][3] = sq(MAX(frontend->_gpsHorizVelNoise,gpsSpdAccuracy));
// clear the timeout flags and counters
velTimeout = false;
lastVelPassTime_ms = imuSampleTime_ms;
} else {
stateStruct.velocity.x = 0.0f;
stateStruct.velocity.y = 0.0f;
// set the variances using the likely speed range
P[4][4] = P[3][3] = sq(25.0f);
// clear the timeout flags and counters
velTimeout = false;
lastVelPassTime_ms = imuSampleTime_ms;
}
}
for (uint8_t i=0; i<imu_buffer_length; i++) {
storedOutput[i].velocity.x = stateStruct.velocity.x;
storedOutput[i].velocity.y = stateStruct.velocity.y;
}
outputDataNew.velocity.x = stateStruct.velocity.x;
outputDataNew.velocity.y = stateStruct.velocity.y;
outputDataDelayed.velocity.x = stateStruct.velocity.x;
outputDataDelayed.velocity.y = stateStruct.velocity.y;
// Calculate the position jump due to the reset
velResetNE.x = stateStruct.velocity.x - velResetNE.x;
velResetNE.y = stateStruct.velocity.y - velResetNE.y;
// store the time of the reset
lastVelReset_ms = imuSampleTime_ms;
}
// resets position states to last GPS measurement or to zero if in constant position mode
void NavEKF2_core::ResetPosition(void)
{
// Store the position before the reset so that we can record the reset delta
posResetNE.x = stateStruct.position.x;
posResetNE.y = stateStruct.position.y;
// reset the corresponding covariances
zeroRows(P,6,7);
zeroCols(P,6,7);
gps_elements gps_corrected = gpsDataNew;
CorrectGPSForAntennaOffset(gps_corrected);
if (PV_AidingMode != AID_ABSOLUTE) {
// reset all position state history to the last known position
stateStruct.position.x = lastKnownPositionNE.x;
stateStruct.position.y = lastKnownPositionNE.y;
// set the variances using the position measurement noise parameter
P[6][6] = P[7][7] = sq(frontend->_gpsHorizPosNoise);
} else {
// Use GPS data as first preference if fresh data is available
if (imuSampleTime_ms - lastTimeGpsReceived_ms < 250) {
// record the ID of the GPS for the data we are using for the reset
last_gps_idx = gps_corrected.sensor_idx;
// write to state vector and compensate for offset between last GPS measurement and the EKF time horizon
stateStruct.position.x = gps_corrected.pos.x + 0.001f*gps_corrected.vel.x*(float(imuDataDelayed.time_ms) - float(gps_corrected.time_ms));
stateStruct.position.y = gps_corrected.pos.y + 0.001f*gps_corrected.vel.y*(float(imuDataDelayed.time_ms) - float(gps_corrected.time_ms));
// set the variances using the position measurement noise parameter
P[6][6] = P[7][7] = sq(MAX(gpsPosAccuracy,frontend->_gpsHorizPosNoise));
// clear the timeout flags and counters
posTimeout = false;
lastPosPassTime_ms = imuSampleTime_ms;
} else if (imuSampleTime_ms - rngBcnLast3DmeasTime_ms < 250) {
// use the range beacon data as a second preference
stateStruct.position.x = receiverPos.x;
stateStruct.position.y = receiverPos.y;
// set the variances from the beacon alignment filter
P[6][6] = receiverPosCov[0][0];
P[7][7] = receiverPosCov[1][1];
// clear the timeout flags and counters
rngBcnTimeout = false;
lastRngBcnPassTime_ms = imuSampleTime_ms;
} else if (imuSampleTime_ms - extNavDataDelayed.time_ms < 250) {
// use the range beacon data as a second preference
stateStruct.position.x = extNavDataDelayed.pos.x;
stateStruct.position.y = extNavDataDelayed.pos.y;
// set the variances from the beacon alignment filter
P[7][7] = P[6][6] = sq(extNavDataDelayed.posErr);
}
}
for (uint8_t i=0; i<imu_buffer_length; i++) {
storedOutput[i].position.x = stateStruct.position.x;
storedOutput[i].position.y = stateStruct.position.y;
}
outputDataNew.position.x = stateStruct.position.x;
outputDataNew.position.y = stateStruct.position.y;
outputDataDelayed.position.x = stateStruct.position.x;
outputDataDelayed.position.y = stateStruct.position.y;
// Calculate the position jump due to the reset
posResetNE.x = stateStruct.position.x - posResetNE.x;
posResetNE.y = stateStruct.position.y - posResetNE.y;
// store the time of the reset
lastPosReset_ms = imuSampleTime_ms;
}
// reset the vertical position state using the last height measurement
void NavEKF2_core::ResetHeight(void)
{
// Store the position before the reset so that we can record the reset delta
posResetD = stateStruct.position.z;
// write to the state vector
stateStruct.position.z = -hgtMea;
outputDataNew.position.z = stateStruct.position.z;
outputDataDelayed.position.z = stateStruct.position.z;
// reset the terrain state height
if (onGround) {
// assume vehicle is sitting on the ground
terrainState = stateStruct.position.z + rngOnGnd;
} else {
// can make no assumption other than vehicle is not below ground level
terrainState = MAX(stateStruct.position.z + rngOnGnd , terrainState);
}
for (uint8_t i=0; i<imu_buffer_length; i++) {
storedOutput[i].position.z = stateStruct.position.z;
}
vertCompFiltState.pos = stateStruct.position.z;
// Calculate the position jump due to the reset
posResetD = stateStruct.position.z - posResetD;
// store the time of the reset
lastPosResetD_ms = imuSampleTime_ms;
// clear the timeout flags and counters
hgtTimeout = false;
lastHgtPassTime_ms = imuSampleTime_ms;
// reset the corresponding covariances
zeroRows(P,8,8);
zeroCols(P,8,8);
// set the variances to the measurement variance
P[8][8] = posDownObsNoise;
// Reset the vertical velocity state using GPS vertical velocity if we are airborne
// Check that GPS vertical velocity data is available and can be used
if (inFlight && !gpsNotAvailable && frontend->_fusionModeGPS == 0 && !frontend->inhibitGpsVertVelUse) {
stateStruct.velocity.z = gpsDataNew.vel.z;
} else if (onGround) {
stateStruct.velocity.z = 0.0f;
}
for (uint8_t i=0; i<imu_buffer_length; i++) {
storedOutput[i].velocity.z = stateStruct.velocity.z;
}
outputDataNew.velocity.z = stateStruct.velocity.z;
outputDataDelayed.velocity.z = stateStruct.velocity.z;
vertCompFiltState.vel = outputDataNew.velocity.z;
// reset the corresponding covariances
zeroRows(P,5,5);
zeroCols(P,5,5);
// set the variances to the measurement variance
P[5][5] = sq(frontend->_gpsVertVelNoise);
}
// Zero the EKF height datum
// Return true if the height datum reset has been performed
bool NavEKF2_core::resetHeightDatum(void)
{
if (activeHgtSource == HGT_SOURCE_RNG || !onGround) {
// only allow resets when on the ground.
// If using using rangefinder for height then never perform a
// reset of the height datum
return false;
}
// record the old height estimate
float oldHgt = -stateStruct.position.z;
// reset the barometer so that it reads zero at the current height
AP::baro().update_calibration();
// reset the height state
stateStruct.position.z = 0.0f;
// adjust the height of the EKF origin so that the origin plus baro height before and after the reset is the same
if (validOrigin) {
if (!gpsGoodToAlign) {
// if we don't have GPS lock then we shouldn't be doing a
// resetHeightDatum, but if we do then the best option is
// to maintain the old error
EKF_origin.alt += (int32_t)(100.0f * oldHgt);
} else {
// if we have a good GPS lock then reset to the GPS
// altitude. This ensures the reported AMSL alt from
// getLLH() is equal to GPS altitude, while also ensuring
// that the relative alt is zero
EKF_origin.alt = AP::gps().location().alt;
}
ekfGpsRefHgt = (double)0.01 * (double)EKF_origin.alt;
}
// set the terrain state to zero (on ground). The adjustment for
// frame height will get added in the later constraints
terrainState = 0;
return true;
}
/*
correct GPS data for position offset of antenna phase centre relative to the IMU
*/
void NavEKF2_core::CorrectGPSForAntennaOffset(gps_elements &gps_data)
{
const Vector3f &posOffsetBody = AP::gps().get_antenna_offset(gpsDataDelayed.sensor_idx) - accelPosOffset;
if (posOffsetBody.is_zero()) {
return;
}
// Don't fuse velocity data if GPS doesn't support it
if (fuseVelData) {
// TODO use a filtered angular rate with a group delay that matches the GPS delay
Vector3f angRate = imuDataDelayed.delAng * (1.0f/imuDataDelayed.delAngDT);
Vector3f velOffsetBody = angRate % posOffsetBody;
Vector3f velOffsetEarth = prevTnb.mul_transpose(velOffsetBody);
gps_data.vel.x -= velOffsetEarth.x;
gps_data.vel.y -= velOffsetEarth.y;
gps_data.vel.z -= velOffsetEarth.z;
}
Vector3f posOffsetEarth = prevTnb.mul_transpose(posOffsetBody);
gps_data.pos.x -= posOffsetEarth.x;
gps_data.pos.y -= posOffsetEarth.y;
gps_data.hgt += posOffsetEarth.z;
}
/********************************************************
* FUSE MEASURED_DATA *
********************************************************/
// select fusion of velocity, position and height measurements
void NavEKF2_core::SelectVelPosFusion()
{
// Check if the magnetometer has been fused on that time step and the filter is running at faster than 200 Hz
// If so, don't fuse measurements on this time step to reduce frame over-runs
// Only allow one time slip to prevent high rate magnetometer data preventing fusion of other measurements
if (magFusePerformed && dtIMUavg < 0.005f && !posVelFusionDelayed) {
posVelFusionDelayed = true;
return;
} else {
posVelFusionDelayed = false;
}
// Check for data at the fusion time horizon
extNavDataToFuse = storedExtNav.recall(extNavDataDelayed, imuDataDelayed.time_ms);
// read GPS data from the sensor and check for new data in the buffer
readGpsData();
gpsDataToFuse = storedGPS.recall(gpsDataDelayed,imuDataDelayed.time_ms);
// Determine if we need to fuse position and velocity data on this time step
if (gpsDataToFuse && PV_AidingMode == AID_ABSOLUTE) {
// set fusion request flags
if (frontend->_fusionModeGPS <= 1) {
fuseVelData = true;
} else {
fuseVelData = false;
}
fusePosData = true;
extNavUsedForPos = false;
// correct for antenna position
CorrectGPSForAntennaOffset(gpsDataDelayed);
// copy corrected GPS data to observation vector
if (fuseVelData) {
velPosObs[0] = gpsDataDelayed.vel.x;
velPosObs[1] = gpsDataDelayed.vel.y;
velPosObs[2] = gpsDataDelayed.vel.z;
}
velPosObs[3] = gpsDataDelayed.pos.x;
velPosObs[4] = gpsDataDelayed.pos.y;
} else if (extNavDataToFuse && PV_AidingMode == AID_ABSOLUTE) {
// This is a special case that uses and external nav system for position
extNavUsedForPos = true;
activeHgtSource = HGT_SOURCE_EV;
fuseVelData = false;
fuseHgtData = true;
fusePosData = true;
velPosObs[3] = extNavDataDelayed.pos.x;
velPosObs[4] = extNavDataDelayed.pos.y;
velPosObs[5] = extNavDataDelayed.pos.z;
// if compass is disabled, also use it for yaw
if (!use_compass()) {
extNavUsedForYaw = true;
if (!yawAlignComplete) {
extNavYawResetRequest = true;
magYawResetRequest = false;
gpsYawResetRequest = false;
controlMagYawReset();
finalInflightYawInit = true;
} else {
fuseEulerYaw();
}
} else {
extNavUsedForYaw = false;
}
} else {
fuseVelData = false;
fusePosData = false;
}
// we have GPS data to fuse and a request to align the yaw using the GPS course
if (gpsYawResetRequest) {
realignYawGPS();
}
// Select height data to be fused from the available baro, range finder and GPS sources
selectHeightForFusion();
// if we are using GPS, check for a change in receiver and reset position and height
if (gpsDataToFuse && PV_AidingMode == AID_ABSOLUTE && gpsDataDelayed.sensor_idx != last_gps_idx) {
// record the ID of the GPS that we are using for the reset
last_gps_idx = gpsDataDelayed.sensor_idx;
// Store the position before the reset so that we can record the reset delta
posResetNE.x = stateStruct.position.x;
posResetNE.y = stateStruct.position.y;
// Set the position states to the position from the new GPS
stateStruct.position.x = gpsDataDelayed.pos.x;
stateStruct.position.y = gpsDataDelayed.pos.y;
// Calculate the position offset due to the reset
posResetNE.x = stateStruct.position.x - posResetNE.x;
posResetNE.y = stateStruct.position.y - posResetNE.y;
// Add the offset to the output observer states
for (uint8_t i=0; i<imu_buffer_length; i++) {
storedOutput[i].position.x += posResetNE.x;
storedOutput[i].position.y += posResetNE.y;
}
outputDataNew.position.x += posResetNE.x;
outputDataNew.position.y += posResetNE.y;
outputDataDelayed.position.x += posResetNE.x;
outputDataDelayed.position.y += posResetNE.y;
// store the time of the reset
lastPosReset_ms = imuSampleTime_ms;
// If we are also using GPS as the height reference, reset the height
if (activeHgtSource == HGT_SOURCE_GPS) {
// Store the position before the reset so that we can record the reset delta
posResetD = stateStruct.position.z;
// write to the state vector
stateStruct.position.z = -hgtMea;
// Calculate the position jump due to the reset
posResetD = stateStruct.position.z - posResetD;
// Add the offset to the output observer states
outputDataNew.position.z += posResetD;
vertCompFiltState.pos = outputDataNew.position.z;
outputDataDelayed.position.z += posResetD;
for (uint8_t i=0; i<imu_buffer_length; i++) {
storedOutput[i].position.z += posResetD;
}
// store the time of the reset
lastPosResetD_ms = imuSampleTime_ms;
}
}
// If we are operating without any aiding, fuse in the last known position
// to constrain tilt drift. This assumes a non-manoeuvring vehicle
// Do this to coincide with the height fusion
if (fuseHgtData && PV_AidingMode == AID_NONE) {
velPosObs[3] = lastKnownPositionNE.x;
velPosObs[4] = lastKnownPositionNE.y;
fusePosData = true;
fuseVelData = false;
}
// perform fusion
if (fuseVelData || fusePosData || fuseHgtData) {
FuseVelPosNED();
// clear the flags to prevent repeated fusion of the same data
fuseVelData = false;
fuseHgtData = false;
fusePosData = false;
}
}
// fuse selected position, velocity and height measurements
void NavEKF2_core::FuseVelPosNED()
{
// start performance timer
hal.util->perf_begin(_perf_FuseVelPosNED);
// health is set bad until test passed
velHealth = false;
posHealth = false;
hgtHealth = false;
// declare variables used to check measurement errors
Vector3f velInnov;
// declare variables used to control access to arrays
bool fuseData[6] = {false,false,false,false,false,false};
uint8_t stateIndex;
uint8_t obsIndex;
// declare variables used by state and covariance update calculations
Vector6 R_OBS; // Measurement variances used for fusion
Vector6 R_OBS_DATA_CHECKS; // Measurement variances used for data checks only
float SK;
// perform sequential fusion of GPS measurements. This assumes that the
// errors in the different velocity and position components are
// uncorrelated which is not true, however in the absence of covariance
// data from the GPS receiver it is the only assumption we can make
// so we might as well take advantage of the computational efficiencies
// associated with sequential fusion
if (fuseVelData || fusePosData || fuseHgtData) {
// calculate additional error in GPS position caused by manoeuvring
float posErr = frontend->gpsPosVarAccScale * accNavMag;
// estimate the GPS Velocity, GPS horiz position and height measurement variances.
// Use different errors if operating without external aiding using an assumed position or velocity of zero
if (PV_AidingMode == AID_NONE) {
if (tiltAlignComplete && motorsArmed) {
// This is a compromise between corrections for gyro errors and reducing effect of manoeuvre accelerations on tilt estimate
R_OBS[0] = sq(constrain_float(frontend->_noaidHorizNoise, 0.5f, 50.0f));
} else {
// Use a smaller value to give faster initial alignment
R_OBS[0] = sq(0.5f);
}
R_OBS[1] = R_OBS[0];
R_OBS[2] = R_OBS[0];
R_OBS[3] = R_OBS[0];
R_OBS[4] = R_OBS[0];
for (uint8_t i=0; i<=2; i++) R_OBS_DATA_CHECKS[i] = R_OBS[i];
} else {
if (gpsSpdAccuracy > 0.0f) {
// use GPS receivers reported speed accuracy if available and floor at value set by GPS velocity noise parameter
R_OBS[0] = sq(constrain_float(gpsSpdAccuracy, frontend->_gpsHorizVelNoise, 50.0f));
R_OBS[2] = sq(constrain_float(gpsSpdAccuracy, frontend->_gpsVertVelNoise, 50.0f));
} else {
// calculate additional error in GPS velocity caused by manoeuvring
R_OBS[0] = sq(constrain_float(frontend->_gpsHorizVelNoise, 0.05f, 5.0f)) + sq(frontend->gpsNEVelVarAccScale * accNavMag);
R_OBS[2] = sq(constrain_float(frontend->_gpsVertVelNoise, 0.05f, 5.0f)) + sq(frontend->gpsDVelVarAccScale * accNavMag);
}
R_OBS[1] = R_OBS[0];
// Use GPS reported position accuracy if available and floor at value set by GPS position noise parameter
if (gpsPosAccuracy > 0.0f) {
R_OBS[3] = sq(constrain_float(gpsPosAccuracy, frontend->_gpsHorizPosNoise, 100.0f));
} else if (extNavUsedForPos) {
R_OBS[3] = sq(constrain_float(extNavDataDelayed.posErr, 0.01f, 10.0f));
} else {
R_OBS[3] = sq(constrain_float(frontend->_gpsHorizPosNoise, 0.1f, 10.0f)) + sq(posErr);
}
R_OBS[4] = R_OBS[3];
// For data integrity checks we use the same measurement variances as used to calculate the Kalman gains for all measurements except GPS horizontal velocity
// For horizontal GPS velocity we don't want the acceptance radius to increase with reported GPS accuracy so we use a value based on best GPS perfomrance
// plus a margin for manoeuvres. It is better to reject GPS horizontal velocity errors early
for (uint8_t i=0; i<=2; i++) R_OBS_DATA_CHECKS[i] = sq(constrain_float(frontend->_gpsHorizVelNoise, 0.05f, 5.0f)) + sq(frontend->gpsNEVelVarAccScale * accNavMag);
}
R_OBS[5] = posDownObsNoise;
for (uint8_t i=3; i<=5; i++) R_OBS_DATA_CHECKS[i] = R_OBS[i];
// if vertical GPS velocity data and an independent height source is being used, check to see if the GPS vertical velocity and altimeter
// innovations have the same sign and are outside limits. If so, then it is likely aliasing is affecting
// the accelerometers and we should disable the GPS and barometer innovation consistency checks.
if (useGpsVertVel && fuseVelData && (frontend->_altSource != 2)) {
// calculate innovations for height and vertical GPS vel measurements
float hgtErr = stateStruct.position.z - velPosObs[5];
float velDErr = stateStruct.velocity.z - velPosObs[2];
// check if they are the same sign and both more than 3-sigma out of bounds
if ((hgtErr*velDErr > 0.0f) && (sq(hgtErr) > 9.0f * (P[8][8] + R_OBS_DATA_CHECKS[5])) && (sq(velDErr) > 9.0f * (P[5][5] + R_OBS_DATA_CHECKS[2]))) {
badIMUdata = true;
} else {
badIMUdata = false;
}
}
// calculate innovations and check GPS data validity using an innovation consistency check
// test position measurements
if (fusePosData) {
// test horizontal position measurements
innovVelPos[3] = stateStruct.position.x - velPosObs[3];
innovVelPos[4] = stateStruct.position.y - velPosObs[4];
varInnovVelPos[3] = P[6][6] + R_OBS_DATA_CHECKS[3];
varInnovVelPos[4] = P[7][7] + R_OBS_DATA_CHECKS[4];
// apply an innovation consistency threshold test, but don't fail if bad IMU data
float maxPosInnov2 = sq(MAX(0.01f * (float)frontend->_gpsPosInnovGate, 1.0f))*(varInnovVelPos[3] + varInnovVelPos[4]);
posTestRatio = (sq(innovVelPos[3]) + sq(innovVelPos[4])) / maxPosInnov2;
posHealth = ((posTestRatio < 1.0f) || badIMUdata);
// use position data if healthy or timed out
if (PV_AidingMode == AID_NONE) {
posHealth = true;
lastPosPassTime_ms = imuSampleTime_ms;
} else if (posHealth || posTimeout) {
posHealth = true;
lastPosPassTime_ms = imuSampleTime_ms;
// if timed out or outside the specified uncertainty radius, reset to the GPS
if (posTimeout || ((P[6][6] + P[7][7]) > sq(float(frontend->_gpsGlitchRadiusMax)))) {
// reset the position to the current GPS position
ResetPosition();
// reset the velocity to the GPS velocity
ResetVelocity();
// don't fuse GPS data on this time step
fusePosData = false;
fuseVelData = false;
// Reset the position variances and corresponding covariances to a value that will pass the checks
zeroRows(P,6,7);
zeroCols(P,6,7);
P[6][6] = sq(float(0.5f*frontend->_gpsGlitchRadiusMax));
P[7][7] = P[6][6];
// Reset the normalised innovation to avoid failing the bad fusion tests
posTestRatio = 0.0f;
velTestRatio = 0.0f;
}
} else {
posHealth = false;
}
}
// test velocity measurements
if (fuseVelData) {
// test velocity measurements
uint8_t imax = 2;
// Don't fuse vertical velocity observations if inhibited by the user or if we are using synthetic data
if (frontend->_fusionModeGPS > 0 || PV_AidingMode != AID_ABSOLUTE || frontend->inhibitGpsVertVelUse) {
imax = 1;
}
float innovVelSumSq = 0; // sum of squares of velocity innovations
float varVelSum = 0; // sum of velocity innovation variances
for (uint8_t i = 0; i<=imax; i++) {
// velocity states start at index 3
stateIndex = i + 3;
// calculate innovations using blended and single IMU predicted states
velInnov[i] = stateStruct.velocity[i] - velPosObs[i]; // blended
// calculate innovation variance
varInnovVelPos[i] = P[stateIndex][stateIndex] + R_OBS_DATA_CHECKS[i];
// sum the innovation and innovation variances
innovVelSumSq += sq(velInnov[i]);
varVelSum += varInnovVelPos[i];
}
// apply an innovation consistency threshold test, but don't fail if bad IMU data
// calculate the test ratio
velTestRatio = innovVelSumSq / (varVelSum * sq(MAX(0.01f * (float)frontend->_gpsVelInnovGate, 1.0f)));
// fail if the ratio is greater than 1
velHealth = ((velTestRatio < 1.0f) || badIMUdata);
// use velocity data if healthy, timed out, or in constant position mode
if (velHealth || velTimeout) {
velHealth = true;
// restart the timeout count
lastVelPassTime_ms = imuSampleTime_ms;
// If we are doing full aiding and velocity fusion times out, reset to the GPS velocity
if (PV_AidingMode == AID_ABSOLUTE && velTimeout) {
// reset the velocity to the GPS velocity
ResetVelocity();
// don't fuse GPS velocity data on this time step
fuseVelData = false;
// Reset the normalised innovation to avoid failing the bad fusion tests
velTestRatio = 0.0f;
}
} else {
velHealth = false;
}
}
// test height measurements
if (fuseHgtData) {
// calculate height innovations
innovVelPos[5] = stateStruct.position.z - velPosObs[5];
varInnovVelPos[5] = P[8][8] + R_OBS_DATA_CHECKS[5];
// calculate the innovation consistency test ratio
hgtTestRatio = sq(innovVelPos[5]) / (sq(MAX(0.01f * (float)frontend->_hgtInnovGate, 1.0f)) * varInnovVelPos[5]);
// when on ground we accept a larger test ratio to allow
// the filter to handle large switch on IMU bias errors
// without rejecting the height sensor
const float maxTestRatio = (PV_AidingMode == AID_NONE && onGround)? 3.0 : 1.0;
// fail if the ratio is > maxTestRatio, but don't fail if bad IMU data
hgtHealth = (hgtTestRatio < maxTestRatio) || badIMUdata;
// Fuse height data if healthy or timed out or in constant position mode
if (hgtHealth || hgtTimeout) {
// Calculate a filtered value to be used by pre-flight health checks
// We need to filter because wind gusts can generate significant baro noise and we want to be able to detect bias errors in the inertial solution
if (onGround) {
float dtBaro = (imuSampleTime_ms - lastHgtPassTime_ms)*1.0e-3f;
const float hgtInnovFiltTC = 2.0f;
float alpha = constrain_float(dtBaro/(dtBaro+hgtInnovFiltTC),0.0f,1.0f);
hgtInnovFiltState += (innovVelPos[5]-hgtInnovFiltState)*alpha;
} else {
hgtInnovFiltState = 0.0f;
}
// if timed out, reset the height
if (hgtTimeout) {
ResetHeight();
}
// If we have got this far then declare the height data as healthy and reset the timeout counter
hgtHealth = true;
lastHgtPassTime_ms = imuSampleTime_ms;
}
}
// set range for sequential fusion of velocity and position measurements depending on which data is available and its health
if (fuseVelData && velHealth) {
fuseData[0] = true;
fuseData[1] = true;
if (useGpsVertVel) {
fuseData[2] = true;
}
tiltErrVec.zero();
}
if (fusePosData && posHealth) {
fuseData[3] = true;
fuseData[4] = true;
tiltErrVec.zero();
}
if (fuseHgtData && hgtHealth) {
fuseData[5] = true;
}
// fuse measurements sequentially
for (obsIndex=0; obsIndex<=5; obsIndex++) {
if (fuseData[obsIndex]) {
stateIndex = 3 + obsIndex;
// calculate the measurement innovation, using states from a different time coordinate if fusing height data
// adjust scaling on GPS measurement noise variances if not enough satellites
if (obsIndex <= 2)
{
innovVelPos[obsIndex] = stateStruct.velocity[obsIndex] - velPosObs[obsIndex];
R_OBS[obsIndex] *= sq(gpsNoiseScaler);
}
else if (obsIndex == 3 || obsIndex == 4) {
innovVelPos[obsIndex] = stateStruct.position[obsIndex-3] - velPosObs[obsIndex];
R_OBS[obsIndex] *= sq(gpsNoiseScaler);
} else if (obsIndex == 5) {
innovVelPos[obsIndex] = stateStruct.position[obsIndex-3] - velPosObs[obsIndex];
const float gndMaxBaroErr = 4.0f;
const float gndBaroInnovFloor = -0.5f;
if(getTouchdownExpected() && activeHgtSource == HGT_SOURCE_BARO) {
// when a touchdown is expected, floor the barometer innovation at gndBaroInnovFloor
// constrain the correction between 0 and gndBaroInnovFloor+gndMaxBaroErr
// this function looks like this:
// |/
//---------|---------
// ____/|
// / |
// / |
innovVelPos[5] += constrain_float(-innovVelPos[5]+gndBaroInnovFloor, 0.0f, gndBaroInnovFloor+gndMaxBaroErr);
}
}
// calculate the Kalman gain and calculate innovation variances
varInnovVelPos[obsIndex] = P[stateIndex][stateIndex] + R_OBS[obsIndex];
SK = 1.0f/varInnovVelPos[obsIndex];
for (uint8_t i= 0; i<=15; i++) {
Kfusion[i] = P[i][stateIndex]*SK;
}
// inhibit magnetic field state estimation by setting Kalman gains to zero
if (!inhibitMagStates) {
for (uint8_t i = 16; i<=21; i++) {
Kfusion[i] = P[i][stateIndex]*SK;
}
} else {
for (uint8_t i = 16; i<=21; i++) {
Kfusion[i] = 0.0f;
}
}
// inhibit wind state estimation by setting Kalman gains to zero
if (!inhibitWindStates) {
Kfusion[22] = P[22][stateIndex]*SK;
Kfusion[23] = P[23][stateIndex]*SK;
} else {
Kfusion[22] = 0.0f;
Kfusion[23] = 0.0f;
}
// update the covariance - take advantage of direct observation of a single state at index = stateIndex to reduce computations
// this is a numerically optimised implementation of standard equation P = (I - K*H)*P;
for (uint8_t i= 0; i<=stateIndexLim; i++) {
for (uint8_t j= 0; j<=stateIndexLim; j++)
{
KHP[i][j] = Kfusion[i] * P[stateIndex][j];
}
}
// Check that we are not going to drive any variances negative and skip the update if so
bool healthyFusion = true;
for (uint8_t i= 0; i<=stateIndexLim; i++) {
if (KHP[i][i] > P[i][i]) {
healthyFusion = false;
}
}
if (healthyFusion) {
// update the covariance matrix
for (uint8_t i= 0; i<=stateIndexLim; i++) {
for (uint8_t j= 0; j<=stateIndexLim; j++) {
P[i][j] = P[i][j] - KHP[i][j];
}
}
// force the covariance matrix to be symmetrical and limit the variances to prevent ill-conditioning.
ForceSymmetry();
ConstrainVariances();
// update the states
// zero the attitude error state - by definition it is assumed to be zero before each observation fusion
stateStruct.angErr.zero();
// calculate state corrections and re-normalise the quaternions for states predicted using the blended IMU data
for (uint8_t i = 0; i<=stateIndexLim; i++) {
statesArray[i] = statesArray[i] - Kfusion[i] * innovVelPos[obsIndex];
}
// the first 3 states represent the angular misalignment vector. This is
// is used to correct the estimated quaternion
stateStruct.quat.rotate(stateStruct.angErr);
// sum the attitude error from velocity and position fusion only
// used as a metric for convergence monitoring
if (obsIndex != 5) {
tiltErrVec += stateStruct.angErr;
}
// record good fusion status
if (obsIndex == 0) {
faultStatus.bad_nvel = false;
} else if (obsIndex == 1) {
faultStatus.bad_evel = false;
} else if (obsIndex == 2) {
faultStatus.bad_dvel = false;
} else if (obsIndex == 3) {
faultStatus.bad_npos = false;
} else if (obsIndex == 4) {
faultStatus.bad_epos = false;
} else if (obsIndex == 5) {
faultStatus.bad_dpos = false;
}
} else {
// record bad fusion status
if (obsIndex == 0) {
faultStatus.bad_nvel = true;
} else if (obsIndex == 1) {
faultStatus.bad_evel = true;
} else if (obsIndex == 2) {
faultStatus.bad_dvel = true;
} else if (obsIndex == 3) {
faultStatus.bad_npos = true;
} else if (obsIndex == 4) {
faultStatus.bad_epos = true;
} else if (obsIndex == 5) {
faultStatus.bad_dpos = true;
}
}
}
}
}
// stop performance timer
hal.util->perf_end(_perf_FuseVelPosNED);
}
/********************************************************
* MISC FUNCTIONS *
********************************************************/
// select the height measurement to be fused from the available baro, range finder and GPS sources
void NavEKF2_core::selectHeightForFusion()
{
// Read range finder data and check for new data in the buffer
// This data is used by both height and optical flow fusion processing
readRangeFinder();
rangeDataToFuse = storedRange.recall(rangeDataDelayed,imuDataDelayed.time_ms);
// correct range data for the body frame position offset relative to the IMU
// the corrected reading is the reading that would have been taken if the sensor was
// co-located with the IMU
const RangeFinder *_rng = AP::rangefinder();
if (_rng && rangeDataToFuse) {
const AP_RangeFinder_Backend *sensor = _rng->get_backend(rangeDataDelayed.sensor_idx);
if (sensor != nullptr) {
Vector3f posOffsetBody = sensor->get_pos_offset() - accelPosOffset;
if (!posOffsetBody.is_zero()) {
Vector3f posOffsetEarth = prevTnb.mul_transpose(posOffsetBody);
rangeDataDelayed.rng += posOffsetEarth.z / prevTnb.c.z;
}
}
}
// read baro height data from the sensor and check for new data in the buffer
readBaroData();
baroDataToFuse = storedBaro.recall(baroDataDelayed, imuDataDelayed.time_ms);
// select height source
if (extNavUsedForPos) {
// always use external vision as the height source if using for position.
activeHgtSource = HGT_SOURCE_EV;
} else if (_rng && ((frontend->_useRngSwHgt > 0) && (frontend->_altSource == 1)) && (imuSampleTime_ms - rngValidMeaTime_ms < 500)) {
if (frontend->_altSource == 1) {
// always use range finder
activeHgtSource = HGT_SOURCE_RNG;
} else {
// determine if we are above or below the height switch region
float rangeMaxUse = 1e-4f * (float)_rng->max_distance_cm_orient(ROTATION_PITCH_270) * (float)frontend->_useRngSwHgt;
bool aboveUpperSwHgt = (terrainState - stateStruct.position.z) > rangeMaxUse;
bool belowLowerSwHgt = (terrainState - stateStruct.position.z) < 0.7f * rangeMaxUse;
// If the terrain height is consistent and we are moving slowly, then it can be
// used as a height reference in combination with a range finder
// apply a hysteresis to the speed check to prevent rapid switching
float horizSpeed = norm(stateStruct.velocity.x, stateStruct.velocity.y);
bool dontTrustTerrain = ((horizSpeed > frontend->_useRngSwSpd) && filterStatus.flags.horiz_vel) || !terrainHgtStable;
float trust_spd_trigger = MAX((frontend->_useRngSwSpd - 1.0f),(frontend->_useRngSwSpd * 0.5f));
bool trustTerrain = (horizSpeed < trust_spd_trigger) && terrainHgtStable;
/*
* Switch between range finder and primary height source using height above ground and speed thresholds with
* hysteresis to avoid rapid switching. Using range finder for height requires a consistent terrain height
* which cannot be assumed if the vehicle is moving horizontally.
*/
if ((aboveUpperSwHgt || dontTrustTerrain) && (activeHgtSource == HGT_SOURCE_RNG)) {
// cannot trust terrain or range finder so stop using range finder height
if (frontend->_altSource == 0) {
activeHgtSource = HGT_SOURCE_BARO;
} else if (frontend->_altSource == 2) {
activeHgtSource = HGT_SOURCE_GPS;
}
} else if (belowLowerSwHgt && trustTerrain && (activeHgtSource != HGT_SOURCE_RNG)) {
// reliable terrain and range finder so start using range finder height
activeHgtSource = HGT_SOURCE_RNG;
}
}
} else if ((frontend->_altSource == 2) && ((imuSampleTime_ms - lastTimeGpsReceived_ms) < 500) && validOrigin && gpsAccuracyGood) {
activeHgtSource = HGT_SOURCE_GPS;
} else if ((frontend->_altSource == 3) && validOrigin && rngBcnGoodToAlign) {
activeHgtSource = HGT_SOURCE_BCN;
} else {
activeHgtSource = HGT_SOURCE_BARO;
}
// Use Baro alt as a fallback if we lose range finder, GPS or external nav
bool lostRngHgt = ((activeHgtSource == HGT_SOURCE_RNG) && ((imuSampleTime_ms - rngValidMeaTime_ms) > 500));
bool lostGpsHgt = ((activeHgtSource == HGT_SOURCE_GPS) && ((imuSampleTime_ms - lastTimeGpsReceived_ms) > 2000));
bool lostExtNavHgt = ((activeHgtSource == HGT_SOURCE_EV) && ((imuSampleTime_ms - extNavMeasTime_ms) > 2000));
if (lostRngHgt || lostGpsHgt || lostExtNavHgt) {
activeHgtSource = HGT_SOURCE_BARO;
}
// if there is new baro data to fuse, calculate filtered baro data required by other processes
if (baroDataToFuse) {
// calculate offset to baro data that enables us to switch to Baro height use during operation
if (activeHgtSource != HGT_SOURCE_BARO) {
calcFiltBaroOffset();
}
// 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;
}
}
// If we are not using GPS as the primary height sensor, correct EKF origin height so that
// combined local NED position height and origin height remains consistent with the GPS altitude
// This also enables the GPS height to be used as a backup height source
if (gpsDataToFuse &&
(((frontend->_originHgtMode & (1 << 0)) && (activeHgtSource == HGT_SOURCE_BARO)) ||
((frontend->_originHgtMode & (1 << 1)) && (activeHgtSource == HGT_SOURCE_RNG)))
) {
correctEkfOriginHeight();
}
// Select the height measurement source
if (extNavDataToFuse && (activeHgtSource == HGT_SOURCE_EV)) {
hgtMea = -extNavDataDelayed.pos.z;
posDownObsNoise = sq(constrain_float(extNavDataDelayed.posErr, 0.01f, 10.0f));
} else if (rangeDataToFuse && (activeHgtSource == HGT_SOURCE_RNG)) {
// using range finder data
// correct for tilt using a flat earth model
if (prevTnb.c.z >= 0.7) {
// calculate height above ground
hgtMea = MAX(rangeDataDelayed.rng * prevTnb.c.z, rngOnGnd);
// correct for terrain position relative to datum
hgtMea -= terrainState;
// enable fusion
fuseHgtData = true;
velPosObs[5] = -hgtMea;
// set the observation noise
posDownObsNoise = sq(constrain_float(frontend->_rngNoise, 0.1f, 10.0f));
// add uncertainty created by terrain gradient and vehicle tilt
posDownObsNoise += sq(rangeDataDelayed.rng * frontend->_terrGradMax) * MAX(0.0f , (1.0f - sq(prevTnb.c.z)));
} else {
// disable fusion if tilted too far
fuseHgtData = false;
}
} else if (gpsDataToFuse && (activeHgtSource == HGT_SOURCE_GPS)) {
// using GPS data
hgtMea = gpsDataDelayed.hgt;
// enable fusion
velPosObs[5] = -hgtMea;
fuseHgtData = true;
// set the observation noise using receiver reported accuracy or the horizontal noise scaled for typical VDOP/HDOP ratio
if (gpsHgtAccuracy > 0.0f) {
posDownObsNoise = sq(constrain_float(gpsHgtAccuracy, 1.5f * frontend->_gpsHorizPosNoise, 100.0f));
} else {
posDownObsNoise = sq(constrain_float(1.5f * frontend->_gpsHorizPosNoise, 0.1f, 10.0f));
}
} else if (baroDataToFuse && (activeHgtSource == HGT_SOURCE_BARO)) {
// using Baro data
hgtMea = baroDataDelayed.hgt - baroHgtOffset;
// enable fusion
velPosObs[5] = -hgtMea;
fuseHgtData = true;
// set the observation noise
posDownObsNoise = sq(constrain_float(frontend->_baroAltNoise, 0.1f, 10.0f));
// reduce weighting (increase observation noise) on baro if we are likely to be in ground effect
if (getTakeoffExpected() || getTouchdownExpected()) {
posDownObsNoise *= frontend->gndEffectBaroScaler;
}
// 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
if (motorsArmed && getTakeoffExpected()) {
hgtMea = MAX(hgtMea, meaHgtAtTakeOff);
}
} else {
fuseHgtData = false;
}
// If we haven't fused height data for a while, then declare the height data as being timed out
// set timeout period based on whether we have vertical GPS velocity available to constrain drift
hgtRetryTime_ms = (useGpsVertVel && !velTimeout) ? frontend->hgtRetryTimeMode0_ms : frontend->hgtRetryTimeMode12_ms;
if (imuSampleTime_ms - lastHgtPassTime_ms > hgtRetryTime_ms) {
hgtTimeout = true;
} else {
hgtTimeout = false;
}
}
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