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ardupilot/libraries/AP_NavEKF2/AP_NavEKF2_MagFusion.cpp

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/// -*- tab-width: 4; Mode: C++; c-basic-offset: 4; indent-tabs-mode: nil -*-
#include <AP_HAL/AP_HAL.h>
#if HAL_CPU_CLASS >= HAL_CPU_CLASS_150
#include "AP_NavEKF2.h"
#include "AP_NavEKF2_core.h"
#include <AP_AHRS/AP_AHRS.h>
#include <AP_Vehicle/AP_Vehicle.h>
#include <stdio.h>
extern const AP_HAL::HAL& hal;
/********************************************************
* RESET FUNCTIONS *
********************************************************/
// Control reset of yaw and magnetic field states
void NavEKF2_core::controlMagYawReset()
{
// Use a quaternion division to calcualte the delta quaternion between the rotation at the current and last time
Quaternion deltaQuat = stateStruct.quat / prevQuatMagReset;
prevQuatMagReset = stateStruct.quat;
// convert the quaternion to a rotation vector and find its length
Vector3f deltaRotVec;
deltaQuat.to_axis_angle(deltaRotVec);
float deltaRot = deltaRotVec.length();
// In-Flight reset for vehicle that cannot use a zero sideslip assumption
// Monitor the gain in height and reset the magnetic field states and heading when initial altitude has been gained
// This is done to prevent magnetic field distoration from steel roofs and adjacent structures causing bad earth field and initial yaw values
// Delay if rotated too far since the last check as rapid rotations will produce errors in the magnetic field states
if (!assume_zero_sideslip() && inFlight && !firstMagYawInit && (stateStruct.position.z - posDownAtTakeoff) < -5.0f && deltaRot < 0.1745f) {
firstMagYawInit = true;
// reset the timer used to prevent magnetometer fusion from affecting attitude until initial field learning is complete
magFuseTiltInhibit_ms = imuSampleTime_ms;
// Update the yaw angle and earth field states using the magnetic field measurements
Quaternion tempQuat;
Vector3f eulerAngles;
stateStruct.quat.to_euler(eulerAngles.x, eulerAngles.y, eulerAngles.z);
tempQuat = stateStruct.quat;
stateStruct.quat = calcQuatAndFieldStates(eulerAngles.x, eulerAngles.y);
// calculate the change in the quaternion state and apply it to the ouput history buffer
tempQuat = stateStruct.quat/tempQuat;
StoreQuatRotate(tempQuat);
}
// In-Flight reset for vehicles that can use a zero sideslip assumption (Planes)
// this is done to protect against unrecoverable heading alignment errors due to compass faults
if (assume_zero_sideslip() && inFlight && !firstMagYawInit) {
alignYawGPS();
firstMagYawInit = true;
}
// inhibit the 3-axis mag fusion from modifying the tilt states for the first few seconds after a mag field reset
// to allow the mag states to converge and prevent disturbances in roll and pitch.
if (imuSampleTime_ms - magFuseTiltInhibit_ms < 5000) {
magFuseTiltInhibit = true;
} else {
magFuseTiltInhibit = false;
}
}
// this function is used to do a forced alignment of the yaw angle to align with the horizontal velocity
// vector from GPS. It is used to align the yaw angle after launch or takeoff.
void NavEKF2_core::alignYawGPS()
{
// get quaternion from existing filter states and calculate roll, pitch and yaw angles
Vector3f eulerAngles;
stateStruct.quat.to_euler(eulerAngles.x, eulerAngles.y, eulerAngles.z);
if ((sq(gpsDataDelayed.vel.x) + sq(gpsDataDelayed.vel.y)) > 25.0f) {
// calculate course yaw angle
float velYaw = atan2f(stateStruct.velocity.y,stateStruct.velocity.x);
// calculate course yaw angle from GPS velocity
float gpsYaw = atan2f(gpsDataNew.vel.y,gpsDataNew.vel.x);
// Check the yaw angles for consistency
float yawErr = max(fabsf(wrap_PI(gpsYaw - velYaw)),max(fabsf(wrap_PI(gpsYaw - eulerAngles.z)),fabsf(wrap_PI(velYaw - eulerAngles.z))));
// If the angles disagree by more than 45 degrees and GPS innovations are large, we declare the magnetic yaw as bad
badMagYaw = ((yawErr > 0.7854f) && (velTestRatio > 1.0f));
// correct yaw angle using GPS ground course compass failed or if not previously aligned
if (badMagYaw) {
// calculate new filter quaternion states from Euler angles
stateStruct.quat.from_euler(eulerAngles.x, eulerAngles.y, gpsYaw);
// The correlations between attitude errors and positon and velocity errors in the covariance matrix
// are invalid becasue og the changed yaw angle, so reset the corresponding row and columns
zeroCols(P,0,2);
zeroRows(P,0,2);
// Set the initial attitude error covariances
P[1][1] = P[0][0] = sq(radians(5.0f));
P[2][2] = sq(radians(45.0f));
// reset tposition fusion timer to casue the states to be reset to the GPS on the next GPS fusion cycle
lastPosPassTime_ms = 0;
}
}
// reset the magnetometer field states - we could have got bad external interference when initialising on-ground
calcQuatAndFieldStates(eulerAngles.x, eulerAngles.y);
// We shoud retry the primary magnetoemter if previously switched or failed
magSelectIndex = 0;
allMagSensorsFailed = false;
}
/********************************************************
* FUSE MEASURED_DATA *
********************************************************/
// select fusion of magnetometer data
void NavEKF2_core::SelectMagFusion()
{
// start performance timer
hal.util->perf_begin(_perf_FuseMagnetometer);
// clear the flag that lets other processes know that the expensive magnetometer fusion operation has been perfomred on that time step
// used for load levelling
magFusePerformed = false;
// check for and read new magnetometer measurements
readMagData();
// If we are using the compass and the magnetometer has been unhealthy for too long we declare a timeout
if (magHealth) {
magTimeout = false;
lastHealthyMagTime_ms = imuSampleTime_ms;
} else if ((imuSampleTime_ms - lastHealthyMagTime_ms) > frontend->magFailTimeLimit_ms && use_compass()) {
magTimeout = true;
}
// check for availability of magnetometer data to fuse
magDataToFuse = RecallMag();
if (magDataToFuse) {
// Control reset of yaw and magnetic field states
controlMagYawReset();
}
// determine if conditions are right to start a new fusion cycle
// wait until the EKF time horizon catches up with the measurement
bool dataReady = (magDataToFuse && statesInitialised && use_compass() && yawAlignComplete);
if (dataReady) {
// If we haven't performed the first airborne magnetic field update or have inhibited magnetic field learning, then we use the simple method of declination to maintain heading
if(inhibitMagStates) {
fuseCompass();
// zero the test ratio output from the inactive 3-axis magneteometer fusion
magTestRatio.zero();
} else {
// if we are not doing aiding with earth relative observations (eg GPS) then the declination is
// maintained by fusing declination as a synthesised observation
if (PV_AidingMode != AID_ABSOLUTE || (imuSampleTime_ms - lastPosPassTime_ms) > 4000) {
FuseDeclination();
}
// fuse the three magnetometer componenents sequentially
for (mag_state.obsIndex = 0; mag_state.obsIndex <= 2; mag_state.obsIndex++) {
hal.util->perf_begin(_perf_test[0]);
FuseMagnetometer();
hal.util->perf_end(_perf_test[0]);
// don't continue fusion if unhealthy
if (!magHealth) {
break;
}
}
// zero the test ratio output from the inactive simple magnetometer yaw fusion
yawTestRatio = 0.0f;
}
}
// stop performance timer
hal.util->perf_end(_perf_FuseMagnetometer);
}
/*
* Fuse magnetometer measurements using explicit algebraic equations generated with Matlab symbolic toolbox.
* The script file used to generate these and other equations in this filter can be found here:
* https://github.com/priseborough/InertialNav/blob/master/derivations/RotationVectorAttitudeParameterisation/GenerateNavFilterEquations.m
*/
void NavEKF2_core::FuseMagnetometer()
{
hal.util->perf_begin(_perf_test[1]);
// declarations
ftype &q0 = mag_state.q0;
ftype &q1 = mag_state.q1;
ftype &q2 = mag_state.q2;
ftype &q3 = mag_state.q3;
ftype &magN = mag_state.magN;
ftype &magE = mag_state.magE;
ftype &magD = mag_state.magD;
ftype &magXbias = mag_state.magXbias;
ftype &magYbias = mag_state.magYbias;
ftype &magZbias = mag_state.magZbias;
uint8_t &obsIndex = mag_state.obsIndex;
Matrix3f &DCM = mag_state.DCM;
Vector3f &MagPred = mag_state.MagPred;
ftype &R_MAG = mag_state.R_MAG;
ftype *SH_MAG = &mag_state.SH_MAG[0];
Vector24 H_MAG;
Vector6 SK_MX;
Vector6 SK_MY;
Vector6 SK_MZ;
hal.util->perf_end(_perf_test[1]);
// perform sequential fusion of magnetometer measurements.
// this assumes that the errors in the different components are
// uncorrelated which is not true, however in the absence of covariance
// data fit is the only assumption we can make
// so we might as well take advantage of the computational efficiencies
// associated with sequential fusion
// calculate observation jacobians and Kalman gains
if (obsIndex == 0)
{
hal.util->perf_begin(_perf_test[2]);
// copy required states to local variable names
q0 = stateStruct.quat[0];
q1 = stateStruct.quat[1];
q2 = stateStruct.quat[2];
q3 = stateStruct.quat[3];
magN = stateStruct.earth_magfield[0];
magE = stateStruct.earth_magfield[1];
magD = stateStruct.earth_magfield[2];
magXbias = stateStruct.body_magfield[0];
magYbias = stateStruct.body_magfield[1];
magZbias = stateStruct.body_magfield[2];
// rotate predicted earth components into body axes and calculate
// predicted measurements
DCM[0][0] = q0*q0 + q1*q1 - q2*q2 - q3*q3;
DCM[0][1] = 2.0f*(q1*q2 + q0*q3);
DCM[0][2] = 2.0f*(q1*q3-q0*q2);
DCM[1][0] = 2.0f*(q1*q2 - q0*q3);
DCM[1][1] = q0*q0 - q1*q1 + q2*q2 - q3*q3;
DCM[1][2] = 2.0f*(q2*q3 + q0*q1);
DCM[2][0] = 2.0f*(q1*q3 + q0*q2);
DCM[2][1] = 2.0f*(q2*q3 - q0*q1);
DCM[2][2] = q0*q0 - q1*q1 - q2*q2 + q3*q3;
MagPred[0] = DCM[0][0]*magN + DCM[0][1]*magE + DCM[0][2]*magD + magXbias;
MagPred[1] = DCM[1][0]*magN + DCM[1][1]*magE + DCM[1][2]*magD + magYbias;
MagPred[2] = DCM[2][0]*magN + DCM[2][1]*magE + DCM[2][2]*magD + magZbias;
// calculate the measurement innovation for each axis
for (uint8_t i = 0; i<=2; i++) {
innovMag[i] = MagPred[i] - magDataDelayed.mag[i];
}
// scale magnetometer observation error with total angular rate to allow for timing errors
R_MAG = sq(constrain_float(frontend->_magNoise, 0.01f, 0.5f)) + sq(frontend->magVarRateScale*imuDataDelayed.delAng.length() / imuDataDelayed.delAngDT);
// calculate common expressions used to calculate observation jacobians an innovation variance for each component
SH_MAG[0] = sq(q0) - sq(q1) + sq(q2) - sq(q3);
SH_MAG[1] = sq(q0) + sq(q1) - sq(q2) - sq(q3);
SH_MAG[2] = sq(q0) - sq(q1) - sq(q2) + sq(q3);
SH_MAG[3] = 2.0f*q0*q1 + 2.0f*q2*q3;
SH_MAG[4] = 2.0f*q0*q3 + 2.0f*q1*q2;
SH_MAG[5] = 2.0f*q0*q2 + 2.0f*q1*q3;
SH_MAG[6] = magE*(2.0f*q0*q1 - 2.0f*q2*q3);
SH_MAG[7] = 2.0f*q1*q3 - 2.0f*q0*q2;
SH_MAG[8] = 2.0f*q0*q3;
// Calculate the innovation variance for each axis
// X axis
varInnovMag[0] = (P[19][19] + R_MAG - P[1][19]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[16][19]*SH_MAG[1] + P[17][19]*SH_MAG[4] + P[18][19]*SH_MAG[7] + P[2][19]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2)) - (magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5])*(P[19][1] - P[1][1]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[16][1]*SH_MAG[1] + P[17][1]*SH_MAG[4] + P[18][1]*SH_MAG[7] + P[2][1]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2))) + SH_MAG[1]*(P[19][16] - P[1][16]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[16][16]*SH_MAG[1] + P[17][16]*SH_MAG[4] + P[18][16]*SH_MAG[7] + P[2][16]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2))) + SH_MAG[4]*(P[19][17] - P[1][17]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[16][17]*SH_MAG[1] + P[17][17]*SH_MAG[4] + P[18][17]*SH_MAG[7] + P[2][17]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2))) + SH_MAG[7]*(P[19][18] - P[1][18]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[16][18]*SH_MAG[1] + P[17][18]*SH_MAG[4] + P[18][18]*SH_MAG[7] + P[2][18]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2))) + (magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2))*(P[19][2] - P[1][2]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[16][2]*SH_MAG[1] + P[17][2]*SH_MAG[4] + P[18][2]*SH_MAG[7] + P[2][2]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2))));
if (varInnovMag[0] >= R_MAG) {
faultStatus.bad_xmag = 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();
obsIndex = 1;
faultStatus.bad_xmag = true;
hal.util->perf_end(_perf_test[2]);
return;
}
// Y axis
varInnovMag[1] = (P[20][20] + R_MAG + P[0][20]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[17][20]*SH_MAG[0] + P[18][20]*SH_MAG[3] - (SH_MAG[8] - 2.0f*q1*q2)*(P[20][16] + P[0][16]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[17][16]*SH_MAG[0] + P[18][16]*SH_MAG[3] - P[2][16]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[16][16]*(SH_MAG[8] - 2.0f*q1*q2)) - P[2][20]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) + (magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5])*(P[20][0] + P[0][0]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[17][0]*SH_MAG[0] + P[18][0]*SH_MAG[3] - P[2][0]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[16][0]*(SH_MAG[8] - 2.0f*q1*q2)) + SH_MAG[0]*(P[20][17] + P[0][17]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[17][17]*SH_MAG[0] + P[18][17]*SH_MAG[3] - P[2][17]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[16][17]*(SH_MAG[8] - 2.0f*q1*q2)) + SH_MAG[3]*(P[20][18] + P[0][18]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[17][18]*SH_MAG[0] + P[18][18]*SH_MAG[3] - P[2][18]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[16][18]*(SH_MAG[8] - 2.0f*q1*q2)) - P[16][20]*(SH_MAG[8] - 2.0f*q1*q2) - (magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1])*(P[20][2] + P[0][2]*(magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5]) + P[17][2]*SH_MAG[0] + P[18][2]*SH_MAG[3] - P[2][2]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[16][2]*(SH_MAG[8] - 2.0f*q1*q2)));
if (varInnovMag[1] >= R_MAG) {
faultStatus.bad_ymag = 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();
obsIndex = 2;
faultStatus.bad_ymag = true;
hal.util->perf_end(_perf_test[2]);
return;
}
// Z axis
varInnovMag[2] = (P[21][21] + R_MAG + P[16][21]*SH_MAG[5] + P[18][21]*SH_MAG[2] - (2.0f*q0*q1 - 2.0f*q2*q3)*(P[21][17] + P[16][17]*SH_MAG[5] + P[18][17]*SH_MAG[2] - P[0][17]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2)) + P[1][17]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[17][17]*(2.0f*q0*q1 - 2.0f*q2*q3)) - P[0][21]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2)) + P[1][21]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) + SH_MAG[5]*(P[21][16] + P[16][16]*SH_MAG[5] + P[18][16]*SH_MAG[2] - P[0][16]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2)) + P[1][16]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[17][16]*(2.0f*q0*q1 - 2.0f*q2*q3)) + SH_MAG[2]*(P[21][18] + P[16][18]*SH_MAG[5] + P[18][18]*SH_MAG[2] - P[0][18]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2)) + P[1][18]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[17][18]*(2.0f*q0*q1 - 2.0f*q2*q3)) - (magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2))*(P[21][0] + P[16][0]*SH_MAG[5] + P[18][0]*SH_MAG[2] - P[0][0]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2)) + P[1][0]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[17][0]*(2.0f*q0*q1 - 2.0f*q2*q3)) - P[17][21]*(2.0f*q0*q1 - 2.0f*q2*q3) + (magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1])*(P[21][1] + P[16][1]*SH_MAG[5] + P[18][1]*SH_MAG[2] - P[0][1]*(magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2)) + P[1][1]*(magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1]) - P[17][1]*(2.0f*q0*q1 - 2.0f*q2*q3)));
if (varInnovMag[2] >= R_MAG) {
faultStatus.bad_zmag = 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();
obsIndex = 3;
faultStatus.bad_zmag = true;
hal.util->perf_end(_perf_test[2]);
return;
}
// calculate the innovation test ratios
for (uint8_t i = 0; i<=2; i++) {
magTestRatio[i] = sq(innovMag[i]) / (sq(max(frontend->_magInnovGate,1)) * varInnovMag[i]);
}
// check the last values from all components and set magnetometer health accordingly
magHealth = (magTestRatio[0] < 1.0f && magTestRatio[1] < 1.0f && magTestRatio[2] < 1.0f);
// if the magnetometer is unhealthy, do not proceed further
if (!magHealth) {
return;
}
for (uint8_t i = 0; i<=stateIndexLim; i++) H_MAG[i] = 0.0f;
H_MAG[1] = SH_MAG[6] - magD*SH_MAG[2] - magN*SH_MAG[5];
H_MAG[2] = magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2);
H_MAG[16] = SH_MAG[1];
H_MAG[17] = SH_MAG[4];
H_MAG[18] = SH_MAG[7];
H_MAG[19] = 1.0f;
// calculate Kalman gain
SK_MX[0] = 1.0f / varInnovMag[0];
SK_MX[1] = magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2);
SK_MX[2] = magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5];
SK_MX[3] = SH_MAG[7];
Kfusion[0] = SK_MX[0]*(P[0][19] + P[0][16]*SH_MAG[1] + P[0][17]*SH_MAG[4] - P[0][1]*SK_MX[2] + P[0][2]*SK_MX[1] + P[0][18]*SK_MX[3]);
Kfusion[1] = SK_MX[0]*(P[1][19] + P[1][16]*SH_MAG[1] + P[1][17]*SH_MAG[4] - P[1][1]*SK_MX[2] + P[1][2]*SK_MX[1] + P[1][18]*SK_MX[3]);
Kfusion[2] = SK_MX[0]*(P[2][19] + P[2][16]*SH_MAG[1] + P[2][17]*SH_MAG[4] - P[2][1]*SK_MX[2] + P[2][2]*SK_MX[1] + P[2][18]*SK_MX[3]);
Kfusion[3] = SK_MX[0]*(P[3][19] + P[3][16]*SH_MAG[1] + P[3][17]*SH_MAG[4] - P[3][1]*SK_MX[2] + P[3][2]*SK_MX[1] + P[3][18]*SK_MX[3]);
Kfusion[4] = SK_MX[0]*(P[4][19] + P[4][16]*SH_MAG[1] + P[4][17]*SH_MAG[4] - P[4][1]*SK_MX[2] + P[4][2]*SK_MX[1] + P[4][18]*SK_MX[3]);
Kfusion[5] = SK_MX[0]*(P[5][19] + P[5][16]*SH_MAG[1] + P[5][17]*SH_MAG[4] - P[5][1]*SK_MX[2] + P[5][2]*SK_MX[1] + P[5][18]*SK_MX[3]);
Kfusion[6] = SK_MX[0]*(P[6][19] + P[6][16]*SH_MAG[1] + P[6][17]*SH_MAG[4] - P[6][1]*SK_MX[2] + P[6][2]*SK_MX[1] + P[6][18]*SK_MX[3]);
Kfusion[7] = SK_MX[0]*(P[7][19] + P[7][16]*SH_MAG[1] + P[7][17]*SH_MAG[4] - P[7][1]*SK_MX[2] + P[7][2]*SK_MX[1] + P[7][18]*SK_MX[3]);
Kfusion[8] = SK_MX[0]*(P[8][19] + P[8][16]*SH_MAG[1] + P[8][17]*SH_MAG[4] - P[8][1]*SK_MX[2] + P[8][2]*SK_MX[1] + P[8][18]*SK_MX[3]);
Kfusion[9] = SK_MX[0]*(P[9][19] + P[9][16]*SH_MAG[1] + P[9][17]*SH_MAG[4] - P[9][1]*SK_MX[2] + P[9][2]*SK_MX[1] + P[9][18]*SK_MX[3]);
Kfusion[10] = SK_MX[0]*(P[10][19] + P[10][16]*SH_MAG[1] + P[10][17]*SH_MAG[4] - P[10][1]*SK_MX[2] + P[10][2]*SK_MX[1] + P[10][18]*SK_MX[3]);
Kfusion[11] = SK_MX[0]*(P[11][19] + P[11][16]*SH_MAG[1] + P[11][17]*SH_MAG[4] - P[11][1]*SK_MX[2] + P[11][2]*SK_MX[1] + P[11][18]*SK_MX[3]);
Kfusion[12] = SK_MX[0]*(P[12][19] + P[12][16]*SH_MAG[1] + P[12][17]*SH_MAG[4] - P[12][1]*SK_MX[2] + P[12][2]*SK_MX[1] + P[12][18]*SK_MX[3]);
Kfusion[13] = SK_MX[0]*(P[13][19] + P[13][16]*SH_MAG[1] + P[13][17]*SH_MAG[4] - P[13][1]*SK_MX[2] + P[13][2]*SK_MX[1] + P[13][18]*SK_MX[3]);
Kfusion[14] = SK_MX[0]*(P[14][19] + P[14][16]*SH_MAG[1] + P[14][17]*SH_MAG[4] - P[14][1]*SK_MX[2] + P[14][2]*SK_MX[1] + P[14][18]*SK_MX[3]);
Kfusion[15] = SK_MX[0]*(P[15][19] + P[15][16]*SH_MAG[1] + P[15][17]*SH_MAG[4] - P[15][1]*SK_MX[2] + P[15][2]*SK_MX[1] + P[15][18]*SK_MX[3]);
// end perf block
// zero Kalman gains to inhibit wind state estimation
if (!inhibitWindStates) {
Kfusion[22] = SK_MX[0]*(P[22][19] + P[22][16]*SH_MAG[1] + P[22][17]*SH_MAG[4] - P[22][1]*SK_MX[2] + P[22][2]*SK_MX[1] + P[22][18]*SK_MX[3]);
Kfusion[23] = SK_MX[0]*(P[23][19] + P[23][16]*SH_MAG[1] + P[23][17]*SH_MAG[4] - P[23][1]*SK_MX[2] + P[23][2]*SK_MX[1] + P[23][18]*SK_MX[3]);
} else {
Kfusion[22] = 0.0f;
Kfusion[23] = 0.0f;
}
// zero Kalman gains to inhibit magnetic field state estimation
if (!inhibitMagStates) {
Kfusion[16] = SK_MX[0]*(P[16][19] + P[16][16]*SH_MAG[1] + P[16][17]*SH_MAG[4] - P[16][1]*SK_MX[2] + P[16][2]*SK_MX[1] + P[16][18]*SK_MX[3]);
Kfusion[17] = SK_MX[0]*(P[17][19] + P[17][16]*SH_MAG[1] + P[17][17]*SH_MAG[4] - P[17][1]*SK_MX[2] + P[17][2]*SK_MX[1] + P[17][18]*SK_MX[3]);
Kfusion[18] = SK_MX[0]*(P[18][19] + P[18][16]*SH_MAG[1] + P[18][17]*SH_MAG[4] - P[18][1]*SK_MX[2] + P[18][2]*SK_MX[1] + P[18][18]*SK_MX[3]);
Kfusion[19] = SK_MX[0]*(P[19][19] + P[19][16]*SH_MAG[1] + P[19][17]*SH_MAG[4] - P[19][1]*SK_MX[2] + P[19][2]*SK_MX[1] + P[19][18]*SK_MX[3]);
Kfusion[20] = SK_MX[0]*(P[20][19] + P[20][16]*SH_MAG[1] + P[20][17]*SH_MAG[4] - P[20][1]*SK_MX[2] + P[20][2]*SK_MX[1] + P[20][18]*SK_MX[3]);
Kfusion[21] = SK_MX[0]*(P[21][19] + P[21][16]*SH_MAG[1] + P[21][17]*SH_MAG[4] - P[21][1]*SK_MX[2] + P[21][2]*SK_MX[1] + P[21][18]*SK_MX[3]);
} else {
for (uint8_t i=16; i<=21; i++) {
Kfusion[i] = 0.0f;
}
}
// reset the observation index to 0 (we start by fusing the X measurement)
obsIndex = 0;
// set flags to indicate to other processes that fusion has been performed and is required on the next frame
// this can be used by other fusion processes to avoid fusing on the same frame as this expensive step
magFusePerformed = true;
magFuseRequired = true;
hal.util->perf_end(_perf_test[2]);
}
else if (obsIndex == 1) // we are now fusing the Y measurement
{
hal.util->perf_begin(_perf_test[3]);
// calculate observation jacobians
for (uint8_t i = 0; i<=stateIndexLim; i++) H_MAG[i] = 0.0f;
H_MAG[0] = magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5];
H_MAG[2] = - magE*SH_MAG[4] - magD*SH_MAG[7] - magN*SH_MAG[1];
H_MAG[16] = 2.0f*q1*q2 - SH_MAG[8];
H_MAG[17] = SH_MAG[0];
H_MAG[18] = SH_MAG[3];
H_MAG[20] = 1.0f;
// calculate Kalman gain
SK_MY[0] = 1.0f / varInnovMag[1];
SK_MY[1] = magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1];
SK_MY[2] = magD*SH_MAG[2] - SH_MAG[6] + magN*SH_MAG[5];
SK_MY[3] = SH_MAG[8] - 2.0f*q1*q2;
Kfusion[0] = SK_MY[0]*(P[0][20] + P[0][17]*SH_MAG[0] + P[0][18]*SH_MAG[3] + P[0][0]*SK_MY[2] - P[0][2]*SK_MY[1] - P[0][16]*SK_MY[3]);
Kfusion[1] = SK_MY[0]*(P[1][20] + P[1][17]*SH_MAG[0] + P[1][18]*SH_MAG[3] + P[1][0]*SK_MY[2] - P[1][2]*SK_MY[1] - P[1][16]*SK_MY[3]);
Kfusion[2] = SK_MY[0]*(P[2][20] + P[2][17]*SH_MAG[0] + P[2][18]*SH_MAG[3] + P[2][0]*SK_MY[2] - P[2][2]*SK_MY[1] - P[2][16]*SK_MY[3]);
Kfusion[3] = SK_MY[0]*(P[3][20] + P[3][17]*SH_MAG[0] + P[3][18]*SH_MAG[3] + P[3][0]*SK_MY[2] - P[3][2]*SK_MY[1] - P[3][16]*SK_MY[3]);
Kfusion[4] = SK_MY[0]*(P[4][20] + P[4][17]*SH_MAG[0] + P[4][18]*SH_MAG[3] + P[4][0]*SK_MY[2] - P[4][2]*SK_MY[1] - P[4][16]*SK_MY[3]);
Kfusion[5] = SK_MY[0]*(P[5][20] + P[5][17]*SH_MAG[0] + P[5][18]*SH_MAG[3] + P[5][0]*SK_MY[2] - P[5][2]*SK_MY[1] - P[5][16]*SK_MY[3]);
Kfusion[6] = SK_MY[0]*(P[6][20] + P[6][17]*SH_MAG[0] + P[6][18]*SH_MAG[3] + P[6][0]*SK_MY[2] - P[6][2]*SK_MY[1] - P[6][16]*SK_MY[3]);
Kfusion[7] = SK_MY[0]*(P[7][20] + P[7][17]*SH_MAG[0] + P[7][18]*SH_MAG[3] + P[7][0]*SK_MY[2] - P[7][2]*SK_MY[1] - P[7][16]*SK_MY[3]);
Kfusion[8] = SK_MY[0]*(P[8][20] + P[8][17]*SH_MAG[0] + P[8][18]*SH_MAG[3] + P[8][0]*SK_MY[2] - P[8][2]*SK_MY[1] - P[8][16]*SK_MY[3]);
Kfusion[9] = SK_MY[0]*(P[9][20] + P[9][17]*SH_MAG[0] + P[9][18]*SH_MAG[3] + P[9][0]*SK_MY[2] - P[9][2]*SK_MY[1] - P[9][16]*SK_MY[3]);
Kfusion[10] = SK_MY[0]*(P[10][20] + P[10][17]*SH_MAG[0] + P[10][18]*SH_MAG[3] + P[10][0]*SK_MY[2] - P[10][2]*SK_MY[1] - P[10][16]*SK_MY[3]);
Kfusion[11] = SK_MY[0]*(P[11][20] + P[11][17]*SH_MAG[0] + P[11][18]*SH_MAG[3] + P[11][0]*SK_MY[2] - P[11][2]*SK_MY[1] - P[11][16]*SK_MY[3]);
Kfusion[12] = SK_MY[0]*(P[12][20] + P[12][17]*SH_MAG[0] + P[12][18]*SH_MAG[3] + P[12][0]*SK_MY[2] - P[12][2]*SK_MY[1] - P[12][16]*SK_MY[3]);
Kfusion[13] = SK_MY[0]*(P[13][20] + P[13][17]*SH_MAG[0] + P[13][18]*SH_MAG[3] + P[13][0]*SK_MY[2] - P[13][2]*SK_MY[1] - P[13][16]*SK_MY[3]);
Kfusion[14] = SK_MY[0]*(P[14][20] + P[14][17]*SH_MAG[0] + P[14][18]*SH_MAG[3] + P[14][0]*SK_MY[2] - P[14][2]*SK_MY[1] - P[14][16]*SK_MY[3]);
Kfusion[15] = SK_MY[0]*(P[15][20] + P[15][17]*SH_MAG[0] + P[15][18]*SH_MAG[3] + P[15][0]*SK_MY[2] - P[15][2]*SK_MY[1] - P[15][16]*SK_MY[3]);
// zero Kalman gains to inhibit wind state estimation
if (!inhibitWindStates) {
Kfusion[22] = SK_MY[0]*(P[22][20] + P[22][17]*SH_MAG[0] + P[22][18]*SH_MAG[3] + P[22][0]*SK_MY[2] - P[22][2]*SK_MY[1] - P[22][16]*SK_MY[3]);
Kfusion[23] = SK_MY[0]*(P[23][20] + P[23][17]*SH_MAG[0] + P[23][18]*SH_MAG[3] + P[23][0]*SK_MY[2] - P[23][2]*SK_MY[1] - P[23][16]*SK_MY[3]);
} else {
Kfusion[22] = 0.0f;
Kfusion[23] = 0.0f;
}
// zero Kalman gains to inhibit magnetic field state estimation
if (!inhibitMagStates) {
Kfusion[16] = SK_MY[0]*(P[16][20] + P[16][17]*SH_MAG[0] + P[16][18]*SH_MAG[3] + P[16][0]*SK_MY[2] - P[16][2]*SK_MY[1] - P[16][16]*SK_MY[3]);
Kfusion[17] = SK_MY[0]*(P[17][20] + P[17][17]*SH_MAG[0] + P[17][18]*SH_MAG[3] + P[17][0]*SK_MY[2] - P[17][2]*SK_MY[1] - P[17][16]*SK_MY[3]);
Kfusion[18] = SK_MY[0]*(P[18][20] + P[18][17]*SH_MAG[0] + P[18][18]*SH_MAG[3] + P[18][0]*SK_MY[2] - P[18][2]*SK_MY[1] - P[18][16]*SK_MY[3]);
Kfusion[19] = SK_MY[0]*(P[19][20] + P[19][17]*SH_MAG[0] + P[19][18]*SH_MAG[3] + P[19][0]*SK_MY[2] - P[19][2]*SK_MY[1] - P[19][16]*SK_MY[3]);
Kfusion[20] = SK_MY[0]*(P[20][20] + P[20][17]*SH_MAG[0] + P[20][18]*SH_MAG[3] + P[20][0]*SK_MY[2] - P[20][2]*SK_MY[1] - P[20][16]*SK_MY[3]);
Kfusion[21] = SK_MY[0]*(P[21][20] + P[21][17]*SH_MAG[0] + P[21][18]*SH_MAG[3] + P[21][0]*SK_MY[2] - P[21][2]*SK_MY[1] - P[21][16]*SK_MY[3]);
} else {
for (uint8_t i=16; i<=21; i++) {
Kfusion[i] = 0.0f;
}
}
// set flags to indicate to other processes that fusion has been performede and is required on the next frame
// this can be used by other fusion processes to avoid fusing on the same frame as this expensive step
magFusePerformed = true;
magFuseRequired = true;
hal.util->perf_end(_perf_test[3]);
}
else if (obsIndex == 2) // we are now fusing the Z measurement
{
hal.util->perf_begin(_perf_test[4]);
// calculate observation jacobians
for (uint8_t i = 0; i<=stateIndexLim; i++) H_MAG[i] = 0.0f;
H_MAG[0] = magN*(SH_MAG[8] - 2.0f*q1*q2) - magD*SH_MAG[3] - magE*SH_MAG[0];
H_MAG[1] = magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1];
H_MAG[16] = SH_MAG[5];
H_MAG[17] = 2.0f*q2*q3 - 2.0f*q0*q1;
H_MAG[18] = SH_MAG[2];
H_MAG[21] = 1.0f;
// calculate Kalman gain
SK_MZ[0] = 1.0f / varInnovMag[2];
SK_MZ[1] = magE*SH_MAG[0] + magD*SH_MAG[3] - magN*(SH_MAG[8] - 2.0f*q1*q2);
SK_MZ[2] = magE*SH_MAG[4] + magD*SH_MAG[7] + magN*SH_MAG[1];
SK_MZ[3] = 2.0f*q0*q1 - 2.0f*q2*q3;
Kfusion[0] = SK_MZ[0]*(P[0][21] + P[0][18]*SH_MAG[2] + P[0][16]*SH_MAG[5] - P[0][0]*SK_MZ[1] + P[0][1]*SK_MZ[2] - P[0][17]*SK_MZ[3]);
Kfusion[1] = SK_MZ[0]*(P[1][21] + P[1][18]*SH_MAG[2] + P[1][16]*SH_MAG[5] - P[1][0]*SK_MZ[1] + P[1][1]*SK_MZ[2] - P[1][17]*SK_MZ[3]);
Kfusion[2] = SK_MZ[0]*(P[2][21] + P[2][18]*SH_MAG[2] + P[2][16]*SH_MAG[5] - P[2][0]*SK_MZ[1] + P[2][1]*SK_MZ[2] - P[2][17]*SK_MZ[3]);
Kfusion[3] = SK_MZ[0]*(P[3][21] + P[3][18]*SH_MAG[2] + P[3][16]*SH_MAG[5] - P[3][0]*SK_MZ[1] + P[3][1]*SK_MZ[2] - P[3][17]*SK_MZ[3]);
Kfusion[4] = SK_MZ[0]*(P[4][21] + P[4][18]*SH_MAG[2] + P[4][16]*SH_MAG[5] - P[4][0]*SK_MZ[1] + P[4][1]*SK_MZ[2] - P[4][17]*SK_MZ[3]);
Kfusion[5] = SK_MZ[0]*(P[5][21] + P[5][18]*SH_MAG[2] + P[5][16]*SH_MAG[5] - P[5][0]*SK_MZ[1] + P[5][1]*SK_MZ[2] - P[5][17]*SK_MZ[3]);
Kfusion[6] = SK_MZ[0]*(P[6][21] + P[6][18]*SH_MAG[2] + P[6][16]*SH_MAG[5] - P[6][0]*SK_MZ[1] + P[6][1]*SK_MZ[2] - P[6][17]*SK_MZ[3]);
Kfusion[7] = SK_MZ[0]*(P[7][21] + P[7][18]*SH_MAG[2] + P[7][16]*SH_MAG[5] - P[7][0]*SK_MZ[1] + P[7][1]*SK_MZ[2] - P[7][17]*SK_MZ[3]);
Kfusion[8] = SK_MZ[0]*(P[8][21] + P[8][18]*SH_MAG[2] + P[8][16]*SH_MAG[5] - P[8][0]*SK_MZ[1] + P[8][1]*SK_MZ[2] - P[8][17]*SK_MZ[3]);
Kfusion[9] = SK_MZ[0]*(P[9][21] + P[9][18]*SH_MAG[2] + P[9][16]*SH_MAG[5] - P[9][0]*SK_MZ[1] + P[9][1]*SK_MZ[2] - P[9][17]*SK_MZ[3]);
Kfusion[10] = SK_MZ[0]*(P[10][21] + P[10][18]*SH_MAG[2] + P[10][16]*SH_MAG[5] - P[10][0]*SK_MZ[1] + P[10][1]*SK_MZ[2] - P[10][17]*SK_MZ[3]);
Kfusion[11] = SK_MZ[0]*(P[11][21] + P[11][18]*SH_MAG[2] + P[11][16]*SH_MAG[5] - P[11][0]*SK_MZ[1] + P[11][1]*SK_MZ[2] - P[11][17]*SK_MZ[3]);
Kfusion[12] = SK_MZ[0]*(P[12][21] + P[12][18]*SH_MAG[2] + P[12][16]*SH_MAG[5] - P[12][0]*SK_MZ[1] + P[12][1]*SK_MZ[2] - P[12][17]*SK_MZ[3]);
Kfusion[13] = SK_MZ[0]*(P[13][21] + P[13][18]*SH_MAG[2] + P[13][16]*SH_MAG[5] - P[13][0]*SK_MZ[1] + P[13][1]*SK_MZ[2] - P[13][17]*SK_MZ[3]);
Kfusion[14] = SK_MZ[0]*(P[14][21] + P[14][18]*SH_MAG[2] + P[14][16]*SH_MAG[5] - P[14][0]*SK_MZ[1] + P[14][1]*SK_MZ[2] - P[14][17]*SK_MZ[3]);
Kfusion[15] = SK_MZ[0]*(P[15][21] + P[15][18]*SH_MAG[2] + P[15][16]*SH_MAG[5] - P[15][0]*SK_MZ[1] + P[15][1]*SK_MZ[2] - P[15][17]*SK_MZ[3]);
// zero Kalman gains to inhibit wind state estimation
if (!inhibitWindStates) {
Kfusion[22] = SK_MZ[0]*(P[22][21] + P[22][18]*SH_MAG[2] + P[22][16]*SH_MAG[5] - P[22][0]*SK_MZ[1] + P[22][1]*SK_MZ[2] - P[22][17]*SK_MZ[3]);
Kfusion[23] = SK_MZ[0]*(P[23][21] + P[23][18]*SH_MAG[2] + P[23][16]*SH_MAG[5] - P[23][0]*SK_MZ[1] + P[23][1]*SK_MZ[2] - P[23][17]*SK_MZ[3]);
} else {
Kfusion[22] = 0.0f;
Kfusion[23] = 0.0f;
}
// zero Kalman gains to inhibit magnetic field state estimation
if (!inhibitMagStates) {
Kfusion[16] = SK_MZ[0]*(P[16][21] + P[16][18]*SH_MAG[2] + P[16][16]*SH_MAG[5] - P[16][0]*SK_MZ[1] + P[16][1]*SK_MZ[2] - P[16][17]*SK_MZ[3]);
Kfusion[17] = SK_MZ[0]*(P[17][21] + P[17][18]*SH_MAG[2] + P[17][16]*SH_MAG[5] - P[17][0]*SK_MZ[1] + P[17][1]*SK_MZ[2] - P[17][17]*SK_MZ[3]);
Kfusion[18] = SK_MZ[0]*(P[18][21] + P[18][18]*SH_MAG[2] + P[18][16]*SH_MAG[5] - P[18][0]*SK_MZ[1] + P[18][1]*SK_MZ[2] - P[18][17]*SK_MZ[3]);
Kfusion[19] = SK_MZ[0]*(P[19][21] + P[19][18]*SH_MAG[2] + P[19][16]*SH_MAG[5] - P[19][0]*SK_MZ[1] + P[19][1]*SK_MZ[2] - P[19][17]*SK_MZ[3]);
Kfusion[20] = SK_MZ[0]*(P[20][21] + P[20][18]*SH_MAG[2] + P[20][16]*SH_MAG[5] - P[20][0]*SK_MZ[1] + P[20][1]*SK_MZ[2] - P[20][17]*SK_MZ[3]);
Kfusion[21] = SK_MZ[0]*(P[21][21] + P[21][18]*SH_MAG[2] + P[21][16]*SH_MAG[5] - P[21][0]*SK_MZ[1] + P[21][1]*SK_MZ[2] - P[21][17]*SK_MZ[3]);
} else {
for (uint8_t i=16; i<=21; i++) {
Kfusion[i] = 0.0f;
}
}
// set flags to indicate to other processes that fusion has been performede and is required on the next frame
// this can be used by other fusion processes to avoid fusing on the same frame as this expensive step
magFusePerformed = true;
magFuseRequired = false;
hal.util->perf_end(_perf_test[4]);
}
hal.util->perf_begin(_perf_test[5]);
// 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] * innovMag[obsIndex];
}
// Inhibit corrections to tilt if requested. This enables mag states to settle after a reset without causing sudden changes in roll and pitch
if (magFuseTiltInhibit) {
stateStruct.angErr.x = 0.0f;
stateStruct.angErr.y = 0.0f;
}
// 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);
// 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<=2; j++) {
KH[i][j] = Kfusion[i] * H_MAG[j];
}
for (unsigned j = 3; j<=15; j++) {
KH[i][j] = 0.0f;
}
for (unsigned j = 16; j<=21; j++) {
KH[i][j] = Kfusion[i] * H_MAG[j];
}
for (unsigned j = 22; j<=23; j++) {
KH[i][j] = 0.0f;
}
}
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][16] * P[16][j];
res += KH[i][17] * P[17][j];
res += KH[i][18] * P[18][j];
res += KH[i][19] * P[19][j];
res += KH[i][20] * P[20][j];
res += KH[i][21] * P[21][j];
KHP[i][j] = res;
}
}
for (unsigned i = 0; i<=stateIndexLim; i++) {
for (unsigned j = 0; j<=stateIndexLim; j++) {
P[i][j] = P[i][j] - KHP[i][j];
}
}
// force the covariance matrix to be symmetrical and limit the variances to prevent
// ill-condiioning.
ForceSymmetry();
ConstrainVariances();
hal.util->perf_end(_perf_test[4]);
}
/*
* Fuse compass measurements using explicit algebraic equations generated with Matlab symbolic toolbox.
* The script file used to generate these and other equations in this filter can be found here:
* https://github.com/priseborough/InertialNav/blob/master/derivations/RotationVectorAttitudeParameterisation/GenerateNavFilterEquations.m
* This fusion method only modifies the orientation, does not require use of the magnetic field states and is computatonally cheaper.
* It is suitable for use when the external magnetic field environment is disturbed (eg close to metal structures, on ground).
* It is not as robust to magneometer failures.
*/
void NavEKF2_core::fuseCompass()
{
float q0 = stateStruct.quat[0];
float q1 = stateStruct.quat[1];
float q2 = stateStruct.quat[2];
float q3 = stateStruct.quat[3];
float magX = magDataDelayed.mag.x;
float magY = magDataDelayed.mag.y;
float magZ = magDataDelayed.mag.z;
// compass measurement error variance (rad^2)
const float R_MAG = 3e-2f;
// Calculate observation Jacobian
float t2 = q0*q0;
float t3 = q1*q1;
float t4 = q2*q2;
float t5 = q3*q3;
float t6 = q0*q2*2.0f;
float t7 = q1*q3*2.0f;
float t8 = t6+t7;
float t9 = q0*q3*2.0f;
float t13 = q1*q2*2.0f;
float t10 = t9-t13;
float t11 = t2+t3-t4-t5;
float t12 = magX*t11;
float t14 = magZ*t8;
float t19 = magY*t10;
float t15 = t12+t14-t19;
float t16 = t2-t3+t4-t5;
float t17 = q0*q1*2.0f;
float t24 = q2*q3*2.0f;
float t18 = t17-t24;
float t20 = 1.0f/t15;
float t21 = magY*t16;
float t22 = t9+t13;
float t23 = magX*t22;
float t28 = magZ*t18;
float t25 = t21+t23-t28;
float t29 = t20*t25;
float t26 = tan(t29);
float t27 = 1.0f/(t15*t15);
float t30 = t26*t26;
float t31 = t30+1.0f;
float H_MAG[3];
H_MAG[0] = -t31*(t20*(magZ*t16+magY*t18)+t25*t27*(magY*t8+magZ*t10));
H_MAG[1] = t31*(t20*(magX*t18+magZ*t22)+t25*t27*(magX*t8-magZ*t11));
H_MAG[2] = t31*(t20*(magX*t16-magY*t22)+t25*t27*(magX*t10+magY*t11));
// Calculate innovation variance and Kalman gains, taking advantage of the fact that only the first 3 elements in H are non zero
float PH[3];
float varInnov = R_MAG;
for (uint8_t rowIndex=0; rowIndex<=2; rowIndex++) {
PH[rowIndex] = 0.0f;
for (uint8_t colIndex=0; colIndex<=2; colIndex++) {
PH[rowIndex] += P[rowIndex][colIndex]*H_MAG[colIndex];
}
varInnov += H_MAG[rowIndex]*PH[rowIndex];
}
float varInnovInv;
if (varInnov >= R_MAG) {
varInnovInv = 1.0f / varInnov;
// All three magnetometer components are used in this measurement, so we output health status on three axes
faultStatus.bad_xmag = false;
faultStatus.bad_ymag = false;
faultStatus.bad_zmag = 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();
// All three magnetometer components are used in this measurement, so we output health status on three axes
faultStatus.bad_xmag = true;
faultStatus.bad_ymag = true;
faultStatus.bad_zmag = true;
return;
}
for (uint8_t rowIndex=0; rowIndex<=stateIndexLim; rowIndex++) {
Kfusion[rowIndex] = 0.0f;
for (uint8_t colIndex=0; colIndex<=2; colIndex++) {
Kfusion[rowIndex] += P[rowIndex][colIndex]*H_MAG[colIndex];
}
Kfusion[rowIndex] *= varInnovInv;
}
// Calculate the innovation
float innovation = calcMagHeadingInnov();
// Copy raw value to output variable used for data logging
innovYaw = innovation;
// limit the innovation so that initial corrections are not too large
if (innovation > 0.5f) {
innovation = 0.5f;
} else if (innovation < -0.5f) {
innovation = -0.5f;
}
// calculate the innovation test ratio
yawTestRatio = sq(innovation) / (sq(max(frontend->_magInnovGate,1)) * varInnov);
// Declare the magnetometer unhealthy if the innovation test fails
if (yawTestRatio > 1.0f) {
magHealth = false;
// On the ground a large innovation could be due to large initial gyro bias or magnetic interference from nearby objects
// If we are flying, then it is more likely due to a magnetometer fault and we should not fuse the data
if (inFlight) {
return;
}
} else {
magHealth = true;
}
// correct the state vector
stateStruct.angErr.zero();
for (uint8_t i=0; i<=stateIndexLim; i++) {
statesArray[i] -= Kfusion[i] * innovation;
}
// 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);
// correct the covariance using P = P - K*H*P taking advantage of the fact that only the first 3 elements in H are non zero
float HP[24];
for (uint8_t colIndex=0; colIndex<=stateIndexLim; colIndex++) {
HP[colIndex] = 0.0f;
for (uint8_t rowIndex=0; rowIndex<=2; rowIndex++) {
HP[colIndex] += H_MAG[rowIndex]*P[rowIndex][colIndex];
}
}
for (uint8_t rowIndex=0; rowIndex<=stateIndexLim; rowIndex++) {
for (uint8_t colIndex=0; colIndex<=stateIndexLim; colIndex++) {
P[rowIndex][colIndex] -= Kfusion[rowIndex] * HP[colIndex];
}
}
// force the covariance matrix to be symmetrical and limit the variances to prevent
// ill-condiioning.
ForceSymmetry();
ConstrainVariances();
}
/*
* Fuse declination angle using explicit algebraic equations generated with Matlab symbolic toolbox.
* The script file used to generate these and other equations in this filter can be found here:
* https://github.com/priseborough/InertialNav/blob/master/derivations/RotationVectorAttitudeParameterisation/GenerateNavFilterEquations.m
* This is used to prevent the declination of the EKF earth field states from drifting during operation without GPS
* or some other absolute position or velocity reference
*/
void NavEKF2_core::FuseDeclination()
{
// declination error variance (rad^2)
const float R_DECL = 1e-2f;
// copy required states to local variables
float magN = stateStruct.earth_magfield.x;
float magE = stateStruct.earth_magfield.y;
// prevent bad earth field states from causing numerical errors or exceptions
if (magN < 1e-3f) {
return;
}
// Calculate observation Jacobian and Kalman gains
float t2 = 1.0f/magN;
float t4 = magE*t2;
float t3 = tanf(t4);
float t5 = t3*t3;
float t6 = t5+1.0f;
float t7 = 1.0f/(magN*magN);
float t8 = P[17][17]*t2*t6;
float t15 = P[16][17]*magE*t6*t7;
float t9 = t8-t15;
float t10 = t2*t6*t9;
float t11 = P[17][16]*t2*t6;
float t16 = P[16][16]*magE*t6*t7;
float t12 = t11-t16;
float t17 = magE*t6*t7*t12;
float t13 = R_DECL+t10-t17;
float t14 = 1.0f/t13;
float t18 = magE;
float t19 = magN;
float t21 = 1.0f/t19;
float t22 = t18*t21;
float t20 = tanf(t22);
float t23 = t20*t20;
float t24 = t23+1.0f;
float H_MAG[24];
H_MAG[16] = -t18*1.0f/(t19*t19)*t24;
H_MAG[17] = t21*t24;
for (uint8_t i=0; i<=15; i++) {
Kfusion[i] = t14*(P[i][17]*t2*t6-P[i][16]*magE*t6*t7);
}
Kfusion[16] = -t14*(t16-P[16][17]*t2*t6);
Kfusion[17] = t14*(t8-P[17][16]*magE*t6*t7);
for (uint8_t i=17; i<=23; i++) {
Kfusion[i] = t14*(P[i][17]*t2*t6-P[i][16]*magE*t6*t7);
}
// get the magnetic declination
float magDecAng = use_compass() ? _ahrs->get_compass()->get_declination() : 0;
// Calculate the innovation
float innovation = atanf(t4) - magDecAng;
// limit the innovation to protect against data errors
if (innovation > 0.5f) {
innovation = 0.5f;
} else if (innovation < -0.5f) {
innovation = -0.5f;
}
// 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] * innovation;
}
// 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);
// 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<=15; j++) {
KH[i][j] = 0.0f;
}
KH[i][16] = Kfusion[i] * H_MAG[16];
KH[i][17] = Kfusion[i] * H_MAG[17];
for (unsigned j = 18; j<=23; j++) {
KH[i][j] = 0.0f;
}
}
for (unsigned j = 0; j<=stateIndexLim; j++) {
for (unsigned i = 0; i<=stateIndexLim; i++) {
KHP[i][j] = KH[i][16] * P[16][j] + KH[i][17] * P[17][j];
}
}
for (unsigned i = 0; i<=stateIndexLim; i++) {
for (unsigned j = 0; j<=stateIndexLim; j++) {
P[i][j] = P[i][j] - KHP[i][j];
}
}
// force the covariance matrix to be symmetrical and limit the variances to prevent
// ill-condiioning.
ForceSymmetry();
ConstrainVariances();
}
// Calculate magnetic heading innovation
float NavEKF2_core::calcMagHeadingInnov()
{
// rotate predicted earth components into body axes and calculate
// predicted measurements
Matrix3f Tbn_temp;
stateStruct.quat.rotation_matrix(Tbn_temp);
Vector3f magMeasNED = Tbn_temp*magDataDelayed.mag;
// calculate the innovation where the predicted measurement is the angle wrt magnetic north of the horizontal component of the measured field
float innovation = atan2f(magMeasNED.y,magMeasNED.x) - _ahrs->get_compass()->get_declination();
// wrap the innovation so it sits on the range from +-pi
if (innovation > M_PI_F) {
innovation = innovation - 2*M_PI_F;
} else if (innovation < -M_PI_F) {
innovation = innovation + 2*M_PI_F;
}
// Unwrap so that a large yaw gyro bias offset that causes the heading to wrap does not lead to continual uncontrolled heading drift
if (innovation - lastInnovation > M_PI_F) {
// Angle has wrapped in the positive direction to subtract an additional 2*Pi
innovationIncrement -= 2*M_PI_F;
} else if (innovation -innovationIncrement < -M_PI_F) {
// Angle has wrapped in the negative direction so add an additional 2*Pi
innovationIncrement += 2*M_PI_F;
}
lastInnovation = innovation;
return innovation + innovationIncrement;
}
/********************************************************
* MISC FUNCTIONS *
********************************************************/
// align the NE earth magnetic field states with the published declination
void NavEKF2_core::alignMagStateDeclination()
{
// get the magnetic declination
float magDecAng = use_compass() ? _ahrs->get_compass()->get_declination() : 0;
// rotate the NE values so that the declination matches the published value
Vector3f initMagNED = stateStruct.earth_magfield;
float magLengthNE = pythagorous2(initMagNED.x,initMagNED.y);
stateStruct.earth_magfield.x = magLengthNE * cosf(magDecAng);
stateStruct.earth_magfield.y = magLengthNE * sinf(magDecAng);
}
#endif // HAL_CPU_CLASS
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