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PX4-Autopilot/EKF/sideslip_fusion.cpp
Paul Riseborough 0d0f46ec1c EKF: Don't run unnecessary makeRowColSymmetric operation 
This operation is expensive when done to the whole covariance matrix and unnecessary after covariance prediction because we calculate the upper diagonal and copy across so it is already symmetric.
2020-01-02 19:26:57 +11:00

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/**
* @file sideslip_fusion.cpp
* sideslip fusion methods.
*
* @author Carl Olsson <carlolsson.co@gmail.com>
* @author Paul Riseborough <p_riseborough@live.com.au>
*
*/
#include "ekf.h"
#include <ecl.h>
#include <mathlib/mathlib.h>
void Ekf::fuseSideslip()
{
float SH_BETA[13] = {}; // Variable used to optimise calculations of measurement jacobian
float H_BETA[24] = {}; // Observation Jacobian
float SK_BETA[8] = {}; // Variable used to optimise calculations of the Kalman gain vector
float Kfusion[24] = {}; // Kalman gain vector
float R_BETA = _params.beta_noise;
// get latest estimated orientation
float q0 = _state.quat_nominal(0);
float q1 = _state.quat_nominal(1);
float q2 = _state.quat_nominal(2);
float q3 = _state.quat_nominal(3);
// get latest velocity in earth frame
float vn = _state.vel(0);
float ve = _state.vel(1);
float vd = _state.vel(2);
// get latest wind velocity in earth frame
float vwn = _state.wind_vel(0);
float vwe = _state.wind_vel(1);
// relative wind velocity in earth frame
Vector3f rel_wind;
rel_wind(0) = vn - vwn;
rel_wind(1) = ve - vwe;
rel_wind(2) = vd;
Dcmf earth_to_body = quat_to_invrotmat(_state.quat_nominal);
// rotate into body axes
rel_wind = earth_to_body * rel_wind;
// perform fusion of assumed sideslip = 0
if (rel_wind.norm() > 7.0f) {
// Calculate the observation jacobians
// intermediate variable from algebraic optimisation
SH_BETA[0] = (vn - vwn)*(sq(q0) + sq(q1) - sq(q2) - sq(q3)) - vd*(2.0f*q0*q2 - 2.0f*q1*q3) + (ve - vwe)*(2.0f*q0*q3 + 2.0f*q1*q2);
if (fabsf(SH_BETA[0]) <= 1e-9f) {
return;
}
SH_BETA[1] = (ve - vwe)*(sq(q0) - sq(q1) + sq(q2) - sq(q3)) + vd*(2.0f*q0*q1 + 2.0f*q2*q3) - (vn - vwn)*(2.0f*q0*q3 - 2.0f*q1*q2);
SH_BETA[2] = vn - vwn;
SH_BETA[3] = ve - vwe;
SH_BETA[4] = 1.0f/sq(SH_BETA[0]);
SH_BETA[5] = 1.0f/SH_BETA[0];
SH_BETA[6] = SH_BETA[5]*(sq(q0) - sq(q1) + sq(q2) - sq(q3));
SH_BETA[7] = sq(q0) + sq(q1) - sq(q2) - sq(q3);
SH_BETA[8] = 2.0f*q0*SH_BETA[3] - 2.0f*q3*SH_BETA[2] + 2.0f*q1*vd;
SH_BETA[9] = 2.0f*q0*SH_BETA[2] + 2.0f*q3*SH_BETA[3] - 2.0f*q2*vd;
SH_BETA[10] = 2.0f*q2*SH_BETA[2] - 2.0f*q1*SH_BETA[3] + 2.0f*q0*vd;
SH_BETA[11] = 2.0f*q1*SH_BETA[2] + 2.0f*q2*SH_BETA[3] + 2.0f*q3*vd;
SH_BETA[12] = 2.0f*q0*q3;
H_BETA[0] = SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9];
H_BETA[1] = SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11];
H_BETA[2] = SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10];
H_BETA[3] = - SH_BETA[5]*SH_BETA[9] - SH_BETA[1]*SH_BETA[4]*SH_BETA[8];
H_BETA[4] = - SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) - SH_BETA[1]*SH_BETA[4]*SH_BETA[7];
H_BETA[5] = SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2);
H_BETA[6] = SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3);
H_BETA[22] = SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7];
H_BETA[23] = SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2) - SH_BETA[6];
for (uint8_t i = 7; i <= 21; i++) {
H_BETA[i] = 0.0f;
}
// determine if we need the sideslip fusion to correct states other than wind
bool update_wind_only = !_is_wind_dead_reckoning;
// intermediate variables - note SK_BETA[0] is 1/(innovation variance)
_beta_innov_var = (R_BETA - (SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7])*(P(22,4)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P(4,4)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P(5,4)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) - P(23,4)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) + P(0,4)*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P(1,4)*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P(2,4)*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P(3,4)*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P(6,4)*(SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))) + (SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7])*(P(22,22)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P(4,22)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P(5,22)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) - P(23,22)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) + P(0,22)*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P(1,22)*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P(2,22)*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P(3,22)*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P(6,22)*(SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))) + (SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2))*(P(22,5)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P(4,5)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P(5,5)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) - P(23,5)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) + P(0,5)*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P(1,5)*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P(2,5)*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P(3,5)*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P(6,5)*(SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))) - (SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2))*(P(22,23)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P(4,23)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P(5,23)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) - P(23,23)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) + P(0,23)*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P(1,23)*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P(2,23)*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P(3,23)*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P(6,23)*(SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))) + (SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9])*(P(22,0)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P(4,0)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P(5,0)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) - P(23,0)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) + P(0,0)*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P(1,0)*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P(2,0)*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P(3,0)*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P(6,0)*(SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))) + (SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11])*(P(22,1)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P(4,1)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P(5,1)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) - P(23,1)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) + P(0,1)*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P(1,1)*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P(2,1)*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P(3,1)*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P(6,1)*(SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))) + (SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10])*(P(22,2)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P(4,2)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P(5,2)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) - P(23,2)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) + P(0,2)*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P(1,2)*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P(2,2)*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P(3,2)*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P(6,2)*(SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))) - (SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8])*(P(22,3)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P(4,3)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P(5,3)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) - P(23,3)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) + P(0,3)*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P(1,3)*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P(2,3)*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P(3,3)*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P(6,3)*(SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))) + (SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))*(P(22,6)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) - P(4,6)*(SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7]) + P(5,6)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) - P(23,6)*(SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2)) + P(0,6)*(SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9]) + P(1,6)*(SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11]) + P(2,6)*(SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10]) - P(3,6)*(SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8]) + P(6,6)*(SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3))));
if (_beta_innov_var >= R_BETA) {
SK_BETA[0] = 1.0f / _beta_innov_var;
_fault_status.flags.bad_sideslip = false;
} else { // Reset the estimator
_fault_status.flags.bad_sideslip = true;
// if we are getting aiding from other sources, warn and reset the wind states and covariances only
if (update_wind_only) {
resetWindStates();
resetWindCovariance();
ECL_ERR_TIMESTAMPED("synthetic sideslip fusion badly conditioned - wind covariance reset");
} else {
initialiseCovariance();
_state.wind_vel.setZero();
ECL_ERR_TIMESTAMPED("synthetic sideslip fusion badly conditioned - full covariance reset");
}
return;
}
SK_BETA[1] = SH_BETA[5]*(SH_BETA[12] - 2.0f*q1*q2) + SH_BETA[1]*SH_BETA[4]*SH_BETA[7];
SK_BETA[2] = SH_BETA[6] - SH_BETA[1]*SH_BETA[4]*(SH_BETA[12] + 2.0f*q1*q2);
SK_BETA[3] = SH_BETA[5]*(2.0f*q0*q1 + 2.0f*q2*q3) + SH_BETA[1]*SH_BETA[4]*(2.0f*q0*q2 - 2.0f*q1*q3);
SK_BETA[4] = SH_BETA[5]*SH_BETA[10] - SH_BETA[1]*SH_BETA[4]*SH_BETA[11];
SK_BETA[5] = SH_BETA[5]*SH_BETA[8] - SH_BETA[1]*SH_BETA[4]*SH_BETA[9];
SK_BETA[6] = SH_BETA[5]*SH_BETA[11] + SH_BETA[1]*SH_BETA[4]*SH_BETA[10];
SK_BETA[7] = SH_BETA[5]*SH_BETA[9] + SH_BETA[1]*SH_BETA[4]*SH_BETA[8];
// Calculate Kalman gains
if (update_wind_only) {
// If we are getting aiding from other sources, then don't allow the sideslip fusion to affect the non-windspeed states
for (unsigned row = 0; row <= 21; row++) {
Kfusion[row] = 0.0f;
}
} else {
Kfusion[0] = SK_BETA[0]*(P(0,0)*SK_BETA[5] + P(0,1)*SK_BETA[4] - P(0,4)*SK_BETA[1] + P(0,5)*SK_BETA[2] + P(0,2)*SK_BETA[6] + P(0,6)*SK_BETA[3] - P(0,3)*SK_BETA[7] + P(0,22)*SK_BETA[1] - P(0,23)*SK_BETA[2]);
Kfusion[1] = SK_BETA[0]*(P(1,0)*SK_BETA[5] + P(1,1)*SK_BETA[4] - P(1,4)*SK_BETA[1] + P(1,5)*SK_BETA[2] + P(1,2)*SK_BETA[6] + P(1,6)*SK_BETA[3] - P(1,3)*SK_BETA[7] + P(1,22)*SK_BETA[1] - P(1,23)*SK_BETA[2]);
Kfusion[2] = SK_BETA[0]*(P(2,0)*SK_BETA[5] + P(2,1)*SK_BETA[4] - P(2,4)*SK_BETA[1] + P(2,5)*SK_BETA[2] + P(2,2)*SK_BETA[6] + P(2,6)*SK_BETA[3] - P(2,3)*SK_BETA[7] + P(2,22)*SK_BETA[1] - P(2,23)*SK_BETA[2]);
Kfusion[3] = SK_BETA[0]*(P(3,0)*SK_BETA[5] + P(3,1)*SK_BETA[4] - P(3,4)*SK_BETA[1] + P(3,5)*SK_BETA[2] + P(3,2)*SK_BETA[6] + P(3,6)*SK_BETA[3] - P(3,3)*SK_BETA[7] + P(3,22)*SK_BETA[1] - P(3,23)*SK_BETA[2]);
Kfusion[4] = SK_BETA[0]*(P(4,0)*SK_BETA[5] + P(4,1)*SK_BETA[4] - P(4,4)*SK_BETA[1] + P(4,5)*SK_BETA[2] + P(4,2)*SK_BETA[6] + P(4,6)*SK_BETA[3] - P(4,3)*SK_BETA[7] + P(4,22)*SK_BETA[1] - P(4,23)*SK_BETA[2]);
Kfusion[5] = SK_BETA[0]*(P(5,0)*SK_BETA[5] + P(5,1)*SK_BETA[4] - P(5,4)*SK_BETA[1] + P(5,5)*SK_BETA[2] + P(5,2)*SK_BETA[6] + P(5,6)*SK_BETA[3] - P(5,3)*SK_BETA[7] + P(5,22)*SK_BETA[1] - P(5,23)*SK_BETA[2]);
Kfusion[6] = SK_BETA[0]*(P(6,0)*SK_BETA[5] + P(6,1)*SK_BETA[4] - P(6,4)*SK_BETA[1] + P(6,5)*SK_BETA[2] + P(6,2)*SK_BETA[6] + P(6,6)*SK_BETA[3] - P(6,3)*SK_BETA[7] + P(6,22)*SK_BETA[1] - P(6,23)*SK_BETA[2]);
Kfusion[7] = SK_BETA[0]*(P(7,0)*SK_BETA[5] + P(7,1)*SK_BETA[4] - P(7,4)*SK_BETA[1] + P(7,5)*SK_BETA[2] + P(7,2)*SK_BETA[6] + P(7,6)*SK_BETA[3] - P(7,3)*SK_BETA[7] + P(7,22)*SK_BETA[1] - P(7,23)*SK_BETA[2]);
Kfusion[8] = SK_BETA[0]*(P(8,0)*SK_BETA[5] + P(8,1)*SK_BETA[4] - P(8,4)*SK_BETA[1] + P(8,5)*SK_BETA[2] + P(8,2)*SK_BETA[6] + P(8,6)*SK_BETA[3] - P(8,3)*SK_BETA[7] + P(8,22)*SK_BETA[1] - P(8,23)*SK_BETA[2]);
Kfusion[9] = SK_BETA[0]*(P(9,0)*SK_BETA[5] + P(9,1)*SK_BETA[4] - P(9,4)*SK_BETA[1] + P(9,5)*SK_BETA[2] + P(9,2)*SK_BETA[6] + P(9,6)*SK_BETA[3] - P(9,3)*SK_BETA[7] + P(9,22)*SK_BETA[1] - P(9,23)*SK_BETA[2]);
Kfusion[10] = SK_BETA[0]*(P(10,0)*SK_BETA[5] + P(10,1)*SK_BETA[4] - P(10,4)*SK_BETA[1] + P(10,5)*SK_BETA[2] + P(10,2)*SK_BETA[6] + P(10,6)*SK_BETA[3] - P(10,3)*SK_BETA[7] + P(10,22)*SK_BETA[1] - P(10,23)*SK_BETA[2]);
Kfusion[11] = SK_BETA[0]*(P(11,0)*SK_BETA[5] + P(11,1)*SK_BETA[4] - P(11,4)*SK_BETA[1] + P(11,5)*SK_BETA[2] + P(11,2)*SK_BETA[6] + P(11,6)*SK_BETA[3] - P(11,3)*SK_BETA[7] + P(11,22)*SK_BETA[1] - P(11,23)*SK_BETA[2]);
Kfusion[12] = SK_BETA[0]*(P(12,0)*SK_BETA[5] + P(12,1)*SK_BETA[4] - P(12,4)*SK_BETA[1] + P(12,5)*SK_BETA[2] + P(12,2)*SK_BETA[6] + P(12,6)*SK_BETA[3] - P(12,3)*SK_BETA[7] + P(12,22)*SK_BETA[1] - P(12,23)*SK_BETA[2]);
Kfusion[13] = SK_BETA[0]*(P(13,0)*SK_BETA[5] + P(13,1)*SK_BETA[4] - P(13,4)*SK_BETA[1] + P(13,5)*SK_BETA[2] + P(13,2)*SK_BETA[6] + P(13,6)*SK_BETA[3] - P(13,3)*SK_BETA[7] + P(13,22)*SK_BETA[1] - P(13,23)*SK_BETA[2]);
Kfusion[14] = SK_BETA[0]*(P(14,0)*SK_BETA[5] + P(14,1)*SK_BETA[4] - P(14,4)*SK_BETA[1] + P(14,5)*SK_BETA[2] + P(14,2)*SK_BETA[6] + P(14,6)*SK_BETA[3] - P(14,3)*SK_BETA[7] + P(14,22)*SK_BETA[1] - P(14,23)*SK_BETA[2]);
Kfusion[15] = SK_BETA[0]*(P(15,0)*SK_BETA[5] + P(15,1)*SK_BETA[4] - P(15,4)*SK_BETA[1] + P(15,5)*SK_BETA[2] + P(15,2)*SK_BETA[6] + P(15,6)*SK_BETA[3] - P(15,3)*SK_BETA[7] + P(15,22)*SK_BETA[1] - P(15,23)*SK_BETA[2]);
// Only update the magnetometer states if we are airborne and using 3D mag fusion
if (_control_status.flags.mag_3D && _control_status.flags.in_air) {
Kfusion[16] = SK_BETA[0]*(P(16,0)*SK_BETA[5] + P(16,1)*SK_BETA[4] - P(16,4)*SK_BETA[1] + P(16,5)*SK_BETA[2] + P(16,2)*SK_BETA[6] + P(16,6)*SK_BETA[3] - P(16,3)*SK_BETA[7] + P(16,22)*SK_BETA[1] - P(16,23)*SK_BETA[2]);
Kfusion[17] = SK_BETA[0]*(P(17,0)*SK_BETA[5] + P(17,1)*SK_BETA[4] - P(17,4)*SK_BETA[1] + P(17,5)*SK_BETA[2] + P(17,2)*SK_BETA[6] + P(17,6)*SK_BETA[3] - P(17,3)*SK_BETA[7] + P(17,22)*SK_BETA[1] - P(17,23)*SK_BETA[2]);
Kfusion[18] = SK_BETA[0]*(P(18,0)*SK_BETA[5] + P(18,1)*SK_BETA[4] - P(18,4)*SK_BETA[1] + P(18,5)*SK_BETA[2] + P(18,2)*SK_BETA[6] + P(18,6)*SK_BETA[3] - P(18,3)*SK_BETA[7] + P(18,22)*SK_BETA[1] - P(18,23)*SK_BETA[2]);
Kfusion[19] = SK_BETA[0]*(P(19,0)*SK_BETA[5] + P(19,1)*SK_BETA[4] - P(19,4)*SK_BETA[1] + P(19,5)*SK_BETA[2] + P(19,2)*SK_BETA[6] + P(19,6)*SK_BETA[3] - P(19,3)*SK_BETA[7] + P(19,22)*SK_BETA[1] - P(19,23)*SK_BETA[2]);
Kfusion[20] = SK_BETA[0]*(P(20,0)*SK_BETA[5] + P(20,1)*SK_BETA[4] - P(20,4)*SK_BETA[1] + P(20,5)*SK_BETA[2] + P(20,2)*SK_BETA[6] + P(20,6)*SK_BETA[3] - P(20,3)*SK_BETA[7] + P(20,22)*SK_BETA[1] - P(20,23)*SK_BETA[2]);
Kfusion[21] = SK_BETA[0]*(P(21,0)*SK_BETA[5] + P(21,1)*SK_BETA[4] - P(21,4)*SK_BETA[1] + P(21,5)*SK_BETA[2] + P(21,2)*SK_BETA[6] + P(21,6)*SK_BETA[3] - P(21,3)*SK_BETA[7] + P(21,22)*SK_BETA[1] - P(21,23)*SK_BETA[2]);
} else {
for (int i = 16; i <= 21; i++) {
Kfusion[i] = 0.0f;
}
}
}
Kfusion[22] = SK_BETA[0]*(P(22,0)*SK_BETA[5] + P(22,1)*SK_BETA[4] - P(22,4)*SK_BETA[1] + P(22,5)*SK_BETA[2] + P(22,2)*SK_BETA[6] + P(22,6)*SK_BETA[3] - P(22,3)*SK_BETA[7] + P(22,22)*SK_BETA[1] - P(22,23)*SK_BETA[2]);
Kfusion[23] = SK_BETA[0]*(P(23,0)*SK_BETA[5] + P(23,1)*SK_BETA[4] - P(23,4)*SK_BETA[1] + P(23,5)*SK_BETA[2] + P(23,2)*SK_BETA[6] + P(23,6)*SK_BETA[3] - P(23,3)*SK_BETA[7] + P(23,22)*SK_BETA[1] - P(23,23)*SK_BETA[2]);
// Calculate predicted sideslip angle and innovation using small angle approximation
_beta_innov = rel_wind(1) / rel_wind(0);
// Compute the ratio of innovation to gate size
_beta_test_ratio = sq(_beta_innov) / (sq(fmaxf(_params.beta_innov_gate, 1.0f)) * _beta_innov_var);
// if the innovation consistency check fails then don't fuse the sample and indicate bad beta health
if (_beta_test_ratio > 1.0f) {
_innov_check_fail_status.flags.reject_sideslip = true;
return;
} else {
_innov_check_fail_status.flags.reject_sideslip = false;
}
// synthetic sideslip measurement sample has passed check so record it
_time_last_beta_fuse = _time_last_imu;
// apply covariance correction via P_new = (I -K*H)*P
// first calculate expression for KHP
// then calculate P - KHP
matrix::SquareMatrix<float, _k_num_states> KHP;
float KH[9];
for (unsigned row = 0; row < _k_num_states; row++) {
KH[0] = Kfusion[row] * H_BETA[0];
KH[1] = Kfusion[row] * H_BETA[1];
KH[2] = Kfusion[row] * H_BETA[2];
KH[3] = Kfusion[row] * H_BETA[3];
KH[4] = Kfusion[row] * H_BETA[4];
KH[5] = Kfusion[row] * H_BETA[5];
KH[6] = Kfusion[row] * H_BETA[6];
KH[7] = Kfusion[row] * H_BETA[22];
KH[8] = Kfusion[row] * H_BETA[23];
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(4,column);
tmp += KH[5] * P(5,column);
tmp += KH[6] * P(6,column);
tmp += KH[7] * P(22,column);
tmp += KH[8] * P(23,column);
KHP(row,column) = tmp;
}
}
// if the covariance correction will result in a negative variance, then
// the covariance matrix is unhealthy and must be corrected
bool healthy = true;
_fault_status.flags.bad_sideslip = false;
for (int i = 0; i < _k_num_states; i++) {
if (P(i,i) < KHP(i,i)) {
// zero rows and columns
P.uncorrelateCovarianceSetVariance<1>(i, 0.0f);
//flag as unhealthy
healthy = false;
// update individual measurement health status
_fault_status.flags.bad_sideslip = true;
}
}
// only apply covariance and state corrections 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 matrix for gross errors
fixCovarianceErrors(true);
// apply the state corrections
fuse(Kfusion, _beta_innov);
}
}
}
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