mirror of https://github.com/ArduPilot/ardupilot
1200 lines
63 KiB
C++
1200 lines
63 KiB
C++
#include <AP_HAL/AP_HAL.h>
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#if HAL_CPU_CLASS >= HAL_CPU_CLASS_150
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#include "AP_NavEKF3.h"
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#include "AP_NavEKF3_core.h"
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#include <AP_AHRS/AP_AHRS.h>
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#include <AP_Vehicle/AP_Vehicle.h>
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#include <GCS_MAVLink/GCS.h>
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extern const AP_HAL::HAL& hal;
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/********************************************************
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* RESET FUNCTIONS *
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********************************************************/
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// Control reset of yaw and magnetic field states
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void NavEKF3_core::controlMagYawReset()
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{
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// Vehicles that can use a zero sideslip assumption (Planes) are a special case
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// They can use the GPS velocity to recover from bad initial compass data
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// This allows recovery for heading alignment errors due to compass faults
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if (assume_zero_sideslip() && !finalInflightYawInit && inFlight ) {
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gpsYawResetRequest = true;
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return;
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} else {
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gpsYawResetRequest = false;
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}
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// Quaternion and delta rotation vector that are re-used for different calculations
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Vector3f deltaRotVecTemp;
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Quaternion deltaQuatTemp;
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bool flightResetAllowed = false;
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bool initialResetAllowed = false;
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if (!finalInflightYawInit) {
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// Use a quaternion division to calculate the delta quaternion between the rotation at the current and last time
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deltaQuatTemp = stateStruct.quat / prevQuatMagReset;
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prevQuatMagReset = stateStruct.quat;
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// convert the quaternion to a rotation vector and find its length
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deltaQuatTemp.to_axis_angle(deltaRotVecTemp);
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// check if the spin rate is OK - high spin rates can cause angular alignment errors
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bool angRateOK = deltaRotVecTemp.length() < 0.1745f;
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initialResetAllowed = angRateOK;
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flightResetAllowed = angRateOK && !onGround;
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}
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// Check if conditions for a interim or final yaw/mag reset are met
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bool finalResetRequest = false;
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bool interimResetRequest = false;
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if (flightResetAllowed && !assume_zero_sideslip()) {
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// check that we have reached a height where ground magnetic interference effects are insignificant
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// and can perform a final reset of the yaw and field states
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finalResetRequest = (stateStruct.position.z - posDownAtTakeoff) < -EKF3_MAG_FINAL_RESET_ALT;
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// check for increasing height
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bool hgtIncreasing = (posDownAtLastMagReset-stateStruct.position.z) > 0.5f;
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float yawInnovIncrease = fabsf(innovYaw) - fabsf(yawInnovAtLastMagReset);
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// check for increasing yaw innovations
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bool yawInnovIncreasing = yawInnovIncrease > 0.25f;
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// check that the yaw innovations haven't been caused by a large change in attitude
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deltaQuatTemp = quatAtLastMagReset / stateStruct.quat;
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deltaQuatTemp.to_axis_angle(deltaRotVecTemp);
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bool largeAngleChange = deltaRotVecTemp.length() > yawInnovIncrease;
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// if yaw innovations and height have increased and we haven't rotated much
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// then we are climbing away from a ground based magnetic anomaly and need to reset
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interimResetRequest = hgtIncreasing && yawInnovIncreasing && !largeAngleChange;
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}
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// an initial reset is required if we have not yet aligned the yaw angle
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bool initialResetRequest = initialResetAllowed && !yawAlignComplete;
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// a combined yaw angle and magnetic field reset can be initiated by:
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magYawResetRequest = magYawResetRequest || // an external request
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initialResetRequest || // an initial alignment performed by all vehicle types using magnetometer
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interimResetRequest || // an interim alignment required to recover from ground based magnetic anomaly
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finalResetRequest; // the final reset when we have acheived enough height to be in stable magnetic field environment
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// Perform a reset of magnetic field states and reset yaw to corrected magnetic heading
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if (magYawResetRequest || magStateResetRequest) {
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// get the euler angles from the current state estimate
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Vector3f eulerAngles;
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stateStruct.quat.to_euler(eulerAngles.x, eulerAngles.y, eulerAngles.z);
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// Use the Euler angles and magnetometer measurement to update the magnetic field states
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// and get an updated quaternion
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Quaternion newQuat = calcQuatAndFieldStates(eulerAngles.x, eulerAngles.y);
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// if a yaw reset has been requested, apply the updated quaternion to the current state
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if (magYawResetRequest) {
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// previous value used to calculate a reset delta
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Quaternion prevQuat = stateStruct.quat;
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// calculate the variance for the rotation estimate expressed as a rotation vector
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// this will be used later to reset the quaternion state covariances
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Vector3f angleErrVarVec = calcRotVecVariances();
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// update the quaternion states using the new yaw angle
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stateStruct.quat = newQuat;
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// update the yaw angle variance using the variance of the measurement
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angleErrVarVec.z = sq(MAX(frontend->_yawNoise, 1.0e-2f));
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// reset the quaternion covariances using the rotation vector variances
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initialiseQuatCovariances(angleErrVarVec);
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// calculate the change in the quaternion state and apply it to the ouput history buffer
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prevQuat = stateStruct.quat/prevQuat;
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StoreQuatRotate(prevQuat);
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// send initial alignment status to console
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if (!yawAlignComplete) {
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gcs().send_text(MAV_SEVERITY_INFO, "EKF3 IMU%u initial yaw alignment complete",(unsigned)imu_index);
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}
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// send in-flight yaw alignment status to console
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if (finalResetRequest) {
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gcs().send_text(MAV_SEVERITY_INFO, "EKF3 IMU%u in-flight yaw alignment complete",(unsigned)imu_index);
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} else if (interimResetRequest) {
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gcs().send_text(MAV_SEVERITY_WARNING, "EKF3 IMU%u ground mag anomaly, yaw re-aligned",(unsigned)imu_index);
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}
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// update the yaw reset completed status
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recordYawReset();
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// clear the yaw reset request flag
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magYawResetRequest = false;
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// clear the complete flags if an interim reset has been performed to allow subsequent
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// and final reset to occur
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if (interimResetRequest) {
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finalInflightYawInit = false;
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finalInflightMagInit = false;
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}
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}
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}
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}
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// this function is used to do a forced re-alignment of the yaw angle to align with the horizontal velocity
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// vector from GPS. It is used to align the yaw angle after launch or takeoff.
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void NavEKF3_core::realignYawGPS()
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{
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// get quaternion from existing filter states and calculate roll, pitch and yaw angles
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Vector3f eulerAngles;
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stateStruct.quat.to_euler(eulerAngles.x, eulerAngles.y, eulerAngles.z);
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if ((sq(gpsDataDelayed.vel.x) + sq(gpsDataDelayed.vel.y)) > 25.0f) {
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// calculate course yaw angle
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float velYaw = atan2f(stateStruct.velocity.y,stateStruct.velocity.x);
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// calculate course yaw angle from GPS velocity
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float gpsYaw = atan2f(gpsDataDelayed.vel.y,gpsDataDelayed.vel.x);
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// Check the yaw angles for consistency
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float yawErr = MAX(fabsf(wrap_PI(gpsYaw - velYaw)),fabsf(wrap_PI(gpsYaw - eulerAngles.z)));
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// If the angles disagree by more than 45 degrees and GPS innovations are large or no previous yaw alignment, we declare the magnetic yaw as bad
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badMagYaw = ((yawErr > 0.7854f) && (velTestRatio > 1.0f) && (PV_AidingMode == AID_ABSOLUTE)) || !yawAlignComplete;
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// correct yaw angle using GPS ground course if compass yaw bad
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if (badMagYaw) {
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// calculate the variance for the rotation estimate expressed as a rotation vector
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// this will be used later to reset the quaternion state covariances
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Vector3f angleErrVarVec = calcRotVecVariances();
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// calculate new filter quaternion states from Euler angles
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stateStruct.quat.from_euler(eulerAngles.x, eulerAngles.y, gpsYaw);
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// reset the velocity and position states as they will be inaccurate due to bad yaw
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velResetSource = GPS;
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ResetVelocity();
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posResetSource = GPS;
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ResetPosition();
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// set the yaw angle variance to a larger value to reflect the uncertainty in yaw
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angleErrVarVec.z = sq(radians(45.0f));
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// reset the quaternion covariances using the rotation vector variances
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zeroRows(P,0,3);
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zeroCols(P,0,3);
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initialiseQuatCovariances(angleErrVarVec);
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// send yaw alignment information to console
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gcs().send_text(MAV_SEVERITY_INFO, "EKF3 IMU%u yaw aligned to GPS velocity",(unsigned)imu_index);
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// record the yaw reset event
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recordYawReset();
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// clear all pending yaw reset requests
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gpsYawResetRequest = false;
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magYawResetRequest = false;
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if (use_compass()) {
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// request a mag field reset which may enable us to use the magnetoemter if the previous fault was due to bad initialisation
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magStateResetRequest = true;
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// clear the all sensors failed status so that the magnetometers sensors get a second chance now that we are flying
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allMagSensorsFailed = false;
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}
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}
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}
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}
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/********************************************************
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* FUSE MEASURED_DATA *
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********************************************************/
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// select fusion of magnetometer data
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void NavEKF3_core::SelectMagFusion()
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{
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// start performance timer
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hal.util->perf_begin(_perf_FuseMagnetometer);
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// clear the flag that lets other processes know that the expensive magnetometer fusion operation has been perfomred on that time step
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// used for load levelling
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magFusePerformed = false;
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// check for and read new magnetometer measurements
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readMagData();
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// If we are using the compass and the magnetometer has been unhealthy for too long we declare a timeout
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if (magHealth) {
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magTimeout = false;
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lastHealthyMagTime_ms = imuSampleTime_ms;
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} else if ((imuSampleTime_ms - lastHealthyMagTime_ms) > frontend->magFailTimeLimit_ms && use_compass()) {
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magTimeout = true;
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}
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// check for availability of magnetometer data to fuse
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magDataToFuse = storedMag.recall(magDataDelayed,imuDataDelayed.time_ms);
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// Control reset of yaw and magnetic field states if we are using compass data
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if (magDataToFuse && use_compass()) {
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controlMagYawReset();
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}
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// determine if conditions are right to start a new fusion cycle
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// wait until the EKF time horizon catches up with the measurement
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bool dataReady = (magDataToFuse && statesInitialised && use_compass() && yawAlignComplete);
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if (dataReady) {
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// use the simple method of declination to maintain heading if we cannot use the magnetic field states
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if(inhibitMagStates || magStateResetRequest || !magStateInitComplete) {
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fuseEulerYaw();
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// zero the test ratio output from the inactive 3-axis magnetometer fusion
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magTestRatio.zero();
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} else {
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// if we are not doing aiding with earth relative observations (eg GPS) then the declination is
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// maintained by fusing declination as a synthesised observation
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if (PV_AidingMode != AID_ABSOLUTE) {
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FuseDeclination(0.34f);
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}
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// fuse the three magnetometer componenents sequentially
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hal.util->perf_begin(_perf_test[0]);
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for (mag_state.obsIndex = 0; mag_state.obsIndex <= 2; mag_state.obsIndex++) {
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FuseMagnetometer();
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// don't continue fusion if unhealthy
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if (!magHealth) {
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hal.util->perf_end(_perf_test[0]);
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break;
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}
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}
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hal.util->perf_end(_perf_test[0]);
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// zero the test ratio output from the inactive simple magnetometer yaw fusion
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yawTestRatio = 0.0f;
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}
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}
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// If we have no magnetometer, fuse in a synthetic heading measurement at 7Hz to prevent the filter covariances
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// from becoming badly conditioned. For planes we only do this on-ground because they can align the yaw from GPS when
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// airborne. For other platform types we do this all the time.
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if (!use_compass()) {
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if ((onGround || !assume_zero_sideslip()) && (imuSampleTime_ms - lastSynthYawTime_ms > 140)) {
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fuseEulerYaw();
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magTestRatio.zero();
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yawTestRatio = 0.0f;
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lastSynthYawTime_ms = imuSampleTime_ms;
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}
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}
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// If the final yaw reset has been performed and the state variances are sufficiently low
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// record that the earth field has been learned.
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if (!magFieldLearned && finalInflightMagInit) {
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magFieldLearned = (P[16][16] < sq(0.01f)) && (P[17][17] < sq(0.01f)) && (P[18][18] < sq(0.01f));
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}
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// record the last learned field variances
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if (magFieldLearned && !inhibitMagStates) {
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earthMagFieldVar.x = P[16][16];
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earthMagFieldVar.y = P[17][17];
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earthMagFieldVar.z = P[18][18];
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bodyMagFieldVar.x = P[19][19];
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bodyMagFieldVar.y = P[20][20];
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bodyMagFieldVar.z = P[21][21];
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}
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// stop performance timer
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hal.util->perf_end(_perf_FuseMagnetometer);
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}
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/*
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* Fuse magnetometer measurements using explicit algebraic equations generated with Matlab symbolic toolbox.
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* The script file used to generate these and other equations in this filter can be found here:
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* https://github.com/PX4/ecl/blob/master/matlab/scripts/Inertial%20Nav%20EKF/GenerateNavFilterEquations.m
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*/
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void NavEKF3_core::FuseMagnetometer()
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{
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// declarations
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ftype &q0 = mag_state.q0;
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ftype &q1 = mag_state.q1;
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ftype &q2 = mag_state.q2;
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ftype &q3 = mag_state.q3;
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ftype &magN = mag_state.magN;
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ftype &magE = mag_state.magE;
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ftype &magD = mag_state.magD;
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ftype &magXbias = mag_state.magXbias;
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ftype &magYbias = mag_state.magYbias;
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ftype &magZbias = mag_state.magZbias;
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uint8_t &obsIndex = mag_state.obsIndex;
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Matrix3f &DCM = mag_state.DCM;
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Vector3f &MagPred = mag_state.MagPred;
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ftype &R_MAG = mag_state.R_MAG;
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ftype *SH_MAG = &mag_state.SH_MAG[0];
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Vector24 H_MAG;
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Vector5 SK_MX;
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Vector5 SK_MY;
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Vector5 SK_MZ;
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// perform sequential fusion of magnetometer measurements.
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// this assumes that the errors in the different components are
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// uncorrelated which is not true, however in the absence of covariance
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// data fit is the only assumption we can make
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// so we might as well take advantage of the computational efficiencies
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// associated with sequential fusion
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// calculate observation jacobians and Kalman gains
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// copy required states to local variable names
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q0 = stateStruct.quat[0];
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q1 = stateStruct.quat[1];
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q2 = stateStruct.quat[2];
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q3 = stateStruct.quat[3];
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magN = stateStruct.earth_magfield[0];
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magE = stateStruct.earth_magfield[1];
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magD = stateStruct.earth_magfield[2];
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magXbias = stateStruct.body_magfield[0];
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magYbias = stateStruct.body_magfield[1];
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magZbias = stateStruct.body_magfield[2];
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// rotate predicted earth components into body axes and calculate
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// predicted measurements
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DCM[0][0] = q0*q0 + q1*q1 - q2*q2 - q3*q3;
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DCM[0][1] = 2.0f*(q1*q2 + q0*q3);
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DCM[0][2] = 2.0f*(q1*q3-q0*q2);
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DCM[1][0] = 2.0f*(q1*q2 - q0*q3);
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DCM[1][1] = q0*q0 - q1*q1 + q2*q2 - q3*q3;
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DCM[1][2] = 2.0f*(q2*q3 + q0*q1);
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DCM[2][0] = 2.0f*(q1*q3 + q0*q2);
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DCM[2][1] = 2.0f*(q2*q3 - q0*q1);
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DCM[2][2] = q0*q0 - q1*q1 - q2*q2 + q3*q3;
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MagPred[0] = DCM[0][0]*magN + DCM[0][1]*magE + DCM[0][2]*magD + magXbias;
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MagPred[1] = DCM[1][0]*magN + DCM[1][1]*magE + DCM[1][2]*magD + magYbias;
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MagPred[2] = DCM[2][0]*magN + DCM[2][1]*magE + DCM[2][2]*magD + magZbias;
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// calculate the measurement innovation for each axis
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for (uint8_t i = 0; i<=2; i++) {
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innovMag[i] = MagPred[i] - magDataDelayed.mag[i];
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}
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// scale magnetometer observation error with total angular rate to allow for timing errors
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R_MAG = sq(constrain_float(frontend->_magNoise, 0.01f, 0.5f)) + sq(frontend->magVarRateScale*imuDataDelayed.delAng.length() / imuDataDelayed.delAngDT);
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// calculate common expressions used to calculate observation jacobians an innovation variance for each component
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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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// Calculate the innovation variance for each axis
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// X axis
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varInnovMag[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));
|
|
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();
|
|
faultStatus.bad_xmag = true;
|
|
return;
|
|
}
|
|
|
|
// Y axis
|
|
varInnovMag[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));
|
|
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();
|
|
faultStatus.bad_ymag = true;
|
|
return;
|
|
}
|
|
|
|
// Z axis
|
|
varInnovMag[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));
|
|
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();
|
|
faultStatus.bad_zmag = true;
|
|
return;
|
|
}
|
|
|
|
// calculate the innovation test ratios
|
|
for (uint8_t i = 0; i<=2; i++) {
|
|
magTestRatio[i] = sq(innovMag[i]) / (sq(MAX(0.01f * (float)frontend->_magInnovGate, 1.0f)) * 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 (obsIndex = 0; obsIndex <= 2; obsIndex++) {
|
|
|
|
if (obsIndex == 0) {
|
|
|
|
for (uint8_t i = 0; i<=stateIndexLim; i++) H_MAG[i] = 0.0f;
|
|
H_MAG[0] = SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2;
|
|
H_MAG[1] = SH_MAG[0];
|
|
H_MAG[2] = -SH_MAG[1];
|
|
H_MAG[3] = SH_MAG[2];
|
|
H_MAG[16] = SH_MAG[5] - SH_MAG[4] - SH_MAG[3] + SH_MAG[6];
|
|
H_MAG[17] = 2.0f*q0*q3 + 2.0f*q1*q2;
|
|
H_MAG[18] = 2.0f*q1*q3 - 2.0f*q0*q2;
|
|
H_MAG[19] = 1.0f;
|
|
|
|
// calculate Kalman gain
|
|
SK_MX[0] = 1.0f / varInnovMag[0];
|
|
SK_MX[1] = SH_MAG[3] + SH_MAG[4] - SH_MAG[5] - SH_MAG[6];
|
|
SK_MX[2] = SH_MAG[7] + SH_MAG[8] - 2.0f*magD*q2;
|
|
SK_MX[3] = 2.0f*q0*q2 - 2.0f*q1*q3;
|
|
SK_MX[4] = 2.0f*q0*q3 + 2.0f*q1*q2;
|
|
|
|
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]);
|
|
|
|
if (!inhibitDelAngBiasStates) {
|
|
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]);
|
|
} else {
|
|
// zero indexes 10 to 12 = 3*4 bytes
|
|
memset(&Kfusion[10], 0, 12);
|
|
}
|
|
|
|
if (!inhibitDelVelBiasStates) {
|
|
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]);
|
|
} else {
|
|
// zero indexes 13 to 15 = 3*4 bytes
|
|
memset(&Kfusion[13], 0, 12);
|
|
}
|
|
// zero Kalman gains to inhibit magnetic field state estimation
|
|
if (!inhibitMagStates) {
|
|
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 {
|
|
// zero indexes 16 to 21 = 6*4 bytes
|
|
memset(&Kfusion[16], 0, 24);
|
|
}
|
|
|
|
// zero Kalman gains to inhibit wind state estimation
|
|
if (!inhibitWindStates) {
|
|
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 {
|
|
// zero indexes 22 to 23 = 2*4 bytes
|
|
memset(&Kfusion[22], 0, 8);
|
|
}
|
|
|
|
// 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;
|
|
|
|
} else if (obsIndex == 1) { // Fuse Y axis
|
|
|
|
// calculate observation jacobians
|
|
for (uint8_t i = 0; i<=stateIndexLim; i++) H_MAG[i] = 0.0f;
|
|
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 Kalman gain
|
|
SK_MY[0] = 1.0f / varInnovMag[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;
|
|
|
|
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]);
|
|
|
|
if (!inhibitDelAngBiasStates) {
|
|
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]);
|
|
} else {
|
|
// zero indexes 10 to 12 = 3*4 bytes
|
|
memset(&Kfusion[10], 0, 12);
|
|
}
|
|
|
|
if (!inhibitDelVelBiasStates) {
|
|
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]);
|
|
} else {
|
|
// zero indexes 13 to 15 = 3*4 bytes
|
|
memset(&Kfusion[13], 0, 12);
|
|
}
|
|
|
|
// zero Kalman gains to inhibit magnetic field state estimation
|
|
if (!inhibitMagStates) {
|
|
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 {
|
|
// zero indexes 16 to 21 = 6*4 bytes
|
|
memset(&Kfusion[16], 0, 24);
|
|
}
|
|
|
|
// zero Kalman gains to inhibit wind state estimation
|
|
if (!inhibitWindStates) {
|
|
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 {
|
|
// zero indexes 22 to 23 = 2*4 bytes
|
|
memset(&Kfusion[22], 0, 8);
|
|
}
|
|
|
|
// 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;
|
|
}
|
|
else if (obsIndex == 2) // we are now fusing the Z measurement
|
|
{
|
|
// calculate observation jacobians
|
|
for (uint8_t i = 0; i<=stateIndexLim; i++) H_MAG[i] = 0.0f;
|
|
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 Kalman gain
|
|
SK_MZ[0] = 1.0f / varInnovMag[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;
|
|
|
|
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]);
|
|
|
|
if (!inhibitDelAngBiasStates) {
|
|
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]);
|
|
} else {
|
|
// zero indexes 10 to 12 = 3*4 bytes
|
|
memset(&Kfusion[10], 0, 12);
|
|
}
|
|
|
|
if (!inhibitDelVelBiasStates) {
|
|
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]);
|
|
} else {
|
|
// zero indexes 13 to 15 = 3*4 bytes
|
|
memset(&Kfusion[13], 0, 12);
|
|
}
|
|
|
|
// zero Kalman gains to inhibit magnetic field state estimation
|
|
if (!inhibitMagStates) {
|
|
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 {
|
|
// zero indexes 16 to 21 = 6*4 bytes
|
|
memset(&Kfusion[16], 0, 24);
|
|
}
|
|
|
|
// zero Kalman gains to inhibit wind state estimation
|
|
if (!inhibitWindStates) {
|
|
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 {
|
|
// zero indexes 22 to 23 = 2*4 bytes
|
|
memset(&Kfusion[22], 0, 8);
|
|
}
|
|
|
|
// 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;
|
|
}
|
|
// correct the covariance P = (I - K*H)*P
|
|
// take advantage of the empty columns in KH to reduce the
|
|
// number of operations
|
|
for (unsigned i = 0; i<=stateIndexLim; i++) {
|
|
for (unsigned j = 0; j<=3; j++) {
|
|
KH[i][j] = Kfusion[i] * H_MAG[j];
|
|
}
|
|
for (unsigned j = 4; 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][3] * P[3][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;
|
|
}
|
|
}
|
|
// Check that we are not going to drive any variances negative and skip the update if so
|
|
bool healthyFusion = true;
|
|
for (uint8_t i= 0; i<=stateIndexLim; i++) {
|
|
if (KHP[i][i] > P[i][i]) {
|
|
healthyFusion = false;
|
|
}
|
|
}
|
|
if (healthyFusion) {
|
|
// update the covariance matrix
|
|
for (uint8_t i= 0; i<=stateIndexLim; i++) {
|
|
for (uint8_t 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();
|
|
|
|
// correct the state vector
|
|
for (uint8_t j= 0; j<=stateIndexLim; j++) {
|
|
statesArray[j] = statesArray[j] - Kfusion[j] * innovMag[obsIndex];
|
|
}
|
|
stateStruct.quat.normalize();
|
|
|
|
} else {
|
|
// record bad axis
|
|
if (obsIndex == 0) {
|
|
faultStatus.bad_xmag = true;
|
|
} else if (obsIndex == 1) {
|
|
faultStatus.bad_ymag = true;
|
|
} else if (obsIndex == 2) {
|
|
faultStatus.bad_zmag = true;
|
|
}
|
|
CovarianceInit();
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
/*
|
|
* Fuse magnetic heading measurement 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/PX4/ecl/blob/master/matlab/scripts/Inertial%20Nav%20EKF/GenerateNavFilterEquations.m
|
|
* This fusion method only modifies the orientation, does not require use of the magnetic field states and is computationally 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 magnetometer failures.
|
|
* It is not suitable for operation where the horizontal magnetic field strength is weak (within 30 degrees latitude of the the magnetic poles)
|
|
*/
|
|
void NavEKF3_core::fuseEulerYaw()
|
|
{
|
|
float q0 = stateStruct.quat[0];
|
|
float q1 = stateStruct.quat[1];
|
|
float q2 = stateStruct.quat[2];
|
|
float q3 = stateStruct.quat[3];
|
|
|
|
// compass measurement error variance (rad^2)
|
|
const float R_YAW = sq(frontend->_yawNoise);
|
|
|
|
// calculate observation jacobian, predicted yaw and zero yaw body to earth rotation matrix
|
|
// determine if a 321 or 312 Euler sequence is best
|
|
float predicted_yaw;
|
|
float H_YAW[4];
|
|
Matrix3f Tbn_zeroYaw;
|
|
if (fabsf(prevTnb[0][2]) < fabsf(prevTnb[1][2])) {
|
|
// 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;
|
|
|
|
// Get the 321 euler angles
|
|
Vector3f euler321;
|
|
stateStruct.quat.to_euler(euler321.x, euler321.y, euler321.z);
|
|
predicted_yaw = euler321.z;
|
|
|
|
// set the yaw to zero and calculate the zero yaw rotation from body to earth frame
|
|
Tbn_zeroYaw.from_euler(euler321.x, euler321.y, 0.0f);
|
|
|
|
} else {
|
|
// calculate observation 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;
|
|
|
|
// Get the 321 euler angles
|
|
Vector3f euler312 = stateStruct.quat.to_vector312();
|
|
predicted_yaw = euler312.z;
|
|
|
|
// set the yaw to zero and calculate the zero yaw rotation from body to earth frame
|
|
Tbn_zeroYaw.from_euler312(euler312.x, euler312.y, 0.0f);
|
|
}
|
|
|
|
// rotate measured mag components into earth frame
|
|
Vector3f magMeasNED = Tbn_zeroYaw*magDataDelayed.mag;
|
|
|
|
// Use the difference between the horizontal projection and declination to give the measured yaw
|
|
// If we can't use compass data, set the measurement to the predicted
|
|
// to prevent uncontrolled variance growth whilst on ground without magnetometer
|
|
float measured_yaw;
|
|
if (use_compass() && yawAlignComplete) {
|
|
measured_yaw = wrap_PI(-atan2f(magMeasNED.y, magMeasNED.x) + _ahrs->get_compass()->get_declination());
|
|
} else {
|
|
measured_yaw = predicted_yaw;
|
|
}
|
|
|
|
// Calculate the innovation
|
|
float innovation = wrap_PI(predicted_yaw - measured_yaw);
|
|
|
|
// Copy raw value to output variable used for data logging
|
|
innovYaw = innovation;
|
|
|
|
// Calculate innovation variance and Kalman gains, taking advantage of the fact that only the first 4 elements in H are non zero
|
|
float PH[4];
|
|
float varInnov = R_YAW;
|
|
for (uint8_t rowIndex=0; rowIndex<=3; rowIndex++) {
|
|
PH[rowIndex] = 0.0f;
|
|
for (uint8_t colIndex=0; colIndex<=3; colIndex++) {
|
|
PH[rowIndex] += P[rowIndex][colIndex]*H_YAW[colIndex];
|
|
}
|
|
varInnov += H_YAW[rowIndex]*PH[rowIndex];
|
|
}
|
|
float varInnovInv;
|
|
if (varInnov >= R_YAW) {
|
|
varInnovInv = 1.0f / varInnov;
|
|
// output numerical health status
|
|
faultStatus.bad_yaw = 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();
|
|
// output numerical health status
|
|
faultStatus.bad_yaw = true;
|
|
return;
|
|
}
|
|
|
|
// calculate Kalman gain
|
|
for (uint8_t rowIndex=0; rowIndex<=stateIndexLim; rowIndex++) {
|
|
Kfusion[rowIndex] = 0.0f;
|
|
for (uint8_t colIndex=0; colIndex<=3; colIndex++) {
|
|
Kfusion[rowIndex] += P[rowIndex][colIndex]*H_YAW[colIndex];
|
|
}
|
|
Kfusion[rowIndex] *= varInnovInv;
|
|
}
|
|
|
|
// calculate the innovation test ratio
|
|
yawTestRatio = sq(innovation) / (sq(MAX(0.01f * (float)frontend->_yawInnovGate, 1.0f)) * 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;
|
|
}
|
|
|
|
// 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;
|
|
}
|
|
|
|
// 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
|
|
// calculate K*H*P
|
|
for (uint8_t row = 0; row <= stateIndexLim; row++) {
|
|
for (uint8_t column = 0; column <= 3; column++) {
|
|
KH[row][column] = Kfusion[row] * H_YAW[column];
|
|
}
|
|
}
|
|
for (uint8_t row = 0; row <= stateIndexLim; row++) {
|
|
for (uint8_t column = 0; column <= stateIndexLim; column++) {
|
|
float tmp = KH[row][0] * P[0][column];
|
|
tmp += KH[row][1] * P[1][column];
|
|
tmp += KH[row][2] * P[2][column];
|
|
tmp += KH[row][3] * P[3][column];
|
|
KHP[row][column] = tmp;
|
|
}
|
|
}
|
|
|
|
// Check that we are not going to drive any variances negative and skip the update if so
|
|
bool healthyFusion = true;
|
|
for (uint8_t i= 0; i<=stateIndexLim; i++) {
|
|
if (KHP[i][i] > P[i][i]) {
|
|
healthyFusion = false;
|
|
}
|
|
}
|
|
if (healthyFusion) {
|
|
// update the covariance matrix
|
|
for (uint8_t i= 0; i<=stateIndexLim; i++) {
|
|
for (uint8_t 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();
|
|
|
|
// correct the state vector
|
|
for (uint8_t i=0; i<=stateIndexLim; i++) {
|
|
statesArray[i] -= Kfusion[i] * innovation;
|
|
}
|
|
stateStruct.quat.normalize();
|
|
|
|
// record fusion numerical health status
|
|
faultStatus.bad_yaw = false;
|
|
|
|
} else {
|
|
// record fusion numerical health status
|
|
faultStatus.bad_yaw = true;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* 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/PX4/ecl/blob/master/matlab/scripts/Inertial%20Nav%20EKF/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 NavEKF3_core::FuseDeclination(float declErr)
|
|
{
|
|
// declination error variance (rad^2)
|
|
const float R_DECL = sq(declErr);
|
|
|
|
// 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
|
|
// 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;
|
|
|
|
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);
|
|
|
|
if (!inhibitDelAngBiasStates) {
|
|
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);
|
|
} else {
|
|
// zero indexes 10 to 12 = 3*4 bytes
|
|
memset(&Kfusion[10], 0, 12);
|
|
}
|
|
|
|
if (!inhibitDelVelBiasStates) {
|
|
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);
|
|
} else {
|
|
// zero indexes 13 to 15 = 3*4 bytes
|
|
memset(&Kfusion[13], 0, 12);
|
|
}
|
|
|
|
if (!inhibitMagStates) {
|
|
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);
|
|
} else {
|
|
// zero indexes 16 to 21 = 6*4 bytes
|
|
memset(&Kfusion[16], 0, 24);
|
|
}
|
|
|
|
if (!inhibitWindStates) {
|
|
Kfusion[22] = -t4*t13*(P[22][16]*magE-P[22][17]*magN);
|
|
Kfusion[23] = -t4*t13*(P[23][16]*magE-P[23][17]*magN);
|
|
} else {
|
|
// zero indexes 22 to 23 = 2*4 bytes
|
|
memset(&Kfusion[22], 0, 8);
|
|
}
|
|
|
|
// get the magnetic declination
|
|
float magDecAng = use_compass() ? _ahrs->get_compass()->get_declination() : 0;
|
|
|
|
// Calculate the innovation
|
|
float innovation = atan2f(magE , magN) - magDecAng;
|
|
|
|
// limit the innovation to protect against data errors
|
|
if (innovation > 0.5f) {
|
|
innovation = 0.5f;
|
|
} else if (innovation < -0.5f) {
|
|
innovation = -0.5f;
|
|
}
|
|
|
|
// 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_DECL[16];
|
|
KH[i][17] = Kfusion[i] * H_DECL[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];
|
|
}
|
|
}
|
|
|
|
// Check that we are not going to drive any variances negative and skip the update if so
|
|
bool healthyFusion = true;
|
|
for (uint8_t i= 0; i<=stateIndexLim; i++) {
|
|
if (KHP[i][i] > P[i][i]) {
|
|
healthyFusion = false;
|
|
}
|
|
}
|
|
|
|
if (healthyFusion) {
|
|
// update the covariance matrix
|
|
for (uint8_t i= 0; i<=stateIndexLim; i++) {
|
|
for (uint8_t 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();
|
|
|
|
// correct the state vector
|
|
for (uint8_t j= 0; j<=stateIndexLim; j++) {
|
|
statesArray[j] = statesArray[j] - Kfusion[j] * innovation;
|
|
}
|
|
stateStruct.quat.normalize();
|
|
|
|
// record fusion health status
|
|
faultStatus.bad_decl = false;
|
|
} else {
|
|
// record fusion health status
|
|
faultStatus.bad_decl = true;
|
|
}
|
|
}
|
|
|
|
/********************************************************
|
|
* MISC FUNCTIONS *
|
|
********************************************************/
|
|
|
|
// align the NE earth magnetic field states with the published declination
|
|
void NavEKF3_core::alignMagStateDeclination()
|
|
{
|
|
// don't do this if we already have a learned magnetic field
|
|
if (magFieldLearned) {
|
|
return;
|
|
}
|
|
|
|
// 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 = norm(initMagNED.x,initMagNED.y);
|
|
stateStruct.earth_magfield.x = magLengthNE * cosf(magDecAng);
|
|
stateStruct.earth_magfield.y = magLengthNE * sinf(magDecAng);
|
|
|
|
if (!inhibitMagStates) {
|
|
// zero the corresponding state covariances if magnetic field state learning is active
|
|
float var_16 = P[16][16];
|
|
float var_17 = P[17][17];
|
|
zeroRows(P,16,17);
|
|
zeroCols(P,16,17);
|
|
P[16][16] = var_16;
|
|
P[17][17] = var_17;
|
|
|
|
// fuse the declination angle to establish covariances and prevent large swings in declination
|
|
// during initial fusion
|
|
FuseDeclination(0.1f);
|
|
|
|
}
|
|
}
|
|
|
|
// record a magnetic field state reset event
|
|
void NavEKF3_core::recordMagReset()
|
|
{
|
|
magStateInitComplete = true;
|
|
if (inFlight) {
|
|
finalInflightMagInit = true;
|
|
}
|
|
// take a snap-shot of the vertical position, quaternion and yaw innovation to use as a reference
|
|
// for post alignment checks
|
|
posDownAtLastMagReset = stateStruct.position.z;
|
|
quatAtLastMagReset = stateStruct.quat;
|
|
yawInnovAtLastMagReset = innovYaw;
|
|
}
|
|
|
|
|
|
#endif // HAL_CPU_CLASS
|