mirror of
https://github.com/ArduPilot/ardupilot
synced 2025-01-04 23:18:28 -04:00
39969e7d8e
AP_NavEKF3: Implement same maths as PX4/ecl EKF Replace attitude vector states with quaternions Remove gyro scale factor states Add XY accel delta velocity bias estimation Initial tuning Add GPS body frame offset compensation AP_NavEKF3: Fix bugs and consolidate aiding switch logic Switching in and out of aiding modes was being performed in more than one place and was using two variables. The reversion out of GPS mode due to prolonged loss of GPS was not working. This consolidates the logic and ensures that PV_AidingMode is only changed by the setAidingMode function. AP_NavEKF3: prevent multiple fusion mode changes per filter update AP_NavEKF3: Update tuning defaults AP_NavEKF3: Fix bug causing switching in and out of aiding If the GPS receiver was disconnected and no data received, then then the gpsGoodToAlign check did not get a chance to run and becasue it was previously true the EKF would switch back into aiding. This prevents this by ensuring that gpsGoodToAlign defaults to false when the check is not being performed. An additional check has also been dded to ensure that there is GPS data to fuse before we declare ready to use GPS. AP_NavEKF3: Fix bug preventing planes recovering from bad magnetometers This bug created a race condition whereby if the EKF had to reset the yaw to the GPS ground course to recover from a bad magnetometer, the new heading could be over-written by the bad magnetic heading when the plane reached the height for the scheduled reset. AP_NavEKF3: Improve switch-over to backup magnetometer When switching over to a back up magnetometer, ensure that the earth field estimate are reset. Otherwise mag earth field estimates due to the previous failed mag could cause data from the new mag to be rejected. AP_NavEKF3: enable automatic use of range finder height AP_NavEKF3: Fix bug in handling of invalid range data AP_NavEKF3: Fix height drift on ground using range finder without GPSAP_NavEKF3: AP_NavEKF3: Handle yaw jumps due to core switches AP_NavEKF3: Enable simultaneous GPS and optical flow use AP_NavEKF3: fix console status reporting AP_NavEKF3: send messages to mavlink instead of console This allows the GCS to better handle the display of messages to the user. AP_NavEKF3: replace deprecated function call AP_NavEKF3: Compensate for sensor body frame offsets AP_NavEKF3: Fix bug in median filter code AP_NavEKF3: save some memory in the position offsets in EKF3 We don't need to copy that vector3f for every sample. A uint8_t does the job AP_NavEKF3: Add fusion of range beacon data AP_NavEKF3: Bring up to date with EKF2 AP_NavEKF3: Misc range beacon updates AP_NavEKF3: Add mising accessors AP_NavEKF3: remove duplicate include AP_NavEKF3: Prevent NaN's when accessing range beacon debug data AP_NavEKF3: Update range beacon naming AP_NavEKF3: updates AP_NavEKF3: miscellaneous changes AP_NavEKF3: misc updates AP_NavEKF3: misc range beacons updates AP_NavEKF3: add missing rover default param
441 lines
31 KiB
C++
441 lines
31 KiB
C++
/// -*- 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
|
|
|
|
#include "AP_NavEKF3.h"
|
|
#include "AP_NavEKF3_core.h"
|
|
#include <AP_AHRS/AP_AHRS.h>
|
|
#include <AP_Vehicle/AP_Vehicle.h>
|
|
|
|
#include <stdio.h>
|
|
|
|
extern const AP_HAL::HAL& hal;
|
|
|
|
/********************************************************
|
|
* RESET FUNCTIONS *
|
|
********************************************************/
|
|
|
|
/********************************************************
|
|
* FUSE MEASURED_DATA *
|
|
********************************************************/
|
|
|
|
/*
|
|
* Fuse true airspeed measurements using explicit algebraic equations generated with Matlab symbolic toolbox.
|
|
* The script file used to generate these and other equations in this filter can be found here:
|
|
* https://github.com/priseborough/InertialNav/blob/master/derivations/RotationVectorAttitudeParameterisation/GenerateNavFilterEquations.m
|
|
*/
|
|
void NavEKF3_core::FuseAirspeed()
|
|
{
|
|
// start performance timer
|
|
hal.util->perf_begin(_perf_FuseAirspeed);
|
|
|
|
// declarations
|
|
float vn;
|
|
float ve;
|
|
float vd;
|
|
float vwn;
|
|
float vwe;
|
|
float EAS2TAS = _ahrs->get_EAS2TAS();
|
|
const float R_TAS = sq(constrain_float(frontend->_easNoise, 0.5f, 5.0f) * constrain_float(EAS2TAS, 0.9f, 10.0f));
|
|
float SH_TAS[3];
|
|
float SK_TAS[2];
|
|
Vector24 H_TAS = {};
|
|
float VtasPred;
|
|
|
|
// health is set bad until test passed
|
|
tasHealth = false;
|
|
|
|
// copy required states to local variable names
|
|
vn = stateStruct.velocity.x;
|
|
ve = stateStruct.velocity.y;
|
|
vd = stateStruct.velocity.z;
|
|
vwn = stateStruct.wind_vel.x;
|
|
vwe = stateStruct.wind_vel.y;
|
|
|
|
// calculate the predicted airspeed
|
|
VtasPred = norm((ve - vwe) , (vn - vwn) , vd);
|
|
// perform fusion of True Airspeed measurement
|
|
if (VtasPred > 1.0f)
|
|
{
|
|
// calculate observation jacobians
|
|
SH_TAS[0] = 1.0f/VtasPred;
|
|
SH_TAS[1] = (SH_TAS[0]*(2.0f*ve - 2.0f*vwe))*0.5f;
|
|
SH_TAS[2] = (SH_TAS[0]*(2.0f*vn - 2.0f*vwn))*0.5f;
|
|
H_TAS[4] = SH_TAS[2];
|
|
H_TAS[5] = SH_TAS[1];
|
|
H_TAS[6] = vd*SH_TAS[0];
|
|
H_TAS[22] = -SH_TAS[2];
|
|
H_TAS[23] = -SH_TAS[1];
|
|
// calculate Kalman gains
|
|
float temp = (R_TAS + SH_TAS[2]*(P[4][4]*SH_TAS[2] + P[5][4]*SH_TAS[1] - P[22][4]*SH_TAS[2] - P[23][4]*SH_TAS[1] + P[6][4]*vd*SH_TAS[0]) + SH_TAS[1]*(P[4][5]*SH_TAS[2] + P[5][5]*SH_TAS[1] - P[22][5]*SH_TAS[2] - P[23][5]*SH_TAS[1] + P[6][5]*vd*SH_TAS[0]) - SH_TAS[2]*(P[4][22]*SH_TAS[2] + P[5][22]*SH_TAS[1] - P[22][22]*SH_TAS[2] - P[23][22]*SH_TAS[1] + P[6][22]*vd*SH_TAS[0]) - SH_TAS[1]*(P[4][23]*SH_TAS[2] + P[5][23]*SH_TAS[1] - P[22][23]*SH_TAS[2] - P[23][23]*SH_TAS[1] + P[6][23]*vd*SH_TAS[0]) + vd*SH_TAS[0]*(P[4][6]*SH_TAS[2] + P[5][6]*SH_TAS[1] - P[22][6]*SH_TAS[2] - P[23][6]*SH_TAS[1] + P[6][6]*vd*SH_TAS[0]));
|
|
if (temp >= R_TAS) {
|
|
SK_TAS[0] = 1.0f / temp;
|
|
faultStatus.bad_airspeed = false;
|
|
} else {
|
|
// the calculation is badly conditioned, so we cannot perform fusion on this step
|
|
// we reset the covariance matrix and try again next measurement
|
|
CovarianceInit();
|
|
faultStatus.bad_airspeed = true;
|
|
return;
|
|
}
|
|
SK_TAS[1] = SH_TAS[1];
|
|
Kfusion[0] = SK_TAS[0]*(P[0][4]*SH_TAS[2] - P[0][22]*SH_TAS[2] + P[0][5]*SK_TAS[1] - P[0][23]*SK_TAS[1] + P[0][6]*vd*SH_TAS[0]);
|
|
Kfusion[1] = SK_TAS[0]*(P[1][4]*SH_TAS[2] - P[1][22]*SH_TAS[2] + P[1][5]*SK_TAS[1] - P[1][23]*SK_TAS[1] + P[1][6]*vd*SH_TAS[0]);
|
|
Kfusion[2] = SK_TAS[0]*(P[2][4]*SH_TAS[2] - P[2][22]*SH_TAS[2] + P[2][5]*SK_TAS[1] - P[2][23]*SK_TAS[1] + P[2][6]*vd*SH_TAS[0]);
|
|
Kfusion[3] = SK_TAS[0]*(P[3][4]*SH_TAS[2] - P[3][22]*SH_TAS[2] + P[3][5]*SK_TAS[1] - P[3][23]*SK_TAS[1] + P[3][6]*vd*SH_TAS[0]);
|
|
Kfusion[4] = SK_TAS[0]*(P[4][4]*SH_TAS[2] - P[4][22]*SH_TAS[2] + P[4][5]*SK_TAS[1] - P[4][23]*SK_TAS[1] + P[4][6]*vd*SH_TAS[0]);
|
|
Kfusion[5] = SK_TAS[0]*(P[5][4]*SH_TAS[2] - P[5][22]*SH_TAS[2] + P[5][5]*SK_TAS[1] - P[5][23]*SK_TAS[1] + P[5][6]*vd*SH_TAS[0]);
|
|
Kfusion[6] = SK_TAS[0]*(P[6][4]*SH_TAS[2] - P[6][22]*SH_TAS[2] + P[6][5]*SK_TAS[1] - P[6][23]*SK_TAS[1] + P[6][6]*vd*SH_TAS[0]);
|
|
Kfusion[7] = SK_TAS[0]*(P[7][4]*SH_TAS[2] - P[7][22]*SH_TAS[2] + P[7][5]*SK_TAS[1] - P[7][23]*SK_TAS[1] + P[7][6]*vd*SH_TAS[0]);
|
|
Kfusion[8] = SK_TAS[0]*(P[8][4]*SH_TAS[2] - P[8][22]*SH_TAS[2] + P[8][5]*SK_TAS[1] - P[8][23]*SK_TAS[1] + P[8][6]*vd*SH_TAS[0]);
|
|
Kfusion[9] = SK_TAS[0]*(P[9][4]*SH_TAS[2] - P[9][22]*SH_TAS[2] + P[9][5]*SK_TAS[1] - P[9][23]*SK_TAS[1] + P[9][6]*vd*SH_TAS[0]);
|
|
Kfusion[10] = SK_TAS[0]*(P[10][4]*SH_TAS[2] - P[10][22]*SH_TAS[2] + P[10][5]*SK_TAS[1] - P[10][23]*SK_TAS[1] + P[10][6]*vd*SH_TAS[0]);
|
|
Kfusion[11] = SK_TAS[0]*(P[11][4]*SH_TAS[2] - P[11][22]*SH_TAS[2] + P[11][5]*SK_TAS[1] - P[11][23]*SK_TAS[1] + P[11][6]*vd*SH_TAS[0]);
|
|
Kfusion[12] = SK_TAS[0]*(P[12][4]*SH_TAS[2] - P[12][22]*SH_TAS[2] + P[12][5]*SK_TAS[1] - P[12][23]*SK_TAS[1] + P[12][6]*vd*SH_TAS[0]);
|
|
Kfusion[13] = SK_TAS[0]*(P[13][4]*SH_TAS[2] - P[13][22]*SH_TAS[2] + P[13][5]*SK_TAS[1] - P[13][23]*SK_TAS[1] + P[13][6]*vd*SH_TAS[0]);
|
|
Kfusion[14] = SK_TAS[0]*(P[14][4]*SH_TAS[2] - P[14][22]*SH_TAS[2] + P[14][5]*SK_TAS[1] - P[14][23]*SK_TAS[1] + P[14][6]*vd*SH_TAS[0]);
|
|
Kfusion[15] = SK_TAS[0]*(P[15][4]*SH_TAS[2] - P[15][22]*SH_TAS[2] + P[15][5]*SK_TAS[1] - P[15][23]*SK_TAS[1] + P[15][6]*vd*SH_TAS[0]);
|
|
Kfusion[22] = SK_TAS[0]*(P[22][4]*SH_TAS[2] - P[22][22]*SH_TAS[2] + P[22][5]*SK_TAS[1] - P[22][23]*SK_TAS[1] + P[22][6]*vd*SH_TAS[0]);
|
|
Kfusion[23] = SK_TAS[0]*(P[23][4]*SH_TAS[2] - P[23][22]*SH_TAS[2] + P[23][5]*SK_TAS[1] - P[23][23]*SK_TAS[1] + P[23][6]*vd*SH_TAS[0]);
|
|
// zero Kalman gains to inhibit magnetic field state estimation
|
|
if (!inhibitMagStates) {
|
|
Kfusion[16] = SK_TAS[0]*(P[16][4]*SH_TAS[2] - P[16][22]*SH_TAS[2] + P[16][5]*SK_TAS[1] - P[16][23]*SK_TAS[1] + P[16][6]*vd*SH_TAS[0]);
|
|
Kfusion[17] = SK_TAS[0]*(P[17][4]*SH_TAS[2] - P[17][22]*SH_TAS[2] + P[17][5]*SK_TAS[1] - P[17][23]*SK_TAS[1] + P[17][6]*vd*SH_TAS[0]);
|
|
Kfusion[18] = SK_TAS[0]*(P[18][4]*SH_TAS[2] - P[18][22]*SH_TAS[2] + P[18][5]*SK_TAS[1] - P[18][23]*SK_TAS[1] + P[18][6]*vd*SH_TAS[0]);
|
|
Kfusion[19] = SK_TAS[0]*(P[19][4]*SH_TAS[2] - P[19][22]*SH_TAS[2] + P[19][5]*SK_TAS[1] - P[19][23]*SK_TAS[1] + P[19][6]*vd*SH_TAS[0]);
|
|
Kfusion[20] = SK_TAS[0]*(P[20][4]*SH_TAS[2] - P[20][22]*SH_TAS[2] + P[20][5]*SK_TAS[1] - P[20][23]*SK_TAS[1] + P[20][6]*vd*SH_TAS[0]);
|
|
Kfusion[21] = SK_TAS[0]*(P[21][4]*SH_TAS[2] - P[21][22]*SH_TAS[2] + P[21][5]*SK_TAS[1] - P[21][23]*SK_TAS[1] + P[21][6]*vd*SH_TAS[0]);
|
|
} else {
|
|
for (uint8_t i=16; i<=21; i++) {
|
|
Kfusion[i] = 0.0f;
|
|
}
|
|
}
|
|
|
|
// calculate measurement innovation variance
|
|
varInnovVtas = 1.0f/SK_TAS[0];
|
|
|
|
// calculate measurement innovation
|
|
innovVtas = VtasPred - tasDataDelayed.tas;
|
|
|
|
// calculate the innovation consistency test ratio
|
|
tasTestRatio = sq(innovVtas) / (sq(MAX(0.01f * (float)frontend->_tasInnovGate, 1.0f)) * varInnovVtas);
|
|
|
|
// fail if the ratio is > 1, but don't fail if bad IMU data
|
|
tasHealth = ((tasTestRatio < 1.0f) || badIMUdata);
|
|
tasTimeout = (imuSampleTime_ms - lastTasPassTime_ms) > frontend->tasRetryTime_ms;
|
|
|
|
// test the ratio before fusing data, forcing fusion if airspeed and position are timed out as we have no choice but to try and use airspeed to constrain error growth
|
|
if (tasHealth || (tasTimeout && posTimeout)) {
|
|
|
|
// restart the counter
|
|
lastTasPassTime_ms = imuSampleTime_ms;
|
|
|
|
// correct the state vector
|
|
for (uint8_t j= 0; j<=stateIndexLim; j++) {
|
|
statesArray[j] = statesArray[j] - Kfusion[j] * innovVtas;
|
|
}
|
|
stateStruct.quat.normalize();
|
|
|
|
// correct the covariance P = (I - K*H)*P
|
|
// take advantage of the empty columns in KH to reduce the
|
|
// number of operations
|
|
for (unsigned i = 0; i<=stateIndexLim; i++) {
|
|
for (unsigned j = 0; j<=3; j++) {
|
|
KH[i][j] = 0.0f;
|
|
}
|
|
for (unsigned j = 4; j<=6; j++) {
|
|
KH[i][j] = Kfusion[i] * H_TAS[j];
|
|
}
|
|
for (unsigned j = 7; j<=21; j++) {
|
|
KH[i][j] = 0.0f;
|
|
}
|
|
for (unsigned j = 22; j<=23; j++) {
|
|
KH[i][j] = Kfusion[i] * H_TAS[j];
|
|
}
|
|
}
|
|
for (unsigned j = 0; j<=stateIndexLim; j++) {
|
|
for (unsigned i = 0; i<=stateIndexLim; i++) {
|
|
ftype res = 0;
|
|
res += KH[i][4] * P[4][j];
|
|
res += KH[i][5] * P[5][j];
|
|
res += KH[i][6] * P[6][j];
|
|
res += KH[i][22] * P[22][j];
|
|
res += KH[i][23] * P[23][j];
|
|
KHP[i][j] = res;
|
|
}
|
|
}
|
|
for (unsigned i = 0; i<=stateIndexLim; i++) {
|
|
for (unsigned j = 0; j<=stateIndexLim; j++) {
|
|
P[i][j] = P[i][j] - KHP[i][j];
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// force the covariance matrix to me symmetrical and limit the variances to prevent ill-condiioning.
|
|
ForceSymmetry();
|
|
ConstrainVariances();
|
|
|
|
// stop performance timer
|
|
hal.util->perf_end(_perf_FuseAirspeed);
|
|
}
|
|
|
|
// select fusion of true airspeed measurements
|
|
void NavEKF3_core::SelectTasFusion()
|
|
{
|
|
// 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 locking out fusion of other measurements
|
|
if (magFusePerformed && dtIMUavg < 0.005f && !airSpdFusionDelayed) {
|
|
airSpdFusionDelayed = true;
|
|
return;
|
|
} else {
|
|
airSpdFusionDelayed = false;
|
|
}
|
|
|
|
// get true airspeed measurement
|
|
readAirSpdData();
|
|
|
|
// If we haven't received airspeed data for a while, then declare the airspeed data as being timed out
|
|
if (imuSampleTime_ms - tasDataNew.time_ms > frontend->tasRetryTime_ms) {
|
|
tasTimeout = true;
|
|
}
|
|
|
|
// if the filter is initialised, wind states are not inhibited and we have data to fuse, then perform TAS fusion
|
|
if (tasDataToFuse && statesInitialised && !inhibitWindStates) {
|
|
FuseAirspeed();
|
|
prevTasStep_ms = imuSampleTime_ms;
|
|
}
|
|
}
|
|
|
|
|
|
// select fusion of synthetic sideslip measurements
|
|
// synthetic sidelip fusion only works for fixed wing aircraft and relies on the average sideslip being close to zero
|
|
// it requires a stable wind for best results and should not be used for aerobatic flight with manoeuvres that induce large sidslip angles (eg knife-edge, spins, etc)
|
|
void NavEKF3_core::SelectBetaFusion()
|
|
{
|
|
// 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 && !sideSlipFusionDelayed) {
|
|
sideSlipFusionDelayed = true;
|
|
return;
|
|
} else {
|
|
sideSlipFusionDelayed = false;
|
|
}
|
|
|
|
// set true when the fusion time interval has triggered
|
|
bool f_timeTrigger = ((imuSampleTime_ms - prevBetaStep_ms) >= frontend->betaAvg_ms);
|
|
// set true when use of synthetic sideslip fusion is necessary because we have limited sensor data or are dead reckoning position
|
|
bool f_required = !(use_compass() && useAirspeed() && ((imuSampleTime_ms - lastPosPassTime_ms) < frontend->posRetryTimeNoVel_ms));
|
|
// set true when sideslip fusion is feasible (requires zero sideslip assumption to be valid and use of wind states)
|
|
bool f_feasible = (assume_zero_sideslip() && !inhibitWindStates);
|
|
// use synthetic sideslip fusion if feasible, required and enough time has lapsed since the last fusion
|
|
if (f_feasible && f_required && f_timeTrigger) {
|
|
FuseSideslip();
|
|
prevBetaStep_ms = imuSampleTime_ms;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Fuse sythetic sideslip measurement of zero using explicit algebraic equations generated with Matlab symbolic toolbox.
|
|
* The script file used to generate these and other equations in this filter can be found here:
|
|
* https://github.com/priseborough/InertialNav/blob/master/derivations/RotationVectorAttitudeParameterisation/GenerateNavFilterEquations.m
|
|
*/
|
|
void NavEKF3_core::FuseSideslip()
|
|
{
|
|
// start performance timer
|
|
hal.util->perf_begin(_perf_FuseSideslip);
|
|
|
|
// declarations
|
|
float q0;
|
|
float q1;
|
|
float q2;
|
|
float q3;
|
|
float vn;
|
|
float ve;
|
|
float vd;
|
|
float vwn;
|
|
float vwe;
|
|
const float R_BETA = 0.03f; // assume a sideslip angle RMS of ~10 deg
|
|
Vector13 SH_BETA;
|
|
Vector8 SK_BETA;
|
|
Vector3f vel_rel_wind;
|
|
Vector24 H_BETA;
|
|
float innovBeta;
|
|
|
|
// copy required states to local variable names
|
|
q0 = stateStruct.quat[0];
|
|
q1 = stateStruct.quat[1];
|
|
q2 = stateStruct.quat[2];
|
|
q3 = stateStruct.quat[3];
|
|
vn = stateStruct.velocity.x;
|
|
ve = stateStruct.velocity.y;
|
|
vd = stateStruct.velocity.z;
|
|
vwn = stateStruct.wind_vel.x;
|
|
vwe = stateStruct.wind_vel.y;
|
|
|
|
// calculate predicted wind relative velocity in NED
|
|
vel_rel_wind.x = vn - vwn;
|
|
vel_rel_wind.y = ve - vwe;
|
|
vel_rel_wind.z = vd;
|
|
|
|
// rotate into body axes
|
|
vel_rel_wind = prevTnb * vel_rel_wind;
|
|
|
|
// perform fusion of assumed sideslip = 0
|
|
if (vel_rel_wind.x > 5.0f)
|
|
{
|
|
// Calculate observation jacobians
|
|
SH_BETA[0] = (vn - vwn)*(sq(q0) + sq(q1) - sq(q2) - sq(q3)) - vd*(2*q0*q2 - 2*q1*q3) + (ve - vwe)*(2*q0*q3 + 2*q1*q2);
|
|
if (fabsf(SH_BETA[0]) <= 1e-9f) {
|
|
faultStatus.bad_sideslip = true;
|
|
return;
|
|
} else {
|
|
faultStatus.bad_sideslip = false;
|
|
}
|
|
SH_BETA[1] = (ve - vwe)*(sq(q0) - sq(q1) + sq(q2) - sq(q3)) + vd*(2*q0*q1 + 2*q2*q3) - (vn - vwn)*(2*q0*q3 - 2*q1*q2);
|
|
SH_BETA[2] = vn - vwn;
|
|
SH_BETA[3] = ve - vwe;
|
|
SH_BETA[4] = 1/sq(SH_BETA[0]);
|
|
SH_BETA[5] = 1/SH_BETA[0];
|
|
SH_BETA[6] = SH_BETA[5]*(sq(q0) - sq(q1) + sq(q2) - sq(q3));
|
|
SH_BETA[7] = sq(q0) + sq(q1) - sq(q2) - sq(q3);
|
|
SH_BETA[8] = 2*q0*SH_BETA[3] - 2*q3*SH_BETA[2] + 2*q1*vd;
|
|
SH_BETA[9] = 2*q0*SH_BETA[2] + 2*q3*SH_BETA[3] - 2*q2*vd;
|
|
SH_BETA[10] = 2*q2*SH_BETA[2] - 2*q1*SH_BETA[3] + 2*q0*vd;
|
|
SH_BETA[11] = 2*q1*SH_BETA[2] + 2*q2*SH_BETA[3] + 2*q3*vd;
|
|
SH_BETA[12] = 2*q0*q3;
|
|
|
|
H_BETA[0] = SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9];
|
|
H_BETA[1] = SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11];
|
|
H_BETA[2] = SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10];
|
|
H_BETA[3] = - SH_BETA[5]*SH_BETA[9] - SH_BETA[1]*SH_BETA[4]*SH_BETA[8];
|
|
H_BETA[4] = - SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) - SH_BETA[1]*SH_BETA[4]*SH_BETA[7];
|
|
H_BETA[5] = SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2);
|
|
H_BETA[6] = SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3);
|
|
for (uint8_t i=7; i<=21; i++) {
|
|
H_BETA[i] = 0.0f;
|
|
}
|
|
H_BETA[22] = SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7];
|
|
H_BETA[23] = SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2) - SH_BETA[6];
|
|
|
|
// Calculate Kalman gains
|
|
float temp = (R_BETA - (SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7])*(P[22][4]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P[4][4]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P[5][4]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) - P[23][4]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) + P[0][4]*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P[1][4]*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P[2][4]*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P[3][4]*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P[6][4]*(SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))) + (SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7])*(P[22][22]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P[4][22]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P[5][22]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) - P[23][22]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) + P[0][22]*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P[1][22]*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P[2][22]*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P[3][22]*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P[6][22]*(SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))) + (SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2))*(P[22][5]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P[4][5]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P[5][5]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) - P[23][5]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) + P[0][5]*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P[1][5]*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P[2][5]*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P[3][5]*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P[6][5]*(SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))) - (SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2))*(P[22][23]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P[4][23]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P[5][23]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) - P[23][23]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) + P[0][23]*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P[1][23]*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P[2][23]*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P[3][23]*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P[6][23]*(SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))) + (SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9])*(P[22][0]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P[4][0]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P[5][0]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) - P[23][0]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) + P[0][0]*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P[1][0]*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P[2][0]*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P[3][0]*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P[6][0]*(SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))) + (SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11])*(P[22][1]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P[4][1]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P[5][1]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) - P[23][1]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) + P[0][1]*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P[1][1]*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P[2][1]*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P[3][1]*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P[6][1]*(SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))) + (SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10])*(P[22][2]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P[4][2]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P[5][2]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) - P[23][2]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) + P[0][2]*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P[1][2]*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P[2][2]*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P[3][2]*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P[6][2]*(SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))) - (SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8])*(P[22][3]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P[4][3]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P[5][3]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) - P[23][3]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) + P[0][3]*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P[1][3]*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P[2][3]*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P[3][3]*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P[6][3]*(SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))) + (SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))*(P[22][6]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P[4][6]*(SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P[5][6]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) - P[23][6]*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2)) + P[0][6]*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P[1][6]*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P[2][6]*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P[3][6]*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P[6][6]*(SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3))));
|
|
if (temp >= R_BETA) {
|
|
SK_BETA[0] = 1.0f / temp;
|
|
faultStatus.bad_sideslip = false;
|
|
} else {
|
|
// the calculation is badly conditioned, so we cannot perform fusion on this step
|
|
// we reset the covariance matrix and try again next measurement
|
|
CovarianceInit();
|
|
faultStatus.bad_sideslip = true;
|
|
return;
|
|
}
|
|
SK_BETA[1] = SH_BETA[5]*(SH_BETA[12] - 2*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7];
|
|
SK_BETA[2] = SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2*q1*q2);
|
|
SK_BETA[3] = SH_BETA[5]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2*q0*q2 - 2*q1*q3);
|
|
SK_BETA[4] = SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11];
|
|
SK_BETA[5] = SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9];
|
|
SK_BETA[6] = SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10];
|
|
SK_BETA[7] = SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8];
|
|
|
|
Kfusion[0] = SK_BETA[0]*(P[0][0]*SK_BETA[5] + P[0][1]*SK_BETA[4] - P[0][4]*SK_BETA[1] + P[0][5]*SK_BETA[2] + P[0][2]*SK_BETA[6] + P[0][6]*SK_BETA[3] - P[0][3]*SK_BETA[7] + P[0][22]*SK_BETA[1] - P[0][23]*SK_BETA[2]);
|
|
Kfusion[1] = SK_BETA[0]*(P[1][0]*SK_BETA[5] + P[1][1]*SK_BETA[4] - P[1][4]*SK_BETA[1] + P[1][5]*SK_BETA[2] + P[1][2]*SK_BETA[6] + P[1][6]*SK_BETA[3] - P[1][3]*SK_BETA[7] + P[1][22]*SK_BETA[1] - P[1][23]*SK_BETA[2]);
|
|
Kfusion[2] = SK_BETA[0]*(P[2][0]*SK_BETA[5] + P[2][1]*SK_BETA[4] - P[2][4]*SK_BETA[1] + P[2][5]*SK_BETA[2] + P[2][2]*SK_BETA[6] + P[2][6]*SK_BETA[3] - P[2][3]*SK_BETA[7] + P[2][22]*SK_BETA[1] - P[2][23]*SK_BETA[2]);
|
|
Kfusion[3] = SK_BETA[0]*(P[3][0]*SK_BETA[5] + P[3][1]*SK_BETA[4] - P[3][4]*SK_BETA[1] + P[3][5]*SK_BETA[2] + P[3][2]*SK_BETA[6] + P[3][6]*SK_BETA[3] - P[3][3]*SK_BETA[7] + P[3][22]*SK_BETA[1] - P[3][23]*SK_BETA[2]);
|
|
Kfusion[4] = SK_BETA[0]*(P[4][0]*SK_BETA[5] + P[4][1]*SK_BETA[4] - P[4][4]*SK_BETA[1] + P[4][5]*SK_BETA[2] + P[4][2]*SK_BETA[6] + P[4][6]*SK_BETA[3] - P[4][3]*SK_BETA[7] + P[4][22]*SK_BETA[1] - P[4][23]*SK_BETA[2]);
|
|
Kfusion[5] = SK_BETA[0]*(P[5][0]*SK_BETA[5] + P[5][1]*SK_BETA[4] - P[5][4]*SK_BETA[1] + P[5][5]*SK_BETA[2] + P[5][2]*SK_BETA[6] + P[5][6]*SK_BETA[3] - P[5][3]*SK_BETA[7] + P[5][22]*SK_BETA[1] - P[5][23]*SK_BETA[2]);
|
|
Kfusion[6] = SK_BETA[0]*(P[6][0]*SK_BETA[5] + P[6][1]*SK_BETA[4] - P[6][4]*SK_BETA[1] + P[6][5]*SK_BETA[2] + P[6][2]*SK_BETA[6] + P[6][6]*SK_BETA[3] - P[6][3]*SK_BETA[7] + P[6][22]*SK_BETA[1] - P[6][23]*SK_BETA[2]);
|
|
Kfusion[7] = SK_BETA[0]*(P[7][0]*SK_BETA[5] + P[7][1]*SK_BETA[4] - P[7][4]*SK_BETA[1] + P[7][5]*SK_BETA[2] + P[7][2]*SK_BETA[6] + P[7][6]*SK_BETA[3] - P[7][3]*SK_BETA[7] + P[7][22]*SK_BETA[1] - P[7][23]*SK_BETA[2]);
|
|
Kfusion[8] = SK_BETA[0]*(P[8][0]*SK_BETA[5] + P[8][1]*SK_BETA[4] - P[8][4]*SK_BETA[1] + P[8][5]*SK_BETA[2] + P[8][2]*SK_BETA[6] + P[8][6]*SK_BETA[3] - P[8][3]*SK_BETA[7] + P[8][22]*SK_BETA[1] - P[8][23]*SK_BETA[2]);
|
|
Kfusion[9] = SK_BETA[0]*(P[9][0]*SK_BETA[5] + P[9][1]*SK_BETA[4] - P[9][4]*SK_BETA[1] + P[9][5]*SK_BETA[2] + P[9][2]*SK_BETA[6] + P[9][6]*SK_BETA[3] - P[9][3]*SK_BETA[7] + P[9][22]*SK_BETA[1] - P[9][23]*SK_BETA[2]);
|
|
Kfusion[10] = SK_BETA[0]*(P[10][0]*SK_BETA[5] + P[10][1]*SK_BETA[4] - P[10][4]*SK_BETA[1] + P[10][5]*SK_BETA[2] + P[10][2]*SK_BETA[6] + P[10][6]*SK_BETA[3] - P[10][3]*SK_BETA[7] + P[10][22]*SK_BETA[1] - P[10][23]*SK_BETA[2]);
|
|
Kfusion[11] = SK_BETA[0]*(P[11][0]*SK_BETA[5] + P[11][1]*SK_BETA[4] - P[11][4]*SK_BETA[1] + P[11][5]*SK_BETA[2] + P[11][2]*SK_BETA[6] + P[11][6]*SK_BETA[3] - P[11][3]*SK_BETA[7] + P[11][22]*SK_BETA[1] - P[11][23]*SK_BETA[2]);
|
|
Kfusion[12] = SK_BETA[0]*(P[12][0]*SK_BETA[5] + P[12][1]*SK_BETA[4] - P[12][4]*SK_BETA[1] + P[12][5]*SK_BETA[2] + P[12][2]*SK_BETA[6] + P[12][6]*SK_BETA[3] - P[12][3]*SK_BETA[7] + P[12][22]*SK_BETA[1] - P[12][23]*SK_BETA[2]);
|
|
Kfusion[13] = SK_BETA[0]*(P[13][0]*SK_BETA[5] + P[13][1]*SK_BETA[4] - P[13][4]*SK_BETA[1] + P[13][5]*SK_BETA[2] + P[13][2]*SK_BETA[6] + P[13][6]*SK_BETA[3] - P[13][3]*SK_BETA[7] + P[13][22]*SK_BETA[1] - P[13][23]*SK_BETA[2]);
|
|
Kfusion[14] = SK_BETA[0]*(P[14][0]*SK_BETA[5] + P[14][1]*SK_BETA[4] - P[14][4]*SK_BETA[1] + P[14][5]*SK_BETA[2] + P[14][2]*SK_BETA[6] + P[14][6]*SK_BETA[3] - P[14][3]*SK_BETA[7] + P[14][22]*SK_BETA[1] - P[14][23]*SK_BETA[2]);
|
|
Kfusion[15] = SK_BETA[0]*(P[15][0]*SK_BETA[5] + P[15][1]*SK_BETA[4] - P[15][4]*SK_BETA[1] + P[15][5]*SK_BETA[2] + P[15][2]*SK_BETA[6] + P[15][6]*SK_BETA[3] - P[15][3]*SK_BETA[7] + P[15][22]*SK_BETA[1] - P[15][23]*SK_BETA[2]);
|
|
Kfusion[22] = SK_BETA[0]*(P[22][0]*SK_BETA[5] + P[22][1]*SK_BETA[4] - P[22][4]*SK_BETA[1] + P[22][5]*SK_BETA[2] + P[22][2]*SK_BETA[6] + P[22][6]*SK_BETA[3] - P[22][3]*SK_BETA[7] + P[22][22]*SK_BETA[1] - P[22][23]*SK_BETA[2]);
|
|
Kfusion[23] = SK_BETA[0]*(P[23][0]*SK_BETA[5] + P[23][1]*SK_BETA[4] - P[23][4]*SK_BETA[1] + P[23][5]*SK_BETA[2] + P[23][2]*SK_BETA[6] + P[23][6]*SK_BETA[3] - P[23][3]*SK_BETA[7] + P[23][22]*SK_BETA[1] - P[23][23]*SK_BETA[2]);
|
|
// zero Kalman gains to inhibit magnetic field state estimation
|
|
if (!inhibitMagStates) {
|
|
Kfusion[16] = SK_BETA[0]*(P[16][0]*SK_BETA[5] + P[16][1]*SK_BETA[4] - P[16][4]*SK_BETA[1] + P[16][5]*SK_BETA[2] + P[16][2]*SK_BETA[6] + P[16][6]*SK_BETA[3] - P[16][3]*SK_BETA[7] + P[16][22]*SK_BETA[1] - P[16][23]*SK_BETA[2]);
|
|
Kfusion[17] = SK_BETA[0]*(P[17][0]*SK_BETA[5] + P[17][1]*SK_BETA[4] - P[17][4]*SK_BETA[1] + P[17][5]*SK_BETA[2] + P[17][2]*SK_BETA[6] + P[17][6]*SK_BETA[3] - P[17][3]*SK_BETA[7] + P[17][22]*SK_BETA[1] - P[17][23]*SK_BETA[2]);
|
|
Kfusion[18] = SK_BETA[0]*(P[18][0]*SK_BETA[5] + P[18][1]*SK_BETA[4] - P[18][4]*SK_BETA[1] + P[18][5]*SK_BETA[2] + P[18][2]*SK_BETA[6] + P[18][6]*SK_BETA[3] - P[18][3]*SK_BETA[7] + P[18][22]*SK_BETA[1] - P[18][23]*SK_BETA[2]);
|
|
Kfusion[19] = SK_BETA[0]*(P[19][0]*SK_BETA[5] + P[19][1]*SK_BETA[4] - P[19][4]*SK_BETA[1] + P[19][5]*SK_BETA[2] + P[19][2]*SK_BETA[6] + P[19][6]*SK_BETA[3] - P[19][3]*SK_BETA[7] + P[19][22]*SK_BETA[1] - P[19][23]*SK_BETA[2]);
|
|
Kfusion[20] = SK_BETA[0]*(P[20][0]*SK_BETA[5] + P[20][1]*SK_BETA[4] - P[20][4]*SK_BETA[1] + P[20][5]*SK_BETA[2] + P[20][2]*SK_BETA[6] + P[20][6]*SK_BETA[3] - P[20][3]*SK_BETA[7] + P[20][22]*SK_BETA[1] - P[20][23]*SK_BETA[2]);
|
|
Kfusion[21] = SK_BETA[0]*(P[21][0]*SK_BETA[5] + P[21][1]*SK_BETA[4] - P[21][4]*SK_BETA[1] + P[21][5]*SK_BETA[2] + P[21][2]*SK_BETA[6] + P[21][6]*SK_BETA[3] - P[21][3]*SK_BETA[7] + P[21][22]*SK_BETA[1] - P[21][23]*SK_BETA[2]);
|
|
} else {
|
|
for (uint8_t i=16; i<=21; i++) {
|
|
Kfusion[i] = 0.0f;
|
|
}
|
|
}
|
|
|
|
// calculate predicted sideslip angle and innovation using small angle approximation
|
|
innovBeta = vel_rel_wind.y / vel_rel_wind.x;
|
|
|
|
// reject measurement if greater than 3-sigma inconsistency
|
|
if (innovBeta > 0.5f) {
|
|
return;
|
|
}
|
|
|
|
// correct the state vector
|
|
for (uint8_t j= 0; j<=stateIndexLim; j++) {
|
|
statesArray[j] = statesArray[j] - Kfusion[j] * innovBeta;
|
|
}
|
|
stateStruct.quat.normalize();
|
|
|
|
// correct the covariance P = (I - K*H)*P
|
|
// take advantage of the empty columns in KH to reduce the
|
|
// number of operations
|
|
for (unsigned i = 0; i<=stateIndexLim; i++) {
|
|
for (unsigned j = 0; j<=6; j++) {
|
|
KH[i][j] = Kfusion[i] * H_BETA[j];
|
|
}
|
|
for (unsigned j = 7; j<=21; j++) {
|
|
KH[i][j] = 0.0f;
|
|
}
|
|
for (unsigned j = 22; j<=23; j++) {
|
|
KH[i][j] = Kfusion[i] * H_BETA[j];
|
|
}
|
|
}
|
|
for (unsigned j = 0; j<=stateIndexLim; j++) {
|
|
for (unsigned i = 0; i<=stateIndexLim; i++) {
|
|
ftype res = 0;
|
|
res += KH[i][0] * P[0][j];
|
|
res += KH[i][1] * P[1][j];
|
|
res += KH[i][2] * P[2][j];
|
|
res += KH[i][3] * P[3][j];
|
|
res += KH[i][4] * P[4][j];
|
|
res += KH[i][5] * P[5][j];
|
|
res += KH[i][6] * P[6][j];
|
|
res += KH[i][22] * P[22][j];
|
|
res += KH[i][23] * P[23][j];
|
|
KHP[i][j] = res;
|
|
}
|
|
}
|
|
for (unsigned i = 0; i<=stateIndexLim; i++) {
|
|
for (unsigned 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-condiioning.
|
|
ForceSymmetry();
|
|
ConstrainVariances();
|
|
|
|
// stop the performance timer
|
|
hal.util->perf_end(_perf_FuseSideslip);
|
|
}
|
|
|
|
/********************************************************
|
|
* MISC FUNCTIONS *
|
|
********************************************************/
|
|
|
|
|
|
#endif // HAL_CPU_CLASS
|