ddb7d92fc8
The airspeed observation buffer was only being checked when new data arrived instead of every frame which introduced some timing jitter. The buffer is now checked every filer update step. The duplication and inconsistent naming of booleans used to indicate availability f data has been fixed.
446 lines
29 KiB
C++
446 lines
29 KiB
C++
/// -*- tab-width: 4; Mode: C++; c-basic-offset: 4; indent-tabs-mode: nil -*-
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#include <AP_HAL/AP_HAL.h>
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#if HAL_CPU_CLASS >= HAL_CPU_CLASS_150
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#include "AP_NavEKF2.h"
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#include "AP_NavEKF2_core.h"
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#include <AP_AHRS/AP_AHRS.h>
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#include <AP_Vehicle/AP_Vehicle.h>
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#include <stdio.h>
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extern const AP_HAL::HAL& hal;
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/********************************************************
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* RESET FUNCTIONS *
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********************************************************/
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/********************************************************
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* FUSE MEASURED_DATA *
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********************************************************/
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/*
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* Fuse true airspeed measurements using explicit algebraic equations generated with Matlab symbolic toolbox.
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* The script file used to generate these and other equations in this filter can be found here:
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* https://github.com/priseborough/InertialNav/blob/master/derivations/RotationVectorAttitudeParameterisation/GenerateNavFilterEquations.m
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*/
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void NavEKF2_core::FuseAirspeed()
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{
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// start performance timer
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hal.util->perf_begin(_perf_FuseAirspeed);
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// declarations
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float vn;
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float ve;
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float vd;
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float vwn;
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float vwe;
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float EAS2TAS = _ahrs->get_EAS2TAS();
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const float R_TAS = sq(constrain_float(frontend->_easNoise, 0.5f, 5.0f) * constrain_float(EAS2TAS, 0.9f, 10.0f));
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Vector3 SH_TAS;
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float SK_TAS;
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Vector24 H_TAS;
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float VtasPred;
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// health is set bad until test passed
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tasHealth = false;
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// copy required states to local variable names
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vn = stateStruct.velocity.x;
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ve = stateStruct.velocity.y;
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vd = stateStruct.velocity.z;
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vwn = stateStruct.wind_vel.x;
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vwe = stateStruct.wind_vel.y;
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// calculate the predicted airspeed
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VtasPred = pythagorous3((ve - vwe) , (vn - vwn) , vd);
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// perform fusion of True Airspeed measurement
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if (VtasPred > 1.0f)
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{
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// calculate observation jacobians
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SH_TAS[0] = 1/(sqrt(sq(ve - vwe) + sq(vn - vwn) + sq(vd)));
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SH_TAS[1] = (SH_TAS[0]*(2*ve - 2*vwe))/2;
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SH_TAS[2] = (SH_TAS[0]*(2*vn - 2*vwn))/2;
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for (uint8_t i=0; i<=2; i++) H_TAS[i] = 0.0f;
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H_TAS[3] = SH_TAS[2];
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H_TAS[4] = SH_TAS[1];
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H_TAS[5] = vd*SH_TAS[0];
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H_TAS[22] = -SH_TAS[2];
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H_TAS[23] = -SH_TAS[1];
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for (uint8_t i=6; i<=21; i++) H_TAS[i] = 0.0f;
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// calculate Kalman gains
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float temp = (R_TAS + SH_TAS[2]*(P[3][3]*SH_TAS[2] + P[4][3]*SH_TAS[1] - P[22][3]*SH_TAS[2] - P[23][3]*SH_TAS[1] + P[5][3]*vd*SH_TAS[0]) + SH_TAS[1]*(P[3][4]*SH_TAS[2] + P[4][4]*SH_TAS[1] - P[22][4]*SH_TAS[2] - P[23][4]*SH_TAS[1] + P[5][4]*vd*SH_TAS[0]) - SH_TAS[2]*(P[3][22]*SH_TAS[2] + P[4][22]*SH_TAS[1] - P[22][22]*SH_TAS[2] - P[23][22]*SH_TAS[1] + P[5][22]*vd*SH_TAS[0]) - SH_TAS[1]*(P[3][23]*SH_TAS[2] + P[4][23]*SH_TAS[1] - P[22][23]*SH_TAS[2] - P[23][23]*SH_TAS[1] + P[5][23]*vd*SH_TAS[0]) + vd*SH_TAS[0]*(P[3][5]*SH_TAS[2] + P[4][5]*SH_TAS[1] - P[22][5]*SH_TAS[2] - P[23][5]*SH_TAS[1] + P[5][5]*vd*SH_TAS[0]));
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if (temp >= R_TAS) {
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SK_TAS = 1.0f / temp;
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faultStatus.bad_airspeed = false;
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} else {
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// the calculation is badly conditioned, so we cannot perform fusion on this step
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// we reset the covariance matrix and try again next measurement
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CovarianceInit();
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faultStatus.bad_airspeed = true;
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return;
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}
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Kfusion[0] = SK_TAS*(P[0][3]*SH_TAS[2] - P[0][22]*SH_TAS[2] + P[0][4]*SH_TAS[1] - P[0][23]*SH_TAS[1] + P[0][5]*vd*SH_TAS[0]);
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Kfusion[1] = SK_TAS*(P[1][3]*SH_TAS[2] - P[1][22]*SH_TAS[2] + P[1][4]*SH_TAS[1] - P[1][23]*SH_TAS[1] + P[1][5]*vd*SH_TAS[0]);
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Kfusion[2] = SK_TAS*(P[2][3]*SH_TAS[2] - P[2][22]*SH_TAS[2] + P[2][4]*SH_TAS[1] - P[2][23]*SH_TAS[1] + P[2][5]*vd*SH_TAS[0]);
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Kfusion[3] = SK_TAS*(P[3][3]*SH_TAS[2] - P[3][22]*SH_TAS[2] + P[3][4]*SH_TAS[1] - P[3][23]*SH_TAS[1] + P[3][5]*vd*SH_TAS[0]);
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Kfusion[4] = SK_TAS*(P[4][3]*SH_TAS[2] - P[4][22]*SH_TAS[2] + P[4][4]*SH_TAS[1] - P[4][23]*SH_TAS[1] + P[4][5]*vd*SH_TAS[0]);
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Kfusion[5] = SK_TAS*(P[5][3]*SH_TAS[2] - P[5][22]*SH_TAS[2] + P[5][4]*SH_TAS[1] - P[5][23]*SH_TAS[1] + P[5][5]*vd*SH_TAS[0]);
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Kfusion[6] = SK_TAS*(P[6][3]*SH_TAS[2] - P[6][22]*SH_TAS[2] + P[6][4]*SH_TAS[1] - P[6][23]*SH_TAS[1] + P[6][5]*vd*SH_TAS[0]);
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Kfusion[7] = SK_TAS*(P[7][3]*SH_TAS[2] - P[7][22]*SH_TAS[2] + P[7][4]*SH_TAS[1] - P[7][23]*SH_TAS[1] + P[7][5]*vd*SH_TAS[0]);
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Kfusion[8] = SK_TAS*(P[8][3]*SH_TAS[2] - P[8][22]*SH_TAS[2] + P[8][4]*SH_TAS[1] - P[8][23]*SH_TAS[1] + P[8][5]*vd*SH_TAS[0]);
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Kfusion[9] = SK_TAS*(P[9][3]*SH_TAS[2] - P[9][22]*SH_TAS[2] + P[9][4]*SH_TAS[1] - P[9][23]*SH_TAS[1] + P[9][5]*vd*SH_TAS[0]);
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Kfusion[10] = SK_TAS*(P[10][3]*SH_TAS[2] - P[10][22]*SH_TAS[2] + P[10][4]*SH_TAS[1] - P[10][23]*SH_TAS[1] + P[10][5]*vd*SH_TAS[0]);
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Kfusion[11] = SK_TAS*(P[11][3]*SH_TAS[2] - P[11][22]*SH_TAS[2] + P[11][4]*SH_TAS[1] - P[11][23]*SH_TAS[1] + P[11][5]*vd*SH_TAS[0]);
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Kfusion[12] = SK_TAS*(P[12][3]*SH_TAS[2] - P[12][22]*SH_TAS[2] + P[12][4]*SH_TAS[1] - P[12][23]*SH_TAS[1] + P[12][5]*vd*SH_TAS[0]);
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Kfusion[13] = SK_TAS*(P[13][3]*SH_TAS[2] - P[13][22]*SH_TAS[2] + P[13][4]*SH_TAS[1] - P[13][23]*SH_TAS[1] + P[13][5]*vd*SH_TAS[0]);
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Kfusion[14] = SK_TAS*(P[14][3]*SH_TAS[2] - P[14][22]*SH_TAS[2] + P[14][4]*SH_TAS[1] - P[14][23]*SH_TAS[1] + P[14][5]*vd*SH_TAS[0]);
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Kfusion[15] = SK_TAS*(P[15][3]*SH_TAS[2] - P[15][22]*SH_TAS[2] + P[15][4]*SH_TAS[1] - P[15][23]*SH_TAS[1] + P[15][5]*vd*SH_TAS[0]);
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Kfusion[22] = SK_TAS*(P[22][3]*SH_TAS[2] - P[22][22]*SH_TAS[2] + P[22][4]*SH_TAS[1] - P[22][23]*SH_TAS[1] + P[22][5]*vd*SH_TAS[0]);
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Kfusion[23] = SK_TAS*(P[23][3]*SH_TAS[2] - P[23][22]*SH_TAS[2] + P[23][4]*SH_TAS[1] - P[23][23]*SH_TAS[1] + P[23][5]*vd*SH_TAS[0]);
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// zero Kalman gains to inhibit magnetic field state estimation
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if (!inhibitMagStates) {
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Kfusion[16] = SK_TAS*(P[16][3]*SH_TAS[2] - P[16][22]*SH_TAS[2] + P[16][4]*SH_TAS[1] - P[16][23]*SH_TAS[1] + P[16][5]*vd*SH_TAS[0]);
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Kfusion[17] = SK_TAS*(P[17][3]*SH_TAS[2] - P[17][22]*SH_TAS[2] + P[17][4]*SH_TAS[1] - P[17][23]*SH_TAS[1] + P[17][5]*vd*SH_TAS[0]);
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Kfusion[18] = SK_TAS*(P[18][3]*SH_TAS[2] - P[18][22]*SH_TAS[2] + P[18][4]*SH_TAS[1] - P[18][23]*SH_TAS[1] + P[18][5]*vd*SH_TAS[0]);
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Kfusion[19] = SK_TAS*(P[19][3]*SH_TAS[2] - P[19][22]*SH_TAS[2] + P[19][4]*SH_TAS[1] - P[19][23]*SH_TAS[1] + P[19][5]*vd*SH_TAS[0]);
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Kfusion[20] = SK_TAS*(P[20][3]*SH_TAS[2] - P[20][22]*SH_TAS[2] + P[20][4]*SH_TAS[1] - P[20][23]*SH_TAS[1] + P[20][5]*vd*SH_TAS[0]);
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Kfusion[21] = SK_TAS*(P[21][3]*SH_TAS[2] - P[21][22]*SH_TAS[2] + P[21][4]*SH_TAS[1] - P[21][23]*SH_TAS[1] + P[21][5]*vd*SH_TAS[0]);
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} else {
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for (uint8_t i=16; i<=21; i++) {
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Kfusion[i] = 0.0f;
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}
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}
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// calculate measurement innovation variance
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varInnovVtas = 1.0f/SK_TAS;
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// calculate measurement innovation
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innovVtas = VtasPred - tasDataDelayed.tas;
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// calculate the innovation consistency test ratio
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tasTestRatio = sq(innovVtas) / (sq(max(0.01f * (float)frontend->_tasInnovGate, 1.0f)) * varInnovVtas);
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// fail if the ratio is > 1, but don't fail if bad IMU data
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tasHealth = ((tasTestRatio < 1.0f) || badIMUdata);
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tasTimeout = (imuSampleTime_ms - lastTasPassTime_ms) > frontend->tasRetryTime_ms;
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// 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
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if (tasHealth || (tasTimeout && posTimeout)) {
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// restart the counter
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lastTasPassTime_ms = imuSampleTime_ms;
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// zero the attitude error state - by definition it is assumed to be zero before each observaton fusion
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stateStruct.angErr.zero();
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// correct the state vector
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for (uint8_t j= 0; j<=stateIndexLim; j++) {
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statesArray[j] = statesArray[j] - Kfusion[j] * innovVtas;
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}
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// the first 3 states represent the angular misalignment vector. This is
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// is used to correct the estimated quaternion on the current time step
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stateStruct.quat.rotate(stateStruct.angErr);
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// correct the covariance P = (I - K*H)*P
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// take advantage of the empty columns in KH to reduce the
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// number of operations
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for (unsigned i = 0; i<=stateIndexLim; i++) {
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for (unsigned j = 0; j<=2; j++) {
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KH[i][j] = 0.0f;
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}
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for (unsigned j = 3; j<=5; j++) {
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KH[i][j] = Kfusion[i] * H_TAS[j];
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}
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for (unsigned j = 6; j<=21; j++) {
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KH[i][j] = 0.0f;
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}
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for (unsigned j = 22; j<=23; j++) {
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KH[i][j] = Kfusion[i] * H_TAS[j];
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}
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}
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for (unsigned j = 0; j<=stateIndexLim; j++) {
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for (unsigned i = 0; i<=stateIndexLim; i++) {
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ftype res = 0;
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res += KH[i][3] * P[3][j];
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res += KH[i][4] * P[4][j];
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res += KH[i][5] * P[5][j];
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res += KH[i][22] * P[22][j];
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res += KH[i][23] * P[23][j];
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KHP[i][j] = res;
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}
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}
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for (unsigned i = 0; i<=stateIndexLim; i++) {
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for (unsigned j = 0; j<=stateIndexLim; j++) {
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P[i][j] = P[i][j] - KHP[i][j];
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}
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}
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}
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}
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// force the covariance matrix to me symmetrical and limit the variances to prevent ill-condiioning.
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ForceSymmetry();
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ConstrainVariances();
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// stop performance timer
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hal.util->perf_end(_perf_FuseAirspeed);
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}
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// select fusion of true airspeed measurements
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void NavEKF2_core::SelectTasFusion()
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{
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// Check if the magnetometer has been fused on that time step and the filter is running at faster than 200 Hz
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// If so, don't fuse measurements on this time step to reduce frame over-runs
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// Only allow one time slip to prevent high rate magnetometer data locking out fusion of other measurements
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if (magFusePerformed && dtIMUavg < 0.005f && !airSpdFusionDelayed) {
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airSpdFusionDelayed = true;
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return;
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} else {
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airSpdFusionDelayed = false;
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}
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// get true airspeed measurement
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readAirSpdData();
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// If we haven't received airspeed data for a while, then declare the airspeed data as being timed out
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if (imuSampleTime_ms - tasDataNew.time_ms > frontend->tasRetryTime_ms) {
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tasTimeout = true;
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}
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// if the filter is initialised, wind states are not inhibited and we have data to fuse, then perform TAS fusion
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if (tasDataToFuse && statesInitialised && !inhibitWindStates) {
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FuseAirspeed();
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prevTasStep_ms = imuSampleTime_ms;
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}
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}
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// select fusion of synthetic sideslip measurements
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// synthetic sidelip fusion only works for fixed wing aircraft and relies on the average sideslip being close to zero
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// 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)
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void NavEKF2_core::SelectBetaFusion()
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{
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// Check if the magnetometer has been fused on that time step and the filter is running at faster than 200 Hz
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// If so, don't fuse measurements on this time step to reduce frame over-runs
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// Only allow one time slip to prevent high rate magnetometer data preventing fusion of other measurements
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if (magFusePerformed && dtIMUavg < 0.005f && !sideSlipFusionDelayed) {
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sideSlipFusionDelayed = true;
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return;
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} else {
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sideSlipFusionDelayed = false;
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}
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// set true when the fusion time interval has triggered
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bool f_timeTrigger = ((imuSampleTime_ms - prevBetaStep_ms) >= frontend->betaAvg_ms);
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// set true when use of synthetic sideslip fusion is necessary because we have limited sensor data or are dead reckoning position
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bool f_required = !(use_compass() && useAirspeed() && ((imuSampleTime_ms - lastPosPassTime_ms) < frontend->gpsRetryTimeNoTAS_ms));
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// set true when sideslip fusion is feasible (requires zero sideslip assumption to be valid and use of wind states)
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bool f_feasible = (assume_zero_sideslip() && !inhibitWindStates);
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// use synthetic sideslip fusion if feasible, required and enough time has lapsed since the last fusion
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if (f_feasible && f_required && f_timeTrigger) {
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FuseSideslip();
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prevBetaStep_ms = imuSampleTime_ms;
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}
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}
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/*
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* Fuse sythetic sideslip measurement of zero using explicit algebraic equations generated with Matlab symbolic toolbox.
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* The script file used to generate these and other equations in this filter can be found here:
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* https://github.com/priseborough/InertialNav/blob/master/derivations/RotationVectorAttitudeParameterisation/GenerateNavFilterEquations.m
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*/
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void NavEKF2_core::FuseSideslip()
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{
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// start performance timer
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hal.util->perf_begin(_perf_FuseSideslip);
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// declarations
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float q0;
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float q1;
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float q2;
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float q3;
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float vn;
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float ve;
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float vd;
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float vwn;
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float vwe;
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const float R_BETA = 0.03f; // assume a sideslip angle RMS of ~10 deg
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Vector10 SH_BETA;
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Vector5 SK_BETA;
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Vector3f vel_rel_wind;
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Vector24 H_BETA;
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float innovBeta;
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// copy required states to local variable names
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q0 = stateStruct.quat[0];
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q1 = stateStruct.quat[1];
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q2 = stateStruct.quat[2];
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q3 = stateStruct.quat[3];
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vn = stateStruct.velocity.x;
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ve = stateStruct.velocity.y;
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vd = stateStruct.velocity.z;
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vwn = stateStruct.wind_vel.x;
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vwe = stateStruct.wind_vel.y;
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// calculate predicted wind relative velocity in NED
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vel_rel_wind.x = vn - vwn;
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vel_rel_wind.y = ve - vwe;
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vel_rel_wind.z = vd;
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// rotate into body axes
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vel_rel_wind = prevTnb * vel_rel_wind;
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// perform fusion of assumed sideslip = 0
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if (vel_rel_wind.x > 5.0f)
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{
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// Calculate observation jacobians
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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);
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if (fabsf(SH_BETA[0]) <= 1e-9f) {
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faultStatus.bad_sideslip = true;
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return;
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} else {
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faultStatus.bad_sideslip = false;
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}
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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);
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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);
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SH_BETA[2] = vd*(sq(q0) - sq(q1) - sq(q2) + sq(q3)) - (ve - vwe)*(2*q0*q1 - 2*q2*q3) + (vn - vwn)*(2*q0*q2 + 2*q1*q3);
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SH_BETA[3] = 1/sq(SH_BETA[0]);
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SH_BETA[4] = (sq(q0) - sq(q1) + sq(q2) - sq(q3))/SH_BETA[0];
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SH_BETA[5] = sq(q0) + sq(q1) - sq(q2) - sq(q3);
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SH_BETA[6] = 1/SH_BETA[0];
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SH_BETA[7] = 2*q0*q3;
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SH_BETA[8] = SH_BETA[7] + 2*q1*q2;
|
|
SH_BETA[9] = SH_BETA[7] - 2*q1*q2;
|
|
H_BETA[0] = SH_BETA[2]*SH_BETA[6];
|
|
H_BETA[1] = SH_BETA[1]*SH_BETA[2]*SH_BETA[3];
|
|
H_BETA[2] = - sq(SH_BETA[1])*SH_BETA[3] - 1;
|
|
H_BETA[3] = - SH_BETA[6]*SH_BETA[9] - SH_BETA[1]*SH_BETA[3]*SH_BETA[5];
|
|
H_BETA[4] = SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8];
|
|
H_BETA[5] = SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3);
|
|
for (uint8_t i=6; i<=21; i++) {
|
|
H_BETA[i] = 0.0f;
|
|
}
|
|
H_BETA[22] = SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5];
|
|
H_BETA[23] = SH_BETA[1]*SH_BETA[3]*SH_BETA[8] - SH_BETA[4];
|
|
|
|
// Calculate Kalman gains
|
|
float temp = (R_BETA + (SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8])*(P[22][4]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[3][4]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[2][4]*(sq(SH_BETA[1])*SH_BETA[3] + 1) + P[5][4]*(SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3)) + P[4][4]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) - P[23][4]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) + P[0][4]*SH_BETA[2]*SH_BETA[6] + P[1][4]*SH_BETA[1]*SH_BETA[2]*SH_BETA[3]) - (SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8])*(P[22][23]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[3][23]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[2][23]*(sq(SH_BETA[1])*SH_BETA[3] + 1) + P[5][23]*(SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3)) + P[4][23]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) - P[23][23]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) + P[0][23]*SH_BETA[2]*SH_BETA[6] + P[1][23]*SH_BETA[1]*SH_BETA[2]*SH_BETA[3]) - (SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5])*(P[22][3]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[3][3]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[2][3]*(sq(SH_BETA[1])*SH_BETA[3] + 1) + P[5][3]*(SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3)) + P[4][3]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) - P[23][3]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) + P[0][3]*SH_BETA[2]*SH_BETA[6] + P[1][3]*SH_BETA[1]*SH_BETA[2]*SH_BETA[3]) + (SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5])*(P[22][22]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[3][22]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[2][22]*(sq(SH_BETA[1])*SH_BETA[3] + 1) + P[5][22]*(SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3)) + P[4][22]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) - P[23][22]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) + P[0][22]*SH_BETA[2]*SH_BETA[6] + P[1][22]*SH_BETA[1]*SH_BETA[2]*SH_BETA[3]) - (sq(SH_BETA[1])*SH_BETA[3] + 1)*(P[22][2]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[3][2]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[2][2]*(sq(SH_BETA[1])*SH_BETA[3] + 1) + P[5][2]*(SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3)) + P[4][2]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) - P[23][2]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) + P[0][2]*SH_BETA[2]*SH_BETA[6] + P[1][2]*SH_BETA[1]*SH_BETA[2]*SH_BETA[3]) + (SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3))*(P[22][5]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[3][5]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[2][5]*(sq(SH_BETA[1])*SH_BETA[3] + 1) + P[5][5]*(SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3)) + P[4][5]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) - P[23][5]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) + P[0][5]*SH_BETA[2]*SH_BETA[6] + P[1][5]*SH_BETA[1]*SH_BETA[2]*SH_BETA[3]) + SH_BETA[2]*SH_BETA[6]*(P[22][0]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[3][0]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[2][0]*(sq(SH_BETA[1])*SH_BETA[3] + 1) + P[5][0]*(SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3)) + P[4][0]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) - P[23][0]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) + P[0][0]*SH_BETA[2]*SH_BETA[6] + P[1][0]*SH_BETA[1]*SH_BETA[2]*SH_BETA[3]) + SH_BETA[1]*SH_BETA[2]*SH_BETA[3]*(P[22][1]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[3][1]*(SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5]) - P[2][1]*(sq(SH_BETA[1])*SH_BETA[3] + 1) + P[5][1]*(SH_BETA[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3)) + P[4][1]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) - P[23][1]*(SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8]) + P[0][1]*SH_BETA[2]*SH_BETA[6] + P[1][1]*SH_BETA[1]*SH_BETA[2]*SH_BETA[3]));
|
|
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[6]*(2*q0*q1 + 2*q2*q3) + SH_BETA[1]*SH_BETA[3]*(2*q0*q2 - 2*q1*q3);
|
|
SK_BETA[2] = SH_BETA[6]*SH_BETA[9] + SH_BETA[1]*SH_BETA[3]*SH_BETA[5];
|
|
SK_BETA[3] = SH_BETA[4] - SH_BETA[1]*SH_BETA[3]*SH_BETA[8];
|
|
SK_BETA[4] = sq(SH_BETA[1])*SH_BETA[3] + 1;
|
|
Kfusion[0] = SK_BETA[0]*(P[0][5]*SK_BETA[1] - P[0][2]*SK_BETA[4] - P[0][3]*SK_BETA[2] + P[0][4]*SK_BETA[3] + P[0][22]*SK_BETA[2] - P[0][23]*SK_BETA[3] + P[0][0]*SH_BETA[6]*SH_BETA[2] + P[0][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[1] = SK_BETA[0]*(P[1][5]*SK_BETA[1] - P[1][2]*SK_BETA[4] - P[1][3]*SK_BETA[2] + P[1][4]*SK_BETA[3] + P[1][22]*SK_BETA[2] - P[1][23]*SK_BETA[3] + P[1][0]*SH_BETA[6]*SH_BETA[2] + P[1][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[2] = SK_BETA[0]*(P[2][5]*SK_BETA[1] - P[2][2]*SK_BETA[4] - P[2][3]*SK_BETA[2] + P[2][4]*SK_BETA[3] + P[2][22]*SK_BETA[2] - P[2][23]*SK_BETA[3] + P[2][0]*SH_BETA[6]*SH_BETA[2] + P[2][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[3] = SK_BETA[0]*(P[3][5]*SK_BETA[1] - P[3][2]*SK_BETA[4] - P[3][3]*SK_BETA[2] + P[3][4]*SK_BETA[3] + P[3][22]*SK_BETA[2] - P[3][23]*SK_BETA[3] + P[3][0]*SH_BETA[6]*SH_BETA[2] + P[3][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[4] = SK_BETA[0]*(P[4][5]*SK_BETA[1] - P[4][2]*SK_BETA[4] - P[4][3]*SK_BETA[2] + P[4][4]*SK_BETA[3] + P[4][22]*SK_BETA[2] - P[4][23]*SK_BETA[3] + P[4][0]*SH_BETA[6]*SH_BETA[2] + P[4][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[5] = SK_BETA[0]*(P[5][5]*SK_BETA[1] - P[5][2]*SK_BETA[4] - P[5][3]*SK_BETA[2] + P[5][4]*SK_BETA[3] + P[5][22]*SK_BETA[2] - P[5][23]*SK_BETA[3] + P[5][0]*SH_BETA[6]*SH_BETA[2] + P[5][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[6] = SK_BETA[0]*(P[6][5]*SK_BETA[1] - P[6][2]*SK_BETA[4] - P[6][3]*SK_BETA[2] + P[6][4]*SK_BETA[3] + P[6][22]*SK_BETA[2] - P[6][23]*SK_BETA[3] + P[6][0]*SH_BETA[6]*SH_BETA[2] + P[6][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[7] = SK_BETA[0]*(P[7][5]*SK_BETA[1] - P[7][2]*SK_BETA[4] - P[7][3]*SK_BETA[2] + P[7][4]*SK_BETA[3] + P[7][22]*SK_BETA[2] - P[7][23]*SK_BETA[3] + P[7][0]*SH_BETA[6]*SH_BETA[2] + P[7][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[8] = SK_BETA[0]*(P[8][5]*SK_BETA[1] - P[8][2]*SK_BETA[4] - P[8][3]*SK_BETA[2] + P[8][4]*SK_BETA[3] + P[8][22]*SK_BETA[2] - P[8][23]*SK_BETA[3] + P[8][0]*SH_BETA[6]*SH_BETA[2] + P[8][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[9] = SK_BETA[0]*(P[9][5]*SK_BETA[1] - P[9][2]*SK_BETA[4] - P[9][3]*SK_BETA[2] + P[9][4]*SK_BETA[3] + P[9][22]*SK_BETA[2] - P[9][23]*SK_BETA[3] + P[9][0]*SH_BETA[6]*SH_BETA[2] + P[9][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[10] = SK_BETA[0]*(P[10][5]*SK_BETA[1] - P[10][2]*SK_BETA[4] - P[10][3]*SK_BETA[2] + P[10][4]*SK_BETA[3] + P[10][22]*SK_BETA[2] - P[10][23]*SK_BETA[3] + P[10][0]*SH_BETA[6]*SH_BETA[2] + P[10][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[11] = SK_BETA[0]*(P[11][5]*SK_BETA[1] - P[11][2]*SK_BETA[4] - P[11][3]*SK_BETA[2] + P[11][4]*SK_BETA[3] + P[11][22]*SK_BETA[2] - P[11][23]*SK_BETA[3] + P[11][0]*SH_BETA[6]*SH_BETA[2] + P[11][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[12] = SK_BETA[0]*(P[12][5]*SK_BETA[1] - P[12][2]*SK_BETA[4] - P[12][3]*SK_BETA[2] + P[12][4]*SK_BETA[3] + P[12][22]*SK_BETA[2] - P[12][23]*SK_BETA[3] + P[12][0]*SH_BETA[6]*SH_BETA[2] + P[12][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[13] = SK_BETA[0]*(P[13][5]*SK_BETA[1] - P[13][2]*SK_BETA[4] - P[13][3]*SK_BETA[2] + P[13][4]*SK_BETA[3] + P[13][22]*SK_BETA[2] - P[13][23]*SK_BETA[3] + P[13][0]*SH_BETA[6]*SH_BETA[2] + P[13][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[14] = SK_BETA[0]*(P[14][5]*SK_BETA[1] - P[14][2]*SK_BETA[4] - P[14][3]*SK_BETA[2] + P[14][4]*SK_BETA[3] + P[14][22]*SK_BETA[2] - P[14][23]*SK_BETA[3] + P[14][0]*SH_BETA[6]*SH_BETA[2] + P[14][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[15] = SK_BETA[0]*(P[15][5]*SK_BETA[1] - P[15][2]*SK_BETA[4] - P[15][3]*SK_BETA[2] + P[15][4]*SK_BETA[3] + P[15][22]*SK_BETA[2] - P[15][23]*SK_BETA[3] + P[15][0]*SH_BETA[6]*SH_BETA[2] + P[15][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[22] = SK_BETA[0]*(P[22][5]*SK_BETA[1] - P[22][2]*SK_BETA[4] - P[22][3]*SK_BETA[2] + P[22][4]*SK_BETA[3] + P[22][22]*SK_BETA[2] - P[22][23]*SK_BETA[3] + P[22][0]*SH_BETA[6]*SH_BETA[2] + P[22][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[23] = SK_BETA[0]*(P[23][5]*SK_BETA[1] - P[23][2]*SK_BETA[4] - P[23][3]*SK_BETA[2] + P[23][4]*SK_BETA[3] + P[23][22]*SK_BETA[2] - P[23][23]*SK_BETA[3] + P[23][0]*SH_BETA[6]*SH_BETA[2] + P[23][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
// zero Kalman gains to inhibit magnetic field state estimation
|
|
if (!inhibitMagStates) {
|
|
Kfusion[16] = SK_BETA[0]*(P[16][5]*SK_BETA[1] - P[16][2]*SK_BETA[4] - P[16][3]*SK_BETA[2] + P[16][4]*SK_BETA[3] + P[16][22]*SK_BETA[2] - P[16][23]*SK_BETA[3] + P[16][0]*SH_BETA[6]*SH_BETA[2] + P[16][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[17] = SK_BETA[0]*(P[17][5]*SK_BETA[1] - P[17][2]*SK_BETA[4] - P[17][3]*SK_BETA[2] + P[17][4]*SK_BETA[3] + P[17][22]*SK_BETA[2] - P[17][23]*SK_BETA[3] + P[17][0]*SH_BETA[6]*SH_BETA[2] + P[17][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[18] = SK_BETA[0]*(P[18][5]*SK_BETA[1] - P[18][2]*SK_BETA[4] - P[18][3]*SK_BETA[2] + P[18][4]*SK_BETA[3] + P[18][22]*SK_BETA[2] - P[18][23]*SK_BETA[3] + P[18][0]*SH_BETA[6]*SH_BETA[2] + P[18][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[19] = SK_BETA[0]*(P[19][5]*SK_BETA[1] - P[19][2]*SK_BETA[4] - P[19][3]*SK_BETA[2] + P[19][4]*SK_BETA[3] + P[19][22]*SK_BETA[2] - P[19][23]*SK_BETA[3] + P[19][0]*SH_BETA[6]*SH_BETA[2] + P[19][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[20] = SK_BETA[0]*(P[20][5]*SK_BETA[1] - P[20][2]*SK_BETA[4] - P[20][3]*SK_BETA[2] + P[20][4]*SK_BETA[3] + P[20][22]*SK_BETA[2] - P[20][23]*SK_BETA[3] + P[20][0]*SH_BETA[6]*SH_BETA[2] + P[20][1]*SH_BETA[1]*SH_BETA[3]*SH_BETA[2]);
|
|
Kfusion[21] = SK_BETA[0]*(P[21][5]*SK_BETA[1] - P[21][2]*SK_BETA[4] - P[21][3]*SK_BETA[2] + P[21][4]*SK_BETA[3] + P[21][22]*SK_BETA[2] - P[21][23]*SK_BETA[3] + P[21][0]*SH_BETA[6]*SH_BETA[2] + P[21][1]*SH_BETA[1]*SH_BETA[3]*SH_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;
|
|
}
|
|
|
|
// zero the attitude error state - by definition it is assumed to be zero before each observaton fusion
|
|
stateStruct.angErr.zero();
|
|
|
|
// correct the state vector
|
|
for (uint8_t j= 0; j<=stateIndexLim; j++) {
|
|
statesArray[j] = statesArray[j] - Kfusion[j] * innovBeta;
|
|
}
|
|
|
|
// the first 3 states represent the angular misalignment vector. This is
|
|
// is used to correct the estimated quaternion on the current time step
|
|
stateStruct.quat.rotate(stateStruct.angErr);
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|
|
|
// 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<=5; j++) {
|
|
KH[i][j] = Kfusion[i] * H_BETA[j];
|
|
}
|
|
for (unsigned j = 6; 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][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 the performance timer
|
|
hal.util->perf_end(_perf_FuseSideslip);
|
|
}
|
|
|
|
/********************************************************
|
|
* MISC FUNCTIONS *
|
|
********************************************************/
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|
|
|
|
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#endif // HAL_CPU_CLASS
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