forked from Archive/PX4-Autopilot
872 lines
45 KiB
C++
872 lines
45 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2015 Estimation and Control Library (ECL). All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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* 3. Neither the name ECL nor the names of its contributors may be
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* used to endorse or promote products derived from this software
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* without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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* OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
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* AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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****************************************************************************/
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/**
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* @file heading_fusion.cpp
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* Magnetometer fusion methods.
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*
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* @author Roman Bast <bapstroman@gmail.com>
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* @author Paul Riseborough <p_riseborough@live.com.au>
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*
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*/
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#include "../ecl.h"
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#include "ekf.h"
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#include "mathlib.h"
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void Ekf::fuseMag()
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{
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// assign intermediate variables
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float q0 = _state.quat_nominal(0);
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float q1 = _state.quat_nominal(1);
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float q2 = _state.quat_nominal(2);
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float q3 = _state.quat_nominal(3);
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float magN = _state.mag_I(0);
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float magE = _state.mag_I(1);
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float magD = _state.mag_I(2);
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// XYZ Measurement uncertainty. Need to consider timing errors for fast rotations
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float R_MAG = fmaxf(_params.mag_noise, 0.0f);
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R_MAG = R_MAG * R_MAG;
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// intermediate variables from algebraic optimisation
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float SH_MAG[9];
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SH_MAG[0] = 2.0f*magD*q3 + 2.0f*magE*q2 + 2.0f*magN*q1;
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SH_MAG[1] = 2.0f*magD*q0 - 2.0f*magE*q1 + 2.0f*magN*q2;
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SH_MAG[2] = 2.0f*magD*q1 + 2.0f*magE*q0 - 2.0f*magN*q3;
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SH_MAG[3] = sq(q3);
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SH_MAG[4] = sq(q2);
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SH_MAG[5] = sq(q1);
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SH_MAG[6] = sq(q0);
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SH_MAG[7] = 2.0f*magN*q0;
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SH_MAG[8] = 2.0f*magE*q3;
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// rotate magnetometer earth field state into body frame
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Dcmf R_to_body(_state.quat_nominal);
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R_to_body = R_to_body.transpose();
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Vector3f mag_I_rot = R_to_body * _state.mag_I;
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// compute magnetometer innovations
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_mag_innov[0] = (mag_I_rot(0) + _state.mag_B(0)) - _mag_sample_delayed.mag(0);
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_mag_innov[1] = (mag_I_rot(1) + _state.mag_B(1)) - _mag_sample_delayed.mag(1);
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_mag_innov[2] = (mag_I_rot(2) + _state.mag_B(2)) - _mag_sample_delayed.mag(2);
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// Observation jacobian and Kalman gain vectors
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float H_MAG[24];
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float Kfusion[24];
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// X axis innovation variance
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_mag_innov_var[0] = (P[19][19] + R_MAG + P[1][19]*SH_MAG[0] - P[2][19]*SH_MAG[1] + P[3][19]*SH_MAG[2] - P[16][19]*(SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6]) + (2.0f*q0*q3 + 2.0f*q1*q2)*(P[19][17] + P[1][17]*SH_MAG[0] - P[2][17]*SH_MAG[1] + P[3][17]*SH_MAG[2] - P[16][17]*(SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6]) + P[17][17]*(2.0f*q0*q3 + 2.0f*q1*q2) - P[18][17]*(2.0f*q0*q2 - 2.0f*q1*q3) + P[0][17]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) - (2.0f*q0*q2 - 2.0f*q1*q3)*(P[19][18] + P[1][18]*SH_MAG[0] - P[2][18]*SH_MAG[1] + P[3][18]*SH_MAG[2] - P[16][18]*(SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6]) + P[17][18]*(2.0f*q0*q3 + 2.0f*q1*q2) - P[18][18]*(2.0f*q0*q2 - 2.0f*q1*q3) + P[0][18]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + (SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)*(P[19][0] + P[1][0]*SH_MAG[0] - P[2][0]*SH_MAG[1] + P[3][0]*SH_MAG[2] - P[16][0]*(SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6]) + P[17][0]*(2.0f*q0*q3 + 2.0f*q1*q2) - P[18][0]*(2.0f*q0*q2 - 2.0f*q1*q3) + P[0][0]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + P[17][19]*(2.0f*q0*q3 + 2.0f*q1*q2) - P[18][19]*(2.0f*q0*q2 - 2.0f*q1*q3) + SH_MAG[0]*(P[19][1] + P[1][1]*SH_MAG[0] - P[2][1]*SH_MAG[1] + P[3][1]*SH_MAG[2] - P[16][1]*(SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6]) + P[17][1]*(2.0f*q0*q3 + 2.0f*q1*q2) - P[18][1]*(2.0f*q0*q2 - 2.0f*q1*q3) + P[0][1]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) - SH_MAG[1]*(P[19][2] + P[1][2]*SH_MAG[0] - P[2][2]*SH_MAG[1] + P[3][2]*SH_MAG[2] - P[16][2]*(SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6]) + P[17][2]*(2.0f*q0*q3 + 2.0f*q1*q2) - P[18][2]*(2.0f*q0*q2 - 2.0f*q1*q3) + P[0][2]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + SH_MAG[2]*(P[19][3] + P[1][3]*SH_MAG[0] - P[2][3]*SH_MAG[1] + P[3][3]*SH_MAG[2] - P[16][3]*(SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6]) + P[17][3]*(2.0f*q0*q3 + 2.0f*q1*q2) - P[18][3]*(2.0f*q0*q2 - 2.0f*q1*q3) + P[0][3]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) - (SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6])*(P[19][16] + P[1][16]*SH_MAG[0] - P[2][16]*SH_MAG[1] + P[3][16]*SH_MAG[2] - P[16][16]*(SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6]) + P[17][16]*(2.0f*q0*q3 + 2.0f*q1*q2) - P[18][16]*(2.0f*q0*q2 - 2.0f*q1*q3) + P[0][16]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + P[0][19]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2));
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// check for a badly conditioned covariance matrix
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if (_mag_innov_var[0] >= R_MAG) {
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// the innovation variance contribution from the state covariances is non-negative - no fault
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_fault_status.flags.bad_mag_x = false;
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} else {
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// the innovation variance contribution from the state covariances is negative which means the covariance matrix is badly conditioned
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_fault_status.flags.bad_mag_x = true;
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// we need to re-initialise covariances and abort this fusion step
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resetMagCovariance();
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ECL_ERR("EKF magX fusion numerical error - covariance reset");
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return;
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}
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// Y axis innovation variance
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_mag_innov_var[1] = (P[20][20] + R_MAG + P[0][20]*SH_MAG[2] + P[1][20]*SH_MAG[1] + P[2][20]*SH_MAG[0] - P[17][20]*(SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6]) - (2.0f*q0*q3 - 2.0f*q1*q2)*(P[20][16] + P[0][16]*SH_MAG[2] + P[1][16]*SH_MAG[1] + P[2][16]*SH_MAG[0] - P[17][16]*(SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6]) - P[16][16]*(2.0f*q0*q3 - 2.0f*q1*q2) + P[18][16]*(2.0f*q0*q1 + 2.0f*q2*q3) - P[3][16]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + (2.0f*q0*q1 + 2.0f*q2*q3)*(P[20][18] + P[0][18]*SH_MAG[2] + P[1][18]*SH_MAG[1] + P[2][18]*SH_MAG[0] - P[17][18]*(SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6]) - P[16][18]*(2.0f*q0*q3 - 2.0f*q1*q2) + P[18][18]*(2.0f*q0*q1 + 2.0f*q2*q3) - P[3][18]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) - (SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)*(P[20][3] + P[0][3]*SH_MAG[2] + P[1][3]*SH_MAG[1] + P[2][3]*SH_MAG[0] - P[17][3]*(SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6]) - P[16][3]*(2.0f*q0*q3 - 2.0f*q1*q2) + P[18][3]*(2.0f*q0*q1 + 2.0f*q2*q3) - P[3][3]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) - P[16][20]*(2.0f*q0*q3 - 2.0f*q1*q2) + P[18][20]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_MAG[2]*(P[20][0] + P[0][0]*SH_MAG[2] + P[1][0]*SH_MAG[1] + P[2][0]*SH_MAG[0] - P[17][0]*(SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6]) - P[16][0]*(2.0f*q0*q3 - 2.0f*q1*q2) + P[18][0]*(2.0f*q0*q1 + 2.0f*q2*q3) - P[3][0]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + SH_MAG[1]*(P[20][1] + P[0][1]*SH_MAG[2] + P[1][1]*SH_MAG[1] + P[2][1]*SH_MAG[0] - P[17][1]*(SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6]) - P[16][1]*(2.0f*q0*q3 - 2.0f*q1*q2) + P[18][1]*(2.0f*q0*q1 + 2.0f*q2*q3) - P[3][1]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + SH_MAG[0]*(P[20][2] + P[0][2]*SH_MAG[2] + P[1][2]*SH_MAG[1] + P[2][2]*SH_MAG[0] - P[17][2]*(SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6]) - P[16][2]*(2.0f*q0*q3 - 2.0f*q1*q2) + P[18][2]*(2.0f*q0*q1 + 2.0f*q2*q3) - P[3][2]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) - (SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6])*(P[20][17] + P[0][17]*SH_MAG[2] + P[1][17]*SH_MAG[1] + P[2][17]*SH_MAG[0] - P[17][17]*(SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6]) - P[16][17]*(2.0f*q0*q3 - 2.0f*q1*q2) + P[18][17]*(2.0f*q0*q1 + 2.0f*q2*q3) - P[3][17]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) - P[3][20]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2));
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// check for a badly conditioned covariance matrix
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if (_mag_innov_var[1] >= R_MAG) {
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// the innovation variance contribution from the state covariances is non-negative - no fault
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_fault_status.flags.bad_mag_y = false;
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} else {
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// the innovation variance contribution from the state covariances is negtive which means the covariance matrix is badly conditioned
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_fault_status.flags.bad_mag_y = true;
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// we need to re-initialise covariances and abort this fusion step
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resetMagCovariance();
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ECL_ERR("EKF magY fusion numerical error - covariance reset");
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return;
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}
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// Z axis innovation variance
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_mag_innov_var[2] = (P[21][21] + R_MAG + P[0][21]*SH_MAG[1] - P[1][21]*SH_MAG[2] + P[3][21]*SH_MAG[0] + P[18][21]*(SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6]) + (2.0f*q0*q2 + 2.0f*q1*q3)*(P[21][16] + P[0][16]*SH_MAG[1] - P[1][16]*SH_MAG[2] + P[3][16]*SH_MAG[0] + P[18][16]*(SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6]) + P[16][16]*(2.0f*q0*q2 + 2.0f*q1*q3) - P[17][16]*(2.0f*q0*q1 - 2.0f*q2*q3) + P[2][16]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) - (2.0f*q0*q1 - 2.0f*q2*q3)*(P[21][17] + P[0][17]*SH_MAG[1] - P[1][17]*SH_MAG[2] + P[3][17]*SH_MAG[0] + P[18][17]*(SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6]) + P[16][17]*(2.0f*q0*q2 + 2.0f*q1*q3) - P[17][17]*(2.0f*q0*q1 - 2.0f*q2*q3) + P[2][17]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + (SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)*(P[21][2] + P[0][2]*SH_MAG[1] - P[1][2]*SH_MAG[2] + P[3][2]*SH_MAG[0] + P[18][2]*(SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6]) + P[16][2]*(2.0f*q0*q2 + 2.0f*q1*q3) - P[17][2]*(2.0f*q0*q1 - 2.0f*q2*q3) + P[2][2]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + P[16][21]*(2.0f*q0*q2 + 2.0f*q1*q3) - P[17][21]*(2.0f*q0*q1 - 2.0f*q2*q3) + SH_MAG[1]*(P[21][0] + P[0][0]*SH_MAG[1] - P[1][0]*SH_MAG[2] + P[3][0]*SH_MAG[0] + P[18][0]*(SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6]) + P[16][0]*(2.0f*q0*q2 + 2.0f*q1*q3) - P[17][0]*(2.0f*q0*q1 - 2.0f*q2*q3) + P[2][0]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) - SH_MAG[2]*(P[21][1] + P[0][1]*SH_MAG[1] - P[1][1]*SH_MAG[2] + P[3][1]*SH_MAG[0] + P[18][1]*(SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6]) + P[16][1]*(2.0f*q0*q2 + 2.0f*q1*q3) - P[17][1]*(2.0f*q0*q1 - 2.0f*q2*q3) + P[2][1]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + SH_MAG[0]*(P[21][3] + P[0][3]*SH_MAG[1] - P[1][3]*SH_MAG[2] + P[3][3]*SH_MAG[0] + P[18][3]*(SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6]) + P[16][3]*(2.0f*q0*q2 + 2.0f*q1*q3) - P[17][3]*(2.0f*q0*q1 - 2.0f*q2*q3) + P[2][3]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + (SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6])*(P[21][18] + P[0][18]*SH_MAG[1] - P[1][18]*SH_MAG[2] + P[3][18]*SH_MAG[0] + P[18][18]*(SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6]) + P[16][18]*(2.0f*q0*q2 + 2.0f*q1*q3) - P[17][18]*(2.0f*q0*q1 - 2.0f*q2*q3) + P[2][18]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2)) + P[2][21]*(SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2));
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// check for a badly conditioned covariance matrix
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if (_mag_innov_var[2] >= R_MAG) {
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// the innovation variance contribution from the state covariances is non-negative - no fault
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_fault_status.flags.bad_mag_z = false;
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} else if (_mag_innov_var[2] > 0.0f) {
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// the innovation variance contribution from the state covariances is negative which means the covariance matrix is badly conditioned
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_fault_status.flags.bad_mag_z = true;
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// we need to re-initialise covariances and abort this fusion step
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resetMagCovariance();
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ECL_ERR("EKF magZ fusion numerical error - covariance reset");
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return;
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}
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// Perform an innovation consistency check and report the result
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bool healthy = true;
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for (uint8_t index = 0; index <= 2; index++) {
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_mag_test_ratio[index] = sq(_mag_innov[index]) / (sq(math::max(_params.mag_innov_gate, 1.0f)) * _mag_innov_var[index]);
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if (_mag_test_ratio[index] > 1.0f) {
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healthy = false;
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_innov_check_fail_status.value |= (1 << (index + 3));
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} else {
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_innov_check_fail_status.value &= ~(1 << (index + 3));
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}
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}
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// we are no longer using heading fusion so set the reported test level to zero
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_yaw_test_ratio = 0.0f;
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// if any axis fails, abort the mag fusion
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if (!healthy) {
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return;
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}
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// update the states and covariance using sequential fusion of the magnetometer components
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for (uint8_t index = 0; index <= 2; index++) {
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// Calculate Kalman gains and observation jacobians
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if (index == 0) {
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// Calculate X axis observation jacobians
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memset(H_MAG, 0, sizeof(H_MAG));
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H_MAG[0] = SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2;
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H_MAG[1] = SH_MAG[0];
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H_MAG[2] = -SH_MAG[1];
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H_MAG[3] = SH_MAG[2];
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H_MAG[16] = SH_MAG[5] - SH_MAG[4] - SH_MAG[3] + SH_MAG[6];
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H_MAG[17] = 2.0f*q0*q3 + 2.0f*q1*q2;
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H_MAG[18] = 2.0f*q1*q3 - 2.0f*q0*q2;
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H_MAG[19] = 1.0f;
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// Calculate X axis Kalman gains
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float SK_MX[5];
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SK_MX[0] = 1.0f / _mag_innov_var[0];
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SK_MX[1] = SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6];
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SK_MX[2] = SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2;
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SK_MX[3] = 2.0f*q0*q2 - 2.0f*q1*q3;
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SK_MX[4] = 2.0f*q0*q3 + 2.0f*q1*q2;
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if (!_control_status.flags.update_mag_states_only) {
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Kfusion[0] = SK_MX[0]*(P[0][19] + P[0][1]*SH_MAG[0] - P[0][2]*SH_MAG[1] + P[0][3]*SH_MAG[2] + P[0][0]*SK_MX[2] - P[0][16]*SK_MX[1] + P[0][17]*SK_MX[4] - P[0][18]*SK_MX[3]);
|
|
Kfusion[1] = SK_MX[0]*(P[1][19] + P[1][1]*SH_MAG[0] - P[1][2]*SH_MAG[1] + P[1][3]*SH_MAG[2] + P[1][0]*SK_MX[2] - P[1][16]*SK_MX[1] + P[1][17]*SK_MX[4] - P[1][18]*SK_MX[3]);
|
|
Kfusion[2] = SK_MX[0]*(P[2][19] + P[2][1]*SH_MAG[0] - P[2][2]*SH_MAG[1] + P[2][3]*SH_MAG[2] + P[2][0]*SK_MX[2] - P[2][16]*SK_MX[1] + P[2][17]*SK_MX[4] - P[2][18]*SK_MX[3]);
|
|
Kfusion[3] = SK_MX[0]*(P[3][19] + P[3][1]*SH_MAG[0] - P[3][2]*SH_MAG[1] + P[3][3]*SH_MAG[2] + P[3][0]*SK_MX[2] - P[3][16]*SK_MX[1] + P[3][17]*SK_MX[4] - P[3][18]*SK_MX[3]);
|
|
Kfusion[4] = SK_MX[0]*(P[4][19] + P[4][1]*SH_MAG[0] - P[4][2]*SH_MAG[1] + P[4][3]*SH_MAG[2] + P[4][0]*SK_MX[2] - P[4][16]*SK_MX[1] + P[4][17]*SK_MX[4] - P[4][18]*SK_MX[3]);
|
|
Kfusion[5] = SK_MX[0]*(P[5][19] + P[5][1]*SH_MAG[0] - P[5][2]*SH_MAG[1] + P[5][3]*SH_MAG[2] + P[5][0]*SK_MX[2] - P[5][16]*SK_MX[1] + P[5][17]*SK_MX[4] - P[5][18]*SK_MX[3]);
|
|
Kfusion[6] = SK_MX[0]*(P[6][19] + P[6][1]*SH_MAG[0] - P[6][2]*SH_MAG[1] + P[6][3]*SH_MAG[2] + P[6][0]*SK_MX[2] - P[6][16]*SK_MX[1] + P[6][17]*SK_MX[4] - P[6][18]*SK_MX[3]);
|
|
Kfusion[7] = SK_MX[0]*(P[7][19] + P[7][1]*SH_MAG[0] - P[7][2]*SH_MAG[1] + P[7][3]*SH_MAG[2] + P[7][0]*SK_MX[2] - P[7][16]*SK_MX[1] + P[7][17]*SK_MX[4] - P[7][18]*SK_MX[3]);
|
|
Kfusion[8] = SK_MX[0]*(P[8][19] + P[8][1]*SH_MAG[0] - P[8][2]*SH_MAG[1] + P[8][3]*SH_MAG[2] + P[8][0]*SK_MX[2] - P[8][16]*SK_MX[1] + P[8][17]*SK_MX[4] - P[8][18]*SK_MX[3]);
|
|
Kfusion[9] = SK_MX[0]*(P[9][19] + P[9][1]*SH_MAG[0] - P[9][2]*SH_MAG[1] + P[9][3]*SH_MAG[2] + P[9][0]*SK_MX[2] - P[9][16]*SK_MX[1] + P[9][17]*SK_MX[4] - P[9][18]*SK_MX[3]);
|
|
Kfusion[10] = SK_MX[0]*(P[10][19] + P[10][1]*SH_MAG[0] - P[10][2]*SH_MAG[1] + P[10][3]*SH_MAG[2] + P[10][0]*SK_MX[2] - P[10][16]*SK_MX[1] + P[10][17]*SK_MX[4] - P[10][18]*SK_MX[3]);
|
|
Kfusion[11] = SK_MX[0]*(P[11][19] + P[11][1]*SH_MAG[0] - P[11][2]*SH_MAG[1] + P[11][3]*SH_MAG[2] + P[11][0]*SK_MX[2] - P[11][16]*SK_MX[1] + P[11][17]*SK_MX[4] - P[11][18]*SK_MX[3]);
|
|
Kfusion[12] = SK_MX[0]*(P[12][19] + P[12][1]*SH_MAG[0] - P[12][2]*SH_MAG[1] + P[12][3]*SH_MAG[2] + P[12][0]*SK_MX[2] - P[12][16]*SK_MX[1] + P[12][17]*SK_MX[4] - P[12][18]*SK_MX[3]);
|
|
Kfusion[13] = SK_MX[0]*(P[13][19] + P[13][1]*SH_MAG[0] - P[13][2]*SH_MAG[1] + P[13][3]*SH_MAG[2] + P[13][0]*SK_MX[2] - P[13][16]*SK_MX[1] + P[13][17]*SK_MX[4] - P[13][18]*SK_MX[3]);
|
|
Kfusion[14] = SK_MX[0]*(P[14][19] + P[14][1]*SH_MAG[0] - P[14][2]*SH_MAG[1] + P[14][3]*SH_MAG[2] + P[14][0]*SK_MX[2] - P[14][16]*SK_MX[1] + P[14][17]*SK_MX[4] - P[14][18]*SK_MX[3]);
|
|
Kfusion[15] = SK_MX[0]*(P[15][19] + P[15][1]*SH_MAG[0] - P[15][2]*SH_MAG[1] + P[15][3]*SH_MAG[2] + P[15][0]*SK_MX[2] - P[15][16]*SK_MX[1] + P[15][17]*SK_MX[4] - P[15][18]*SK_MX[3]);
|
|
Kfusion[22] = SK_MX[0]*(P[22][19] + P[22][1]*SH_MAG[0] - P[22][2]*SH_MAG[1] + P[22][3]*SH_MAG[2] + P[22][0]*SK_MX[2] - P[22][16]*SK_MX[1] + P[22][17]*SK_MX[4] - P[22][18]*SK_MX[3]);
|
|
Kfusion[23] = SK_MX[0]*(P[23][19] + P[23][1]*SH_MAG[0] - P[23][2]*SH_MAG[1] + P[23][3]*SH_MAG[2] + P[23][0]*SK_MX[2] - P[23][16]*SK_MX[1] + P[23][17]*SK_MX[4] - P[23][18]*SK_MX[3]);
|
|
} else {
|
|
for (uint8_t i = 0; i < 16; i++) {
|
|
Kfusion[i] = 0.0f;
|
|
}
|
|
Kfusion[22] = 0.0f;
|
|
Kfusion[23] = 0.0f;
|
|
}
|
|
|
|
Kfusion[16] = SK_MX[0]*(P[16][19] + P[16][1]*SH_MAG[0] - P[16][2]*SH_MAG[1] + P[16][3]*SH_MAG[2] + P[16][0]*SK_MX[2] - P[16][16]*SK_MX[1] + P[16][17]*SK_MX[4] - P[16][18]*SK_MX[3]);
|
|
Kfusion[17] = SK_MX[0]*(P[17][19] + P[17][1]*SH_MAG[0] - P[17][2]*SH_MAG[1] + P[17][3]*SH_MAG[2] + P[17][0]*SK_MX[2] - P[17][16]*SK_MX[1] + P[17][17]*SK_MX[4] - P[17][18]*SK_MX[3]);
|
|
Kfusion[18] = SK_MX[0]*(P[18][19] + P[18][1]*SH_MAG[0] - P[18][2]*SH_MAG[1] + P[18][3]*SH_MAG[2] + P[18][0]*SK_MX[2] - P[18][16]*SK_MX[1] + P[18][17]*SK_MX[4] - P[18][18]*SK_MX[3]);
|
|
Kfusion[19] = SK_MX[0]*(P[19][19] + P[19][1]*SH_MAG[0] - P[19][2]*SH_MAG[1] + P[19][3]*SH_MAG[2] + P[19][0]*SK_MX[2] - P[19][16]*SK_MX[1] + P[19][17]*SK_MX[4] - P[19][18]*SK_MX[3]);
|
|
Kfusion[20] = SK_MX[0]*(P[20][19] + P[20][1]*SH_MAG[0] - P[20][2]*SH_MAG[1] + P[20][3]*SH_MAG[2] + P[20][0]*SK_MX[2] - P[20][16]*SK_MX[1] + P[20][17]*SK_MX[4] - P[20][18]*SK_MX[3]);
|
|
Kfusion[21] = SK_MX[0]*(P[21][19] + P[21][1]*SH_MAG[0] - P[21][2]*SH_MAG[1] + P[21][3]*SH_MAG[2] + P[21][0]*SK_MX[2] - P[21][16]*SK_MX[1] + P[21][17]*SK_MX[4] - P[21][18]*SK_MX[3]);
|
|
|
|
} else if (index == 1) {
|
|
// Calculate Y axis observation jacobians
|
|
memset(H_MAG, 0, sizeof(H_MAG));
|
|
H_MAG[0] = SH_MAG[2];
|
|
H_MAG[1] = SH_MAG[1];
|
|
H_MAG[2] = SH_MAG[0];
|
|
H_MAG[3] = 2.0f*magD*q2 - SH_MAG[8] - SH_MAG[7];
|
|
H_MAG[16] = 2.0f*q1*q2 - 2.0f*q0*q3;
|
|
H_MAG[17] = SH_MAG[4] - SH_MAG[3] - SH_MAG[5] + SH_MAG[6];
|
|
H_MAG[18] = 2.0f*q0*q1 + 2.0f*q2*q3;
|
|
H_MAG[20] = 1.0f;
|
|
|
|
// Calculate Y axis Kalman gains
|
|
float SK_MY[5];
|
|
SK_MY[0] = 1.0f / _mag_innov_var[1];
|
|
SK_MY[1] = SH_MAG[3] - SH_MAG[4] + SH_MAG[5] - SH_MAG[6];
|
|
SK_MY[2] = SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2;
|
|
SK_MY[3] = 2.0f*q0*q3 - 2.0f*q1*q2;
|
|
SK_MY[4] = 2.0f*q0*q1 + 2.0f*q2*q3;
|
|
|
|
if (!_control_status.flags.update_mag_states_only) {
|
|
Kfusion[0] = SK_MY[0]*(P[0][20] + P[0][0]*SH_MAG[2] + P[0][1]*SH_MAG[1] + P[0][2]*SH_MAG[0] - P[0][3]*SK_MY[2] - P[0][17]*SK_MY[1] - P[0][16]*SK_MY[3] + P[0][18]*SK_MY[4]);
|
|
Kfusion[1] = SK_MY[0]*(P[1][20] + P[1][0]*SH_MAG[2] + P[1][1]*SH_MAG[1] + P[1][2]*SH_MAG[0] - P[1][3]*SK_MY[2] - P[1][17]*SK_MY[1] - P[1][16]*SK_MY[3] + P[1][18]*SK_MY[4]);
|
|
Kfusion[2] = SK_MY[0]*(P[2][20] + P[2][0]*SH_MAG[2] + P[2][1]*SH_MAG[1] + P[2][2]*SH_MAG[0] - P[2][3]*SK_MY[2] - P[2][17]*SK_MY[1] - P[2][16]*SK_MY[3] + P[2][18]*SK_MY[4]);
|
|
Kfusion[3] = SK_MY[0]*(P[3][20] + P[3][0]*SH_MAG[2] + P[3][1]*SH_MAG[1] + P[3][2]*SH_MAG[0] - P[3][3]*SK_MY[2] - P[3][17]*SK_MY[1] - P[3][16]*SK_MY[3] + P[3][18]*SK_MY[4]);
|
|
Kfusion[4] = SK_MY[0]*(P[4][20] + P[4][0]*SH_MAG[2] + P[4][1]*SH_MAG[1] + P[4][2]*SH_MAG[0] - P[4][3]*SK_MY[2] - P[4][17]*SK_MY[1] - P[4][16]*SK_MY[3] + P[4][18]*SK_MY[4]);
|
|
Kfusion[5] = SK_MY[0]*(P[5][20] + P[5][0]*SH_MAG[2] + P[5][1]*SH_MAG[1] + P[5][2]*SH_MAG[0] - P[5][3]*SK_MY[2] - P[5][17]*SK_MY[1] - P[5][16]*SK_MY[3] + P[5][18]*SK_MY[4]);
|
|
Kfusion[6] = SK_MY[0]*(P[6][20] + P[6][0]*SH_MAG[2] + P[6][1]*SH_MAG[1] + P[6][2]*SH_MAG[0] - P[6][3]*SK_MY[2] - P[6][17]*SK_MY[1] - P[6][16]*SK_MY[3] + P[6][18]*SK_MY[4]);
|
|
Kfusion[7] = SK_MY[0]*(P[7][20] + P[7][0]*SH_MAG[2] + P[7][1]*SH_MAG[1] + P[7][2]*SH_MAG[0] - P[7][3]*SK_MY[2] - P[7][17]*SK_MY[1] - P[7][16]*SK_MY[3] + P[7][18]*SK_MY[4]);
|
|
Kfusion[8] = SK_MY[0]*(P[8][20] + P[8][0]*SH_MAG[2] + P[8][1]*SH_MAG[1] + P[8][2]*SH_MAG[0] - P[8][3]*SK_MY[2] - P[8][17]*SK_MY[1] - P[8][16]*SK_MY[3] + P[8][18]*SK_MY[4]);
|
|
Kfusion[9] = SK_MY[0]*(P[9][20] + P[9][0]*SH_MAG[2] + P[9][1]*SH_MAG[1] + P[9][2]*SH_MAG[0] - P[9][3]*SK_MY[2] - P[9][17]*SK_MY[1] - P[9][16]*SK_MY[3] + P[9][18]*SK_MY[4]);
|
|
Kfusion[10] = SK_MY[0]*(P[10][20] + P[10][0]*SH_MAG[2] + P[10][1]*SH_MAG[1] + P[10][2]*SH_MAG[0] - P[10][3]*SK_MY[2] - P[10][17]*SK_MY[1] - P[10][16]*SK_MY[3] + P[10][18]*SK_MY[4]);
|
|
Kfusion[11] = SK_MY[0]*(P[11][20] + P[11][0]*SH_MAG[2] + P[11][1]*SH_MAG[1] + P[11][2]*SH_MAG[0] - P[11][3]*SK_MY[2] - P[11][17]*SK_MY[1] - P[11][16]*SK_MY[3] + P[11][18]*SK_MY[4]);
|
|
Kfusion[12] = SK_MY[0]*(P[12][20] + P[12][0]*SH_MAG[2] + P[12][1]*SH_MAG[1] + P[12][2]*SH_MAG[0] - P[12][3]*SK_MY[2] - P[12][17]*SK_MY[1] - P[12][16]*SK_MY[3] + P[12][18]*SK_MY[4]);
|
|
Kfusion[13] = SK_MY[0]*(P[13][20] + P[13][0]*SH_MAG[2] + P[13][1]*SH_MAG[1] + P[13][2]*SH_MAG[0] - P[13][3]*SK_MY[2] - P[13][17]*SK_MY[1] - P[13][16]*SK_MY[3] + P[13][18]*SK_MY[4]);
|
|
Kfusion[14] = SK_MY[0]*(P[14][20] + P[14][0]*SH_MAG[2] + P[14][1]*SH_MAG[1] + P[14][2]*SH_MAG[0] - P[14][3]*SK_MY[2] - P[14][17]*SK_MY[1] - P[14][16]*SK_MY[3] + P[14][18]*SK_MY[4]);
|
|
Kfusion[15] = SK_MY[0]*(P[15][20] + P[15][0]*SH_MAG[2] + P[15][1]*SH_MAG[1] + P[15][2]*SH_MAG[0] - P[15][3]*SK_MY[2] - P[15][17]*SK_MY[1] - P[15][16]*SK_MY[3] + P[15][18]*SK_MY[4]);
|
|
Kfusion[22] = SK_MY[0]*(P[22][20] + P[22][0]*SH_MAG[2] + P[22][1]*SH_MAG[1] + P[22][2]*SH_MAG[0] - P[22][3]*SK_MY[2] - P[22][17]*SK_MY[1] - P[22][16]*SK_MY[3] + P[22][18]*SK_MY[4]);
|
|
Kfusion[23] = SK_MY[0]*(P[23][20] + P[23][0]*SH_MAG[2] + P[23][1]*SH_MAG[1] + P[23][2]*SH_MAG[0] - P[23][3]*SK_MY[2] - P[23][17]*SK_MY[1] - P[23][16]*SK_MY[3] + P[23][18]*SK_MY[4]);
|
|
} else {
|
|
for (uint8_t i = 0; i < 16; i++) {
|
|
Kfusion[i] = 0.0f;
|
|
}
|
|
Kfusion[22] = 0.0f;
|
|
Kfusion[23] = 0.0f;
|
|
}
|
|
|
|
Kfusion[16] = SK_MY[0]*(P[16][20] + P[16][0]*SH_MAG[2] + P[16][1]*SH_MAG[1] + P[16][2]*SH_MAG[0] - P[16][3]*SK_MY[2] - P[16][17]*SK_MY[1] - P[16][16]*SK_MY[3] + P[16][18]*SK_MY[4]);
|
|
Kfusion[17] = SK_MY[0]*(P[17][20] + P[17][0]*SH_MAG[2] + P[17][1]*SH_MAG[1] + P[17][2]*SH_MAG[0] - P[17][3]*SK_MY[2] - P[17][17]*SK_MY[1] - P[17][16]*SK_MY[3] + P[17][18]*SK_MY[4]);
|
|
Kfusion[18] = SK_MY[0]*(P[18][20] + P[18][0]*SH_MAG[2] + P[18][1]*SH_MAG[1] + P[18][2]*SH_MAG[0] - P[18][3]*SK_MY[2] - P[18][17]*SK_MY[1] - P[18][16]*SK_MY[3] + P[18][18]*SK_MY[4]);
|
|
Kfusion[19] = SK_MY[0]*(P[19][20] + P[19][0]*SH_MAG[2] + P[19][1]*SH_MAG[1] + P[19][2]*SH_MAG[0] - P[19][3]*SK_MY[2] - P[19][17]*SK_MY[1] - P[19][16]*SK_MY[3] + P[19][18]*SK_MY[4]);
|
|
Kfusion[20] = SK_MY[0]*(P[20][20] + P[20][0]*SH_MAG[2] + P[20][1]*SH_MAG[1] + P[20][2]*SH_MAG[0] - P[20][3]*SK_MY[2] - P[20][17]*SK_MY[1] - P[20][16]*SK_MY[3] + P[20][18]*SK_MY[4]);
|
|
Kfusion[21] = SK_MY[0]*(P[21][20] + P[21][0]*SH_MAG[2] + P[21][1]*SH_MAG[1] + P[21][2]*SH_MAG[0] - P[21][3]*SK_MY[2] - P[21][17]*SK_MY[1] - P[21][16]*SK_MY[3] + P[21][18]*SK_MY[4]);
|
|
|
|
} else if (index == 2) {
|
|
// calculate Z axis observation jacobians
|
|
memset(H_MAG, 0, sizeof(H_MAG));
|
|
H_MAG[0] = SH_MAG[1];
|
|
H_MAG[1] = -SH_MAG[2];
|
|
H_MAG[2] = SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2;
|
|
H_MAG[3] = SH_MAG[0];
|
|
H_MAG[16] = 2.0f*q0*q2 + 2.0f*q1*q3;
|
|
H_MAG[17] = 2.0f*q2*q3 - 2.0f*q0*q1;
|
|
H_MAG[18] = SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6];
|
|
H_MAG[21] = 1.0f;
|
|
|
|
// Calculate Z axis Kalman gains
|
|
float SK_MZ[5];
|
|
SK_MZ[0] = 1.0f / _mag_innov_var[2];
|
|
SK_MZ[1] = SH_MAG[3] - SH_MAG[4] - SH_MAG[5] + SH_MAG[6];
|
|
SK_MZ[2] = SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2;
|
|
SK_MZ[3] = 2.0f*q0*q1 - 2.0f*q2*q3;
|
|
SK_MZ[4] = 2.0f*q0*q2 + 2.0f*q1*q3;
|
|
|
|
if (!_control_status.flags.update_mag_states_only) {
|
|
Kfusion[0] = SK_MZ[0]*(P[0][21] + P[0][0]*SH_MAG[1] - P[0][1]*SH_MAG[2] + P[0][3]*SH_MAG[0] + P[0][2]*SK_MZ[2] + P[0][18]*SK_MZ[1] + P[0][16]*SK_MZ[4] - P[0][17]*SK_MZ[3]);
|
|
Kfusion[1] = SK_MZ[0]*(P[1][21] + P[1][0]*SH_MAG[1] - P[1][1]*SH_MAG[2] + P[1][3]*SH_MAG[0] + P[1][2]*SK_MZ[2] + P[1][18]*SK_MZ[1] + P[1][16]*SK_MZ[4] - P[1][17]*SK_MZ[3]);
|
|
Kfusion[2] = SK_MZ[0]*(P[2][21] + P[2][0]*SH_MAG[1] - P[2][1]*SH_MAG[2] + P[2][3]*SH_MAG[0] + P[2][2]*SK_MZ[2] + P[2][18]*SK_MZ[1] + P[2][16]*SK_MZ[4] - P[2][17]*SK_MZ[3]);
|
|
Kfusion[3] = SK_MZ[0]*(P[3][21] + P[3][0]*SH_MAG[1] - P[3][1]*SH_MAG[2] + P[3][3]*SH_MAG[0] + P[3][2]*SK_MZ[2] + P[3][18]*SK_MZ[1] + P[3][16]*SK_MZ[4] - P[3][17]*SK_MZ[3]);
|
|
Kfusion[4] = SK_MZ[0]*(P[4][21] + P[4][0]*SH_MAG[1] - P[4][1]*SH_MAG[2] + P[4][3]*SH_MAG[0] + P[4][2]*SK_MZ[2] + P[4][18]*SK_MZ[1] + P[4][16]*SK_MZ[4] - P[4][17]*SK_MZ[3]);
|
|
Kfusion[5] = SK_MZ[0]*(P[5][21] + P[5][0]*SH_MAG[1] - P[5][1]*SH_MAG[2] + P[5][3]*SH_MAG[0] + P[5][2]*SK_MZ[2] + P[5][18]*SK_MZ[1] + P[5][16]*SK_MZ[4] - P[5][17]*SK_MZ[3]);
|
|
Kfusion[6] = SK_MZ[0]*(P[6][21] + P[6][0]*SH_MAG[1] - P[6][1]*SH_MAG[2] + P[6][3]*SH_MAG[0] + P[6][2]*SK_MZ[2] + P[6][18]*SK_MZ[1] + P[6][16]*SK_MZ[4] - P[6][17]*SK_MZ[3]);
|
|
Kfusion[7] = SK_MZ[0]*(P[7][21] + P[7][0]*SH_MAG[1] - P[7][1]*SH_MAG[2] + P[7][3]*SH_MAG[0] + P[7][2]*SK_MZ[2] + P[7][18]*SK_MZ[1] + P[7][16]*SK_MZ[4] - P[7][17]*SK_MZ[3]);
|
|
Kfusion[8] = SK_MZ[0]*(P[8][21] + P[8][0]*SH_MAG[1] - P[8][1]*SH_MAG[2] + P[8][3]*SH_MAG[0] + P[8][2]*SK_MZ[2] + P[8][18]*SK_MZ[1] + P[8][16]*SK_MZ[4] - P[8][17]*SK_MZ[3]);
|
|
Kfusion[9] = SK_MZ[0]*(P[9][21] + P[9][0]*SH_MAG[1] - P[9][1]*SH_MAG[2] + P[9][3]*SH_MAG[0] + P[9][2]*SK_MZ[2] + P[9][18]*SK_MZ[1] + P[9][16]*SK_MZ[4] - P[9][17]*SK_MZ[3]);
|
|
Kfusion[10] = SK_MZ[0]*(P[10][21] + P[10][0]*SH_MAG[1] - P[10][1]*SH_MAG[2] + P[10][3]*SH_MAG[0] + P[10][2]*SK_MZ[2] + P[10][18]*SK_MZ[1] + P[10][16]*SK_MZ[4] - P[10][17]*SK_MZ[3]);
|
|
Kfusion[11] = SK_MZ[0]*(P[11][21] + P[11][0]*SH_MAG[1] - P[11][1]*SH_MAG[2] + P[11][3]*SH_MAG[0] + P[11][2]*SK_MZ[2] + P[11][18]*SK_MZ[1] + P[11][16]*SK_MZ[4] - P[11][17]*SK_MZ[3]);
|
|
Kfusion[12] = SK_MZ[0]*(P[12][21] + P[12][0]*SH_MAG[1] - P[12][1]*SH_MAG[2] + P[12][3]*SH_MAG[0] + P[12][2]*SK_MZ[2] + P[12][18]*SK_MZ[1] + P[12][16]*SK_MZ[4] - P[12][17]*SK_MZ[3]);
|
|
Kfusion[13] = SK_MZ[0]*(P[13][21] + P[13][0]*SH_MAG[1] - P[13][1]*SH_MAG[2] + P[13][3]*SH_MAG[0] + P[13][2]*SK_MZ[2] + P[13][18]*SK_MZ[1] + P[13][16]*SK_MZ[4] - P[13][17]*SK_MZ[3]);
|
|
Kfusion[14] = SK_MZ[0]*(P[14][21] + P[14][0]*SH_MAG[1] - P[14][1]*SH_MAG[2] + P[14][3]*SH_MAG[0] + P[14][2]*SK_MZ[2] + P[14][18]*SK_MZ[1] + P[14][16]*SK_MZ[4] - P[14][17]*SK_MZ[3]);
|
|
Kfusion[15] = SK_MZ[0]*(P[15][21] + P[15][0]*SH_MAG[1] - P[15][1]*SH_MAG[2] + P[15][3]*SH_MAG[0] + P[15][2]*SK_MZ[2] + P[15][18]*SK_MZ[1] + P[15][16]*SK_MZ[4] - P[15][17]*SK_MZ[3]);
|
|
Kfusion[22] = SK_MZ[0]*(P[22][21] + P[22][0]*SH_MAG[1] - P[22][1]*SH_MAG[2] + P[22][3]*SH_MAG[0] + P[22][2]*SK_MZ[2] + P[22][18]*SK_MZ[1] + P[22][16]*SK_MZ[4] - P[22][17]*SK_MZ[3]);
|
|
Kfusion[23] = SK_MZ[0]*(P[23][21] + P[23][0]*SH_MAG[1] - P[23][1]*SH_MAG[2] + P[23][3]*SH_MAG[0] + P[23][2]*SK_MZ[2] + P[23][18]*SK_MZ[1] + P[23][16]*SK_MZ[4] - P[23][17]*SK_MZ[3]);
|
|
} else {
|
|
for (uint8_t i = 0; i < 16; i++) {
|
|
Kfusion[i] = 0.0f;
|
|
}
|
|
Kfusion[22] = 0.0f;
|
|
Kfusion[23] = 0.0f;
|
|
}
|
|
|
|
Kfusion[16] = SK_MZ[0]*(P[16][21] + P[16][0]*SH_MAG[1] - P[16][1]*SH_MAG[2] + P[16][3]*SH_MAG[0] + P[16][2]*SK_MZ[2] + P[16][18]*SK_MZ[1] + P[16][16]*SK_MZ[4] - P[16][17]*SK_MZ[3]);
|
|
Kfusion[17] = SK_MZ[0]*(P[17][21] + P[17][0]*SH_MAG[1] - P[17][1]*SH_MAG[2] + P[17][3]*SH_MAG[0] + P[17][2]*SK_MZ[2] + P[17][18]*SK_MZ[1] + P[17][16]*SK_MZ[4] - P[17][17]*SK_MZ[3]);
|
|
Kfusion[18] = SK_MZ[0]*(P[18][21] + P[18][0]*SH_MAG[1] - P[18][1]*SH_MAG[2] + P[18][3]*SH_MAG[0] + P[18][2]*SK_MZ[2] + P[18][18]*SK_MZ[1] + P[18][16]*SK_MZ[4] - P[18][17]*SK_MZ[3]);
|
|
Kfusion[19] = SK_MZ[0]*(P[19][21] + P[19][0]*SH_MAG[1] - P[19][1]*SH_MAG[2] + P[19][3]*SH_MAG[0] + P[19][2]*SK_MZ[2] + P[19][18]*SK_MZ[1] + P[19][16]*SK_MZ[4] - P[19][17]*SK_MZ[3]);
|
|
Kfusion[20] = SK_MZ[0]*(P[20][21] + P[20][0]*SH_MAG[1] - P[20][1]*SH_MAG[2] + P[20][3]*SH_MAG[0] + P[20][2]*SK_MZ[2] + P[20][18]*SK_MZ[1] + P[20][16]*SK_MZ[4] - P[20][17]*SK_MZ[3]);
|
|
Kfusion[21] = SK_MZ[0]*(P[21][21] + P[21][0]*SH_MAG[1] - P[21][1]*SH_MAG[2] + P[21][3]*SH_MAG[0] + P[21][2]*SK_MZ[2] + P[21][18]*SK_MZ[1] + P[21][16]*SK_MZ[4] - P[21][17]*SK_MZ[3]);
|
|
|
|
} else {
|
|
return;
|
|
}
|
|
|
|
// apply covariance correction via P_new = (I -K*H)*P
|
|
// first calculate expression for KHP
|
|
// then calculate P - KHP
|
|
float KHP[_k_num_states][_k_num_states];
|
|
float KH[10];
|
|
for (unsigned row = 0; row < _k_num_states; row++) {
|
|
|
|
KH[0] = Kfusion[row] * H_MAG[0];
|
|
KH[1] = Kfusion[row] * H_MAG[1];
|
|
KH[2] = Kfusion[row] * H_MAG[2];
|
|
KH[3] = Kfusion[row] * H_MAG[3];
|
|
KH[4] = Kfusion[row] * H_MAG[16];
|
|
KH[5] = Kfusion[row] * H_MAG[17];
|
|
KH[6] = Kfusion[row] * H_MAG[18];
|
|
KH[7] = Kfusion[row] * H_MAG[19];
|
|
KH[8] = Kfusion[row] * H_MAG[20];
|
|
KH[9] = Kfusion[row] * H_MAG[21];
|
|
|
|
for (unsigned column = 0; column < _k_num_states; column++) {
|
|
float tmp = KH[0] * P[0][column];
|
|
tmp += KH[1] * P[1][column];
|
|
tmp += KH[2] * P[2][column];
|
|
tmp += KH[3] * P[3][column];
|
|
tmp += KH[4] * P[16][column];
|
|
tmp += KH[5] * P[17][column];
|
|
tmp += KH[6] * P[18][column];
|
|
tmp += KH[7] * P[19][column];
|
|
tmp += KH[8] * P[20][column];
|
|
tmp += KH[9] * P[21][column];
|
|
KHP[row][column] = tmp;
|
|
}
|
|
}
|
|
|
|
// if the covariance correction will result in a negative variance, then
|
|
// the covariance marix is unhealthy and must be corrected
|
|
_fault_status.flags.bad_mag_x = false;
|
|
_fault_status.flags.bad_mag_y = false;
|
|
_fault_status.flags.bad_mag_z = false;
|
|
for (int i = 0; i < _k_num_states; i++) {
|
|
if (P[i][i] < KHP[i][i]) {
|
|
// zero rows and columns
|
|
zeroRows(P,i,i);
|
|
zeroCols(P,i,i);
|
|
|
|
//flag as unhealthy
|
|
healthy = false;
|
|
|
|
// update individual measurement health status
|
|
if (index == 0) {
|
|
_fault_status.flags.bad_mag_x = true;
|
|
} else if (index == 1) {
|
|
_fault_status.flags.bad_mag_y = true;
|
|
} else if (index == 2) {
|
|
_fault_status.flags.bad_mag_z = true;
|
|
}
|
|
}
|
|
}
|
|
|
|
// only apply covariance and state corrrections if healthy
|
|
if (healthy) {
|
|
// apply the covariance corrections
|
|
for (unsigned row = 0; row < _k_num_states; row++) {
|
|
for (unsigned column = 0; column < _k_num_states; column++) {
|
|
P[row][column] = P[row][column] - KHP[row][column];
|
|
}
|
|
}
|
|
|
|
// correct the covariance marix for gross errors
|
|
fixCovarianceErrors();
|
|
|
|
// apply the state corrections
|
|
fuse(Kfusion, _mag_innov[index]);
|
|
|
|
}
|
|
}
|
|
}
|
|
|
|
void Ekf::fuseHeading()
|
|
{
|
|
// assign intermediate state variables
|
|
float q0 = _state.quat_nominal(0);
|
|
float q1 = _state.quat_nominal(1);
|
|
float q2 = _state.quat_nominal(2);
|
|
float q3 = _state.quat_nominal(3);
|
|
|
|
float R_YAW = 1.0f;
|
|
float predicted_hdg;
|
|
float H_YAW[4];
|
|
Vector3f mag_earth_pred;
|
|
float measured_hdg;
|
|
|
|
// determine if a 321 or 312 Euler sequence is best
|
|
if (fabsf(_R_to_earth(2, 0)) < fabsf(_R_to_earth(2, 1))) {
|
|
// calculate observation jacobian when we are observing the first rotation in a 321 sequence
|
|
float t9 = q0*q3;
|
|
float t10 = q1*q2;
|
|
float t2 = t9+t10;
|
|
float t3 = q0*q0;
|
|
float t4 = q1*q1;
|
|
float t5 = q2*q2;
|
|
float t6 = q3*q3;
|
|
float t7 = t3+t4-t5-t6;
|
|
float t8 = t7*t7;
|
|
if (t8 > 1e-6f) {
|
|
t8 = 1.0f/t8;
|
|
} else {
|
|
return;
|
|
}
|
|
float t11 = t2*t2;
|
|
float t12 = t8*t11*4.0f;
|
|
float t13 = t12+1.0f;
|
|
float t14;
|
|
if (fabsf(t13) > 1e-6f) {
|
|
t14 = 1.0f/t13;
|
|
} else {
|
|
return;
|
|
}
|
|
|
|
H_YAW[0] = t8*t14*(q3*t3-q3*t4+q3*t5+q3*t6+q0*q1*q2*2.0f)*-2.0f;
|
|
H_YAW[1] = t8*t14*(-q2*t3+q2*t4+q2*t5+q2*t6+q0*q1*q3*2.0f)*-2.0f;
|
|
H_YAW[2] = t8*t14*(q1*t3+q1*t4+q1*t5-q1*t6+q0*q2*q3*2.0f)*2.0f;
|
|
H_YAW[3] = t8*t14*(q0*t3+q0*t4-q0*t5+q0*t6+q1*q2*q3*2.0f)*2.0f;
|
|
|
|
// rotate the magnetometer measurement into earth frame
|
|
Eulerf euler321(_state.quat_nominal);
|
|
predicted_hdg = euler321(2); // we will need the predicted heading to calculate the innovation
|
|
|
|
// calculate the observed yaw angle
|
|
if (_control_status.flags.mag_hdg) {
|
|
// Set the yaw angle to zero and rotate the measurements into earth frame using the zero yaw angle
|
|
euler321(2) = 0.0f;
|
|
Dcmf R_to_earth(euler321);
|
|
|
|
// rotate the magnetometer measurements into earth frame using a zero yaw angle
|
|
mag_earth_pred = R_to_earth * _mag_sample_delayed.mag;
|
|
|
|
// the angle of the projection onto the horizontal gives the yaw angle
|
|
measured_hdg = -atan2f(mag_earth_pred(1), mag_earth_pred(0)) + _mag_declination;
|
|
|
|
} else if (_control_status.flags.ev_yaw) {
|
|
// calculate the yaw angle for a 321 sequence
|
|
// Expressions obtained from yaw_input_321.c produced by https://github.com/PX4/ecl/blob/master/matlab/scripts/Inertial%20Nav%20EKF/quat2yaw321.m
|
|
float Tbn_1_0 = 2.0f*(_ev_sample_delayed.quat(0)*_ev_sample_delayed.quat(3)+_ev_sample_delayed.quat(1)*_ev_sample_delayed.quat(2));
|
|
float Tbn_0_0 = sq(_ev_sample_delayed.quat(0))+sq(_ev_sample_delayed.quat(1))-sq(_ev_sample_delayed.quat(2))-sq(_ev_sample_delayed.quat(3));
|
|
measured_hdg = atan2f(Tbn_1_0,Tbn_0_0);
|
|
|
|
} else {
|
|
// there is no yaw observation
|
|
return;
|
|
}
|
|
|
|
} else {
|
|
// calculate observaton jacobian when we are observing a rotation in a 312 sequence
|
|
float t9 = q0*q3;
|
|
float t10 = q1*q2;
|
|
float t2 = t9-t10;
|
|
float t3 = q0*q0;
|
|
float t4 = q1*q1;
|
|
float t5 = q2*q2;
|
|
float t6 = q3*q3;
|
|
float t7 = t3-t4+t5-t6;
|
|
float t8 = t7*t7;
|
|
if (t8 > 1e-6f) {
|
|
t8 = 1.0f/t8;
|
|
} else {
|
|
return;
|
|
}
|
|
float t11 = t2*t2;
|
|
float t12 = t8*t11*4.0f;
|
|
float t13 = t12+1.0f;
|
|
float t14;
|
|
if (fabsf(t13) > 1e-6f) {
|
|
t14 = 1.0f/t13;
|
|
} else {
|
|
return;
|
|
}
|
|
|
|
H_YAW[0] = t8*t14*(q3*t3+q3*t4-q3*t5+q3*t6-q0*q1*q2*2.0f)*-2.0f;
|
|
H_YAW[1] = t8*t14*(q2*t3+q2*t4+q2*t5-q2*t6-q0*q1*q3*2.0f)*-2.0f;
|
|
H_YAW[2] = t8*t14*(-q1*t3+q1*t4+q1*t5+q1*t6-q0*q2*q3*2.0f)*2.0f;
|
|
H_YAW[3] = t8*t14*(q0*t3-q0*t4+q0*t5+q0*t6-q1*q2*q3*2.0f)*2.0f;
|
|
|
|
/* Calculate the 312 sequence euler angles that rotate from earth to body frame
|
|
* Derived from https://github.com/PX4/ecl/blob/master/matlab/scripts/Inertial%20Nav%20EKF/quat2yaw312.m
|
|
* Body to nav frame transformation using a yaw-roll-pitch rotation sequence is given by:
|
|
*
|
|
[ cos(pitch)*cos(yaw) - sin(pitch)*sin(roll)*sin(yaw), -cos(roll)*sin(yaw), cos(yaw)*sin(pitch) + cos(pitch)*sin(roll)*sin(yaw)]
|
|
[ cos(pitch)*sin(yaw) + cos(yaw)*sin(pitch)*sin(roll), cos(roll)*cos(yaw), sin(pitch)*sin(yaw) - cos(pitch)*cos(yaw)*sin(roll)]
|
|
[ -cos(roll)*sin(pitch), sin(roll), cos(pitch)*cos(roll)]
|
|
*/
|
|
float yaw = atan2f(-_R_to_earth(0, 1), _R_to_earth(1, 1)); // first rotation (yaw)
|
|
float roll = asinf(_R_to_earth(2, 1)); // second rotation (roll)
|
|
float pitch = atan2f(-_R_to_earth(2, 0), _R_to_earth(2, 2)); // third rotation (pitch)
|
|
|
|
predicted_hdg = yaw; // we will need the predicted heading to calculate the innovation
|
|
|
|
// calculate the observed yaw angle
|
|
if (_control_status.flags.mag_hdg) {
|
|
// Set the first rotation (yaw) to zero and rotate the measurements into earth frame
|
|
yaw = 0.0f;
|
|
|
|
// Calculate the body to earth frame rotation matrix from the euler angles using a 312 rotation sequence
|
|
// Equations from Tbn_312.c produced by https://github.com/PX4/ecl/blob/master/matlab/scripts/Inertial%20Nav%20EKF/quat2yaw312.m
|
|
Dcmf R_to_earth;
|
|
float sy = sinf(yaw);
|
|
float cy = cosf(yaw);
|
|
float sp = sinf(pitch);
|
|
float cp = cosf(pitch);
|
|
float sr = sinf(roll);
|
|
float cr = cosf(roll);
|
|
R_to_earth(0,0) = cy*cp-sy*sp*sr;
|
|
R_to_earth(0,1) = -sy*cr;
|
|
R_to_earth(0,2) = cy*sp+sy*cp*sr;
|
|
R_to_earth(1,0) = sy*cp+cy*sp*sr;
|
|
R_to_earth(1,1) = cy*cr;
|
|
R_to_earth(1,2) = sy*sp-cy*cp*sr;
|
|
R_to_earth(2,0) = -sp*cr;
|
|
R_to_earth(2,1) = sr;
|
|
R_to_earth(2,2) = cp*cr;
|
|
|
|
// rotate the magnetometer measurements into earth frame using a zero yaw angle
|
|
mag_earth_pred = R_to_earth * _mag_sample_delayed.mag;
|
|
|
|
// the angle of the projection onto the horizontal gives the yaw angle
|
|
measured_hdg = -atan2f(mag_earth_pred(1), mag_earth_pred(0)) + _mag_declination;
|
|
|
|
} else if (_control_status.flags.ev_yaw) {
|
|
// calculate the yaw angle for a 312 sequence
|
|
// Values from yaw_input_312.c file produced by https://github.com/PX4/ecl/blob/master/matlab/scripts/Inertial%20Nav%20EKF/quat2yaw312.m
|
|
float Tbn_0_1_neg = 2.0f*(_ev_sample_delayed.quat(0)*_ev_sample_delayed.quat(3)-_ev_sample_delayed.quat(1)*_ev_sample_delayed.quat(2));
|
|
float Tbn_1_1 = sq(_ev_sample_delayed.quat(0))-sq(_ev_sample_delayed.quat(1))+sq(_ev_sample_delayed.quat(2))-sq(_ev_sample_delayed.quat(3));
|
|
measured_hdg = atan2f(Tbn_0_1_neg,Tbn_1_1);
|
|
|
|
} else {
|
|
// there is no yaw observation
|
|
return;
|
|
|
|
}
|
|
}
|
|
|
|
// Calculate the observation variance
|
|
if (_control_status.flags.mag_hdg) {
|
|
// using magnetic heading tuning parameter
|
|
R_YAW = sq(fmaxf(_params.mag_heading_noise, 1.0e-2f));
|
|
} else if (_control_status.flags.ev_yaw) {
|
|
// using error estimate from external vision data
|
|
R_YAW = sq(fmaxf(_ev_sample_delayed.angErr, 1.0e-2f));
|
|
} else {
|
|
// there is no yaw observation
|
|
return;
|
|
}
|
|
|
|
// Calculate innovation variance and Kalman gains, taking advantage of the fact that only the first 3 elements in H are non zero
|
|
// calculate the innovaton variance
|
|
float PH[4];
|
|
_heading_innov_var = R_YAW;
|
|
for (unsigned row = 0; row <= 3; row++) {
|
|
PH[row] = 0.0f;
|
|
|
|
for (uint8_t col = 0; col <= 3; col++) {
|
|
PH[row] += P[row][col] * H_YAW[col];
|
|
}
|
|
|
|
_heading_innov_var += H_YAW[row] * PH[row];
|
|
}
|
|
|
|
float heading_innov_var_inv;
|
|
|
|
// check if the innovation variance calculation is badly conditioned
|
|
if (_heading_innov_var >= R_YAW) {
|
|
// the innovation variance contribution from the state covariances is not negative, no fault
|
|
_fault_status.flags.bad_mag_hdg = false;
|
|
heading_innov_var_inv = 1.0f / _heading_innov_var;
|
|
|
|
} else {
|
|
// the innovation variance contribution from the state covariances is negative which means the covariance matrix is badly conditioned
|
|
_fault_status.flags.bad_mag_hdg = true;
|
|
|
|
// we reinitialise the covariance matrix and abort this fusion step
|
|
initialiseCovariance();
|
|
ECL_ERR("EKF mag yaw fusion numerical error - covariance reset");
|
|
return;
|
|
}
|
|
|
|
// calculate the Kalman gains
|
|
// only calculate gains for states we are using
|
|
float Kfusion[_k_num_states] = {};
|
|
|
|
for (uint8_t row = 0; row <= 15; row++) {
|
|
Kfusion[row] = 0.0f;
|
|
|
|
for (uint8_t col = 0; col <= 3; col++) {
|
|
Kfusion[row] += P[row][col] * H_YAW[col];
|
|
}
|
|
|
|
Kfusion[row] *= heading_innov_var_inv;
|
|
}
|
|
|
|
if (_control_status.flags.wind) {
|
|
for (uint8_t row = 22; row <= 23; row++) {
|
|
Kfusion[row] = 0.0f;
|
|
|
|
for (uint8_t col = 0; col <= 3; col++) {
|
|
Kfusion[row] += P[row][col] * H_YAW[col];
|
|
}
|
|
|
|
Kfusion[row] *= heading_innov_var_inv;
|
|
}
|
|
}
|
|
|
|
// wrap the heading to the interval between +-pi
|
|
measured_hdg = wrap_pi(measured_hdg);
|
|
|
|
// calculate the innovation
|
|
_heading_innov = predicted_hdg - measured_hdg;
|
|
|
|
// wrap the innovation to the interval between +-pi
|
|
_heading_innov = wrap_pi(_heading_innov);
|
|
|
|
// innovation test ratio
|
|
_yaw_test_ratio = sq(_heading_innov) / (sq(math::max(_params.heading_innov_gate, 1.0f)) * _heading_innov_var);
|
|
|
|
// we are no longer using 3-axis fusion so set the reported test levels to zero
|
|
memset(_mag_test_ratio, 0, sizeof(_mag_test_ratio));
|
|
|
|
// set the magnetometer unhealthy if the test fails
|
|
if (_yaw_test_ratio > 1.0f) {
|
|
_innov_check_fail_status.flags.reject_yaw = true;
|
|
|
|
// if we are in air we don't want to fuse the measurement
|
|
// we allow to use it when on the ground because the large innovation could be caused
|
|
// by interference or a large initial gyro bias
|
|
if (_control_status.flags.in_air) {
|
|
return;
|
|
|
|
} else {
|
|
// constrain the innovation to the maximum set by the gate
|
|
float gate_limit = sqrtf((sq(math::max(_params.heading_innov_gate, 1.0f)) * _heading_innov_var));
|
|
_heading_innov = math::constrain(_heading_innov, -gate_limit, gate_limit);
|
|
}
|
|
|
|
} else {
|
|
_innov_check_fail_status.flags.reject_yaw = false;
|
|
}
|
|
|
|
// apply covariance correction via P_new = (I -K*H)*P
|
|
// first calculate expression for KHP
|
|
// then calculate P - KHP
|
|
float KHP[_k_num_states][_k_num_states];
|
|
float KH[4];
|
|
for (unsigned row = 0; row < _k_num_states; row++) {
|
|
|
|
KH[0] = Kfusion[row] * H_YAW[0];
|
|
KH[1] = Kfusion[row] * H_YAW[1];
|
|
KH[2] = Kfusion[row] * H_YAW[2];
|
|
KH[3] = Kfusion[row] * H_YAW[3];
|
|
|
|
for (unsigned column = 0; column < _k_num_states; column++) {
|
|
float tmp = KH[0] * P[0][column];
|
|
tmp += KH[1] * P[1][column];
|
|
tmp += KH[2] * P[2][column];
|
|
tmp += KH[3] * P[3][column];
|
|
KHP[row][column] = tmp;
|
|
}
|
|
}
|
|
|
|
// if the covariance correction will result in a negative variance, then
|
|
// the covariance marix is unhealthy and must be corrected
|
|
bool healthy = true;
|
|
_fault_status.flags.bad_mag_hdg = false;
|
|
for (int i = 0; i < _k_num_states; i++) {
|
|
if (P[i][i] < KHP[i][i]) {
|
|
// zero rows and columns
|
|
zeroRows(P,i,i);
|
|
zeroCols(P,i,i);
|
|
|
|
//flag as unhealthy
|
|
healthy = false;
|
|
|
|
// update individual measurement health status
|
|
_fault_status.flags.bad_mag_hdg = true;
|
|
|
|
}
|
|
}
|
|
|
|
// only apply covariance and state corrrections if healthy
|
|
if (healthy) {
|
|
// apply the covariance corrections
|
|
for (unsigned row = 0; row < _k_num_states; row++) {
|
|
for (unsigned column = 0; column < _k_num_states; column++) {
|
|
P[row][column] = P[row][column] - KHP[row][column];
|
|
}
|
|
}
|
|
|
|
// correct the covariance marix for gross errors
|
|
fixCovarianceErrors();
|
|
|
|
// apply the state corrections
|
|
fuse(Kfusion, _heading_innov);
|
|
|
|
}
|
|
}
|
|
|
|
void Ekf::fuseDeclination()
|
|
{
|
|
// assign intermediate state variables
|
|
float magN = _state.mag_I(0);
|
|
float magE = _state.mag_I(1);
|
|
|
|
float R_DECL = sq(0.5f);
|
|
|
|
// Calculate intermediate variables
|
|
float t2 = magE*magE;
|
|
float t3 = magN*magN;
|
|
float t4 = t2+t3;
|
|
// if the horizontal magnetic field is too small, this calculation will be badly conditioned
|
|
if (t4 < 1e-4f) {
|
|
return;
|
|
}
|
|
float t5 = P[16][16]*t2;
|
|
float t6 = P[17][17]*t3;
|
|
float t7 = t2*t2;
|
|
float t8 = R_DECL*t7;
|
|
float t9 = t3*t3;
|
|
float t10 = R_DECL*t9;
|
|
float t11 = R_DECL*t2*t3*2.0f;
|
|
float t14 = P[16][17]*magE*magN;
|
|
float t15 = P[17][16]*magE*magN;
|
|
float t12 = t5+t6+t8+t10+t11-t14-t15;
|
|
float t13;
|
|
if (fabsf(t12) > 1e-6f) {
|
|
t13 = 1.0f / t12;
|
|
} else {
|
|
return;
|
|
}
|
|
float t18 = magE*magE;
|
|
float t19 = magN*magN;
|
|
float t20 = t18+t19;
|
|
float t21;
|
|
if (fabsf(t20) > 1e-6f) {
|
|
t21 = 1.0f/t20;
|
|
} else {
|
|
return;
|
|
}
|
|
|
|
// Calculate the observation Jacobian
|
|
// Note only 2 terms are non-zero which can be used in matrix operations for calculation of Kalman gains and covariance update to significantly reduce cost
|
|
float H_DECL[24] = {};
|
|
H_DECL[16] = -magE*t21;
|
|
H_DECL[17] = magN*t21;
|
|
|
|
// Calculate the Kalman gains
|
|
float Kfusion[_k_num_states] = {};
|
|
Kfusion[0] = -t4*t13*(P[0][16]*magE-P[0][17]*magN);
|
|
Kfusion[1] = -t4*t13*(P[1][16]*magE-P[1][17]*magN);
|
|
Kfusion[2] = -t4*t13*(P[2][16]*magE-P[2][17]*magN);
|
|
Kfusion[3] = -t4*t13*(P[3][16]*magE-P[3][17]*magN);
|
|
Kfusion[4] = -t4*t13*(P[4][16]*magE-P[4][17]*magN);
|
|
Kfusion[5] = -t4*t13*(P[5][16]*magE-P[5][17]*magN);
|
|
Kfusion[6] = -t4*t13*(P[6][16]*magE-P[6][17]*magN);
|
|
Kfusion[7] = -t4*t13*(P[7][16]*magE-P[7][17]*magN);
|
|
Kfusion[8] = -t4*t13*(P[8][16]*magE-P[8][17]*magN);
|
|
Kfusion[9] = -t4*t13*(P[9][16]*magE-P[9][17]*magN);
|
|
Kfusion[10] = -t4*t13*(P[10][16]*magE-P[10][17]*magN);
|
|
Kfusion[11] = -t4*t13*(P[11][16]*magE-P[11][17]*magN);
|
|
Kfusion[12] = -t4*t13*(P[12][16]*magE-P[12][17]*magN);
|
|
Kfusion[13] = -t4*t13*(P[13][16]*magE-P[13][17]*magN);
|
|
Kfusion[14] = -t4*t13*(P[14][16]*magE-P[14][17]*magN);
|
|
Kfusion[15] = -t4*t13*(P[15][16]*magE-P[15][17]*magN);
|
|
Kfusion[16] = -t4*t13*(P[16][16]*magE-P[16][17]*magN);
|
|
Kfusion[17] = -t4*t13*(P[17][16]*magE-P[17][17]*magN);
|
|
Kfusion[18] = -t4*t13*(P[18][16]*magE-P[18][17]*magN);
|
|
Kfusion[19] = -t4*t13*(P[19][16]*magE-P[19][17]*magN);
|
|
Kfusion[20] = -t4*t13*(P[20][16]*magE-P[20][17]*magN);
|
|
Kfusion[21] = -t4*t13*(P[21][16]*magE-P[21][17]*magN);
|
|
Kfusion[22] = -t4*t13*(P[22][16]*magE-P[22][17]*magN);
|
|
Kfusion[23] = -t4*t13*(P[23][16]*magE-P[23][17]*magN);
|
|
|
|
// calculate innovation and constrain
|
|
float innovation = atan2f(magE, magN) - _mag_declination;
|
|
innovation = math::constrain(innovation, -0.5f, 0.5f);
|
|
|
|
// apply covariance correction via P_new = (I -K*H)*P
|
|
// first calculate expression for KHP
|
|
// then calculate P - KHP
|
|
// take advantage of the empty columns in KH to reduce the number of operations
|
|
float KHP[_k_num_states][_k_num_states];
|
|
float KH[2];
|
|
for (unsigned row = 0; row < _k_num_states; row++) {
|
|
|
|
KH[0] = Kfusion[row] * H_DECL[16];
|
|
KH[1] = Kfusion[row] * H_DECL[17];
|
|
|
|
for (unsigned column = 0; column < _k_num_states; column++) {
|
|
float tmp = KH[0] * P[16][column];
|
|
tmp += KH[1] * P[17][column];
|
|
KHP[row][column] = tmp;
|
|
}
|
|
}
|
|
|
|
// if the covariance correction will result in a negative variance, then
|
|
// the covariance marix is unhealthy and must be corrected
|
|
bool healthy = true;
|
|
_fault_status.flags.bad_mag_decl = false;
|
|
for (int i = 0; i < _k_num_states; i++) {
|
|
if (P[i][i] < KHP[i][i]) {
|
|
// zero rows and columns
|
|
zeroRows(P,i,i);
|
|
zeroCols(P,i,i);
|
|
|
|
//flag as unhealthy
|
|
healthy = false;
|
|
|
|
// update individual measurement health status
|
|
_fault_status.flags.bad_mag_decl = true;
|
|
|
|
}
|
|
}
|
|
|
|
// only apply covariance and state corrrections if healthy
|
|
if (healthy) {
|
|
// apply the covariance corrections
|
|
for (unsigned row = 0; row < _k_num_states; row++) {
|
|
for (unsigned column = 0; column < _k_num_states; column++) {
|
|
P[row][column] = P[row][column] - KHP[row][column];
|
|
}
|
|
}
|
|
|
|
// correct the covariance marix for gross errors
|
|
fixCovarianceErrors();
|
|
|
|
// apply the state corrections
|
|
fuse(Kfusion, innovation);
|
|
|
|
}
|
|
}
|