#include #include "AP_NavEKF2.h" #include "AP_NavEKF2_core.h" #include extern const AP_HAL::HAL& hal; /******************************************************** * RESET FUNCTIONS * ********************************************************/ // Control reset of yaw and magnetic field states void NavEKF2_core::controlMagYawReset() { // Vehicles that can use a zero sideslip assumption (Planes) are a special case // They can use the GPS velocity to recover from bad initial compass data // This allows recovery for heading alignment errors due to compass faults if (assume_zero_sideslip() && !finalInflightYawInit && inFlight ) { gpsYawResetRequest = true; return; } else { gpsYawResetRequest = false; } // QuaternionF and delta rotation vector that are re-used for different calculations Vector3F deltaRotVecTemp; QuaternionF deltaQuatTemp; bool flightResetAllowed = false; bool initialResetAllowed = false; if (!finalInflightYawInit) { // Use a quaternion division to calculate the delta quaternion between the rotation at the current and last time deltaQuatTemp = stateStruct.quat / prevQuatMagReset; prevQuatMagReset = stateStruct.quat; // convert the quaternion to a rotation vector and find its length deltaQuatTemp.to_axis_angle(deltaRotVecTemp); // check if the spin rate is OK - high spin rates can cause angular alignment errors bool angRateOK = deltaRotVecTemp.length() < 0.1745f; initialResetAllowed = angRateOK; flightResetAllowed = angRateOK && !onGround; } // reset the limit on the number of magnetic anomaly resets for each takeoff if (onGround) { magYawAnomallyCount = 0; } // Check if conditions for a interim or final yaw/mag reset are met bool finalResetRequest = false; bool interimResetRequest = false; if (flightResetAllowed && !assume_zero_sideslip()) { // check that we have reached a height where ground magnetic interference effects are insignificant // and can perform a final reset of the yaw and field states finalResetRequest = (stateStruct.position.z - posDownAtTakeoff) < -EKF2_MAG_FINAL_RESET_ALT; // check for increasing height bool hgtIncreasing = (posDownAtLastMagReset-stateStruct.position.z) > 0.5f; ftype yawInnovIncrease = fabsF(innovYaw) - fabsF(yawInnovAtLastMagReset); // check for increasing yaw innovations bool yawInnovIncreasing = yawInnovIncrease > 0.25f; // check that the yaw innovations haven't been caused by a large change in attitude deltaQuatTemp = quatAtLastMagReset / stateStruct.quat; deltaQuatTemp.to_axis_angle(deltaRotVecTemp); bool largeAngleChange = deltaRotVecTemp.length() > yawInnovIncrease; // if yaw innovations and height have increased and we haven't rotated much // then we are climbing away from a ground based magnetic anomaly and need to reset interimResetRequest = !finalInflightYawInit && !finalResetRequest && (magYawAnomallyCount < MAG_ANOMALY_RESET_MAX) && hgtIncreasing && yawInnovIncreasing && !largeAngleChange; } // an initial reset is required if we have not yet aligned the yaw angle bool initialResetRequest = initialResetAllowed && !yawAlignComplete; // a combined yaw angle and magnetic field reset can be initiated by: magYawResetRequest = magYawResetRequest || // an external request initialResetRequest || // an initial alignment performed by all vehicle types using magnetometer interimResetRequest || // an interim alignment required to recover from ground based magnetic anomaly finalResetRequest; // the final reset when we have acheived enough height to be in stable magnetic field environment // Perform a reset of magnetic field states and reset yaw to corrected magnetic heading if (magYawResetRequest || magStateResetRequest || extNavYawResetRequest) { // if a yaw reset has been requested, apply the updated quaternion to the current state if (extNavYawResetRequest) { // get the euler angles from the current state estimate Vector3F eulerAnglesOld; stateStruct.quat.to_euler(eulerAnglesOld.x, eulerAnglesOld.y, eulerAnglesOld.z); // previous value used to calculate a reset delta QuaternionF prevQuat = stateStruct.quat; // Get the Euler angles from the external vision data Vector3F eulerAnglesNew; extNavDataDelayed.quat.to_euler(eulerAnglesNew.x, eulerAnglesNew.y, eulerAnglesNew.z); // the new quaternion uses the old roll/pitch and new yaw angle stateStruct.quat.from_euler(eulerAnglesOld.x, eulerAnglesOld.y, eulerAnglesNew.z); // calculate the change in the quaternion state and apply it to the output history buffer prevQuat = stateStruct.quat/prevQuat; StoreQuatRotate(prevQuat); // send initial alignment status to console if (!yawAlignComplete) { GCS_SEND_TEXT(MAV_SEVERITY_INFO, "EKF2 IMU%u ext nav yaw alignment complete",(unsigned)imu_index); } // record the reset as complete and also record the in-flight reset as complete to stop further resets when height is gained // in-flight reset is unnecessary because we do not need to consider ground based magnetic anomaly effects yawAlignComplete = true; finalInflightYawInit = true; // clear the yaw reset request flag extNavYawResetRequest = false; } else if (magYawResetRequest || magStateResetRequest) { // get the euler angles from the current state estimate Vector3F eulerAngles; stateStruct.quat.to_euler(eulerAngles.x, eulerAngles.y, eulerAngles.z); // Use the Euler angles and magnetometer measurement to update the magnetic field states // and get an updated quaternion QuaternionF newQuat = calcQuatAndFieldStates(eulerAngles.x, eulerAngles.y); if (magYawResetRequest) { // previous value used to calculate a reset delta QuaternionF prevQuat = stateStruct.quat; // update the quaternion states using the new yaw angle stateStruct.quat = newQuat; // calculate the change in the quaternion state and apply it to the ouput history buffer prevQuat = stateStruct.quat/prevQuat; StoreQuatRotate(prevQuat); // send initial alignment status to console if (!yawAlignComplete) { GCS_SEND_TEXT(MAV_SEVERITY_INFO, "EKF2 IMU%u MAG%u initial yaw alignment complete",(unsigned)imu_index, (unsigned)magSelectIndex); } // send in-flight yaw alignment status to console if (finalResetRequest) { GCS_SEND_TEXT(MAV_SEVERITY_INFO, "EKF2 IMU%u MAG%u in-flight yaw alignment complete",(unsigned)imu_index, (unsigned)magSelectIndex); } else if (interimResetRequest) { GCS_SEND_TEXT(MAV_SEVERITY_WARNING, "EKF2 IMU%u MAG%u ground mag anomaly, yaw re-aligned",(unsigned)imu_index, (unsigned)magSelectIndex); } // update the yaw reset completed status recordYawReset(); // clear the yaw reset request flag magYawResetRequest = false; // clear the complete flags if an interim reset has been performed to allow subsequent // and final reset to occur if (interimResetRequest) { finalInflightYawInit = false; finalInflightMagInit = false; } } } } } // this function is used to do a forced re-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::realignYawGPS() { if ((sq(gpsDataDelayed.vel.x) + sq(gpsDataDelayed.vel.y)) > 25.0f) { // 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); // calculate course yaw angle ftype velYaw = atan2F(stateStruct.velocity.y,stateStruct.velocity.x); // calculate course yaw angle from GPS velocity ftype gpsYaw = atan2F(gpsDataDelayed.vel.y,gpsDataDelayed.vel.x); // Check the yaw angles for consistency ftype yawErr = MAX(fabsF(wrap_PI(gpsYaw - velYaw)),fabsF(wrap_PI(gpsYaw - eulerAngles.z))); // 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 bool badMagYaw = ((yawErr > 0.7854f) && (velTestRatio > 1.0f) && (PV_AidingMode == AID_ABSOLUTE)) || !yawAlignComplete; // correct yaw angle using GPS ground course if compass yaw bad if (badMagYaw) { // calculate new filter quaternion states from Euler angles stateStruct.quat.from_euler(eulerAngles.x, eulerAngles.y, gpsYaw); // reset the velocity and position states as they will be inaccurate due to bad yaw ResetVelocity(); ResetPosition(); // send yaw alignment information to console GCS_SEND_TEXT(MAV_SEVERITY_INFO, "EKF2 IMU%u yaw aligned to GPS velocity",(unsigned)imu_index); // zero the attitude covariances because the correlations will now be invalid zeroAttCovOnly(); // record the yaw reset event recordYawReset(); // clear all pending yaw reset requests gpsYawResetRequest = false; magYawResetRequest = false; if (use_compass()) { // request a mag field reset which may enable us to use the magnetometer if the previous fault was due to bad initialisation magStateResetRequest = true; // clear the all sensors failed status so that the magnetometers sensors get a second chance now that we are flying allMagSensorsFailed = false; } } } } /******************************************************** * FUSE MEASURED_DATA * ********************************************************/ // select fusion of magnetometer data void NavEKF2_core::SelectMagFusion() { // clear the flag that lets other processes know that the expensive magnetometer fusion operation has been performed on that time step // used for load levelling magFusePerformed = false; // Handle case where we are not using a yaw sensor of any type and and attempt to reset the yaw in // flight using the output from the GSF yaw estimator. if (!use_compass() && tiltAlignComplete) { if ((onGround || !assume_zero_sideslip()) && (imuSampleTime_ms - lastYawTime_ms > 140)) { fuseEulerYaw(); } if (yawAlignComplete) { return; } yawAlignComplete = EKFGSF_resetMainFilterYaw(); return; } // 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 and read new magnetometer measurements readMagData(); // check for availability of magnetometer data to fuse magDataToFuse = storedMag.recall(magDataDelayed,imuDataDelayed.time_ms); // Control reset of yaw and magnetic field states if we are using compass data if (magDataToFuse && use_compass()) { 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) { // use the simple method of declination to maintain heading if we cannot use the magnetic field states if(inhibitMagStates || magStateResetRequest || !magStateInitComplete) { fuseEulerYaw(); // zero the test ratio output from the inactive 3-axis magnetometer 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 // We also fuse declination if we are using the WMM tables if (PV_AidingMode != AID_ABSOLUTE || (frontend->_mag_ef_limit > 0 && have_table_earth_field)) { FuseDeclination(0.34f); } // fuse the three magnetometer componenents using sequential fusion of each axis FuseMagnetometer(); // zero the test ratio output from the inactive simple magnetometer yaw fusion yawTestRatio = 0.0f; } } // If the final yaw reset has been performed and the state variances are sufficiently low // record that the earth field has been learned. if (!magFieldLearned && finalInflightMagInit) { magFieldLearned = (P[16][16] < sq(0.01f)) && (P[17][17] < sq(0.01f)) && (P[18][18] < sq(0.01f)); } // record the last learned field variances if (magFieldLearned && !inhibitMagStates) { earthMagFieldVar.x = P[16][16]; earthMagFieldVar.y = P[17][17]; earthMagFieldVar.z = P[18][18]; bodyMagFieldVar.x = P[19][19]; bodyMagFieldVar.y = P[20][20]; bodyMagFieldVar.z = P[21][21]; } } /* * 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() { // 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; 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; // 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_ftype(frontend->_magNoise, 0.01f, 0.5f)) + sq(frontend->magVarRateScale*delAngCorrected.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(); faultStatus.bad_xmag = true; 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(); faultStatus.bad_ymag = true; 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(); 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 * (ftype)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; } // 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 for (uint8_t obsIndex = 0; obsIndex <= 2; obsIndex++) { if (obsIndex == 0) { // calculate observation jacobians ZERO_FARRAY(H_MAG); 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]); // 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; } } // set flags to indicate to other processes that fusion has been performed // this can be used by other fusion processes to avoid fusing on the same frame as this expensive step magFusePerformed = true; } else if (obsIndex == 1) // we are now fusing the Y measurement { // calculate observation jacobians ZERO_FARRAY(H_MAG); 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 performed // this can be used by other fusion processes to avoid fusing on the same frame as this expensive step magFusePerformed = true; } else if (obsIndex == 2) // we are now fusing the Z measurement { // calculate observation jacobians ZERO_FARRAY(H_MAG); 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 performed // 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<=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; } } // 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-conditioning. ForceSymmetry(); ConstrainVariances(); // update the states // zero the attitude error state - by definition it is assumed to be zero before each observation fusion stateStruct.angErr.zero(); // correct the state vector for (uint8_t j= 0; j<=stateIndexLim; j++) { statesArray[j] = statesArray[j] - Kfusion[j] * innovMag[obsIndex]; } // add table constraint here for faster convergence if (have_table_earth_field && frontend->_mag_ef_limit > 0) { MagTableConstrain(); } // the first 3 states represent the angular misalignment vector. // This is used to correct the estimated quaternion on the current time step stateStruct.quat.rotate(stateStruct.angErr); } 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/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 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 magnetic poles) */ void NavEKF2_core::fuseEulerYaw() { ftype q0 = stateStruct.quat[0]; ftype q1 = stateStruct.quat[1]; ftype q2 = stateStruct.quat[2]; ftype q3 = stateStruct.quat[3]; // compass measurement error variance (rad^2) set to parameter value as a default ftype 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 ftype predicted_yaw; ftype measured_yaw; ftype H_YAW[3]; 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 ftype t2 = q0*q0; ftype t3 = q1*q1; ftype t4 = q2*q2; ftype t5 = q3*q3; ftype t6 = t2+t3-t4-t5; ftype t7 = q0*q3*2.0f; ftype t8 = q1*q2*2.0f; ftype t9 = t7+t8; ftype t10 = sq(t6); if (t10 > 1e-6f) { t10 = 1.0f / t10; } else { return; } ftype t11 = t9*t9; ftype t12 = t10*t11; ftype t13 = t12+1.0f; ftype t14; if (fabsF(t13) > 1e-3f) { t14 = 1.0f/t13; } else { return; } ftype t15 = 1.0f/t6; H_YAW[0] = 0.0f; H_YAW[1] = t14*(t15*(q0*q1*2.0f-q2*q3*2.0f)+t9*t10*(q0*q2*2.0f+q1*q3*2.0f)); H_YAW[2] = t14*(t15*(t2-t3+t4-t5)+t9*t10*(t7-t8)); // calculate predicted and measured yaw angle Vector3F euler321; stateStruct.quat.to_euler(euler321.x, euler321.y, euler321.z); predicted_yaw = euler321.z; if (use_compass() && yawAlignComplete && magStateInitComplete) { // Use measured mag components rotated into earth frame to measure yaw Tbn_zeroYaw.from_euler(euler321.x, euler321.y, 0.0f); Vector3F magMeasNED = Tbn_zeroYaw*magDataDelayed.mag; measured_yaw = wrap_PI(-atan2F(magMeasNED.y, magMeasNED.x) + MagDeclination()); } else if (extNavUsedForYaw) { // Get the yaw angle from the external vision data R_YAW = sq(extNavDataDelayed.angErr); extNavDataDelayed.quat.to_euler(euler321.x, euler321.y, euler321.z); measured_yaw = euler321.z; } else { if (imuSampleTime_ms - prevBetaStep_ms > 1000 && yawEstimator != nullptr) { ftype gsfYaw, gsfYawVariance, velInnovLength; if (yawEstimator->getYawData(gsfYaw, gsfYawVariance) && is_positive(gsfYawVariance) && gsfYawVariance < sq(radians(15.0f)) && (assume_zero_sideslip() || (yawEstimator->getVelInnovLength(velInnovLength) && velInnovLength < frontend->maxYawEstVelInnov))) { measured_yaw = gsfYaw; R_YAW = gsfYawVariance; } else { // use predicted to prevent unconstrained variance growth measured_yaw = predicted_yaw; } } else { // use predicted to prevent unconstrained variance growth measured_yaw = predicted_yaw; } } } else { // calculate observation jacobian when we are observing a rotation in a 312 sequence ftype t2 = q0*q0; ftype t3 = q1*q1; ftype t4 = q2*q2; ftype t5 = q3*q3; ftype t6 = t2-t3+t4-t5; ftype t7 = q0*q3*2.0f; ftype t10 = q1*q2*2.0f; ftype t8 = t7-t10; ftype t9 = sq(t6); if (t9 > 1e-6f) { t9 = 1.0f/t9; } else { return; } ftype t11 = t8*t8; ftype t12 = t9*t11; ftype t13 = t12+1.0f; ftype t14; if (fabsF(t13) > 1e-3f) { t14 = 1.0f/t13; } else { return; } ftype t15 = 1.0f/t6; H_YAW[0] = -t14*(t15*(q0*q2*2.0+q1*q3*2.0)-t8*t9*(q0*q1*2.0-q2*q3*2.0)); H_YAW[1] = 0.0f; H_YAW[2] = t14*(t15*(t2+t3-t4-t5)+t8*t9*(t7+t10)); // calculate predicted and measured yaw angle Vector3F euler312 = stateStruct.quat.to_vector312(); predicted_yaw = euler312.z; if (use_compass() && yawAlignComplete && magStateInitComplete) { // Use measured mag components rotated into earth frame to measure yaw Tbn_zeroYaw.from_euler312(euler312.x, euler312.y, 0.0f); Vector3F magMeasNED = Tbn_zeroYaw*magDataDelayed.mag; measured_yaw = wrap_PI(-atan2F(magMeasNED.y, magMeasNED.x) + MagDeclination()); } else if (extNavUsedForYaw) { // Get the yaw angle from the external vision data R_YAW = sq(extNavDataDelayed.angErr); euler312 = extNavDataDelayed.quat.to_vector312(); measured_yaw = euler312.z; } else { if (imuSampleTime_ms - prevBetaStep_ms > 1000 && yawEstimator != nullptr) { ftype gsfYaw, gsfYawVariance, velInnovLength; if (yawEstimator->getYawData(gsfYaw, gsfYawVariance) && is_positive(gsfYawVariance) && gsfYawVariance < sq(radians(15.0f)) && (assume_zero_sideslip() || (yawEstimator->getVelInnovLength(velInnovLength) && velInnovLength < frontend->maxYawEstVelInnov))) { measured_yaw = gsfYaw; R_YAW = gsfYawVariance; } else { // use predicted to prevent unconstrained variance growth measured_yaw = predicted_yaw; } } else { // use predicted to prevent unconstrained variance growth measured_yaw = predicted_yaw; } } } // Calculate the innovation ftype 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 3 elements in H are non zero ftype PH[3]; ftype varInnov = R_YAW; 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_YAW[colIndex]; } varInnov += H_YAW[rowIndex]*PH[rowIndex]; } ftype 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<=2; colIndex++) { Kfusion[rowIndex] += P[rowIndex][colIndex]*H_YAW[colIndex]; } Kfusion[rowIndex] *= varInnovInv; } // calculate the innovation test ratio yawTestRatio = sq(innovation) / (sq(MAX(0.01f * (ftype)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 <= 2; 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++) { ftype tmp = KH[row][0] * P[0][column]; tmp += KH[row][1] * P[1][column]; tmp += KH[row][2] * P[2][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-conditioning. ForceSymmetry(); ConstrainVariances(); // zero the attitude error state - by definition it is assumed to be zero before each observation fusion stateStruct.angErr.zero(); // correct the state vector for (uint8_t i=0; i<=stateIndexLim; i++) { statesArray[i] -= Kfusion[i] * innovation; } // the first 3 states represent the angular misalignment vector. // This is used to correct the estimated quaternion on the current time step stateStruct.quat.rotate(stateStruct.angErr); // record fusion event faultStatus.bad_yaw = false; lastYawTime_ms = imuSampleTime_ms; } 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/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(ftype declErr) { // declination error variance (rad^2) const ftype R_DECL = sq(declErr); // copy required states to local variables ftype magN = stateStruct.earth_magfield.x; ftype 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 ftype t2 = magE*magE; ftype t3 = magN*magN; ftype t4 = t2+t3; ftype t5 = 1.0f/t4; ftype t22 = magE*t5; ftype t23 = magN*t5; ftype t6 = P[16][16]*t22; ftype t13 = P[17][16]*t23; ftype t7 = t6-t13; ftype t8 = t22*t7; ftype t9 = P[16][17]*t22; ftype t14 = P[17][17]*t23; ftype t10 = t9-t14; ftype t15 = t23*t10; ftype t11 = R_DECL+t8-t15; // innovation variance if (t11 < R_DECL) { return; } ftype t12 = 1.0f/t11; ftype H_MAG[24]; H_MAG[16] = -magE*t5; H_MAG[17] = magN*t5; for (uint8_t i=0; i<=15; i++) { Kfusion[i] = -t12*(P[i][16]*t22-P[i][17]*t23); } Kfusion[16] = -t12*(t6-P[16][17]*t23); Kfusion[17] = t12*(t14-P[17][16]*t22); for (uint8_t i=17; i<=23; i++) { Kfusion[i] = -t12*(P[i][16]*t22-P[i][17]*t23); } // get the magnetic declination ftype magDecAng = MagDeclination(); // Calculate the innovation ftype 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_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]; } } // 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-conditioning. ForceSymmetry(); ConstrainVariances(); // zero the attitude error state - by definition it is assumed to be zero before each observation 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 used to correct the estimated quaternion on the current time step stateStruct.quat.rotate(stateStruct.angErr); // 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 NavEKF2_core::alignMagStateDeclination() { // don't do this if we already have a learned magnetic field if (magFieldLearned) { return; } // get the magnetic declination ftype magDecAng = MagDeclination(); // rotate the NE values so that the declination matches the published value Vector3F initMagNED = stateStruct.earth_magfield; ftype 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 ftype var_16 = P[16][16]; ftype 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 NavEKF2_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; } // Reset states using yaw from EKF-GSF and velocity and position from GPS bool NavEKF2_core::EKFGSF_resetMainFilterYaw() { // Don't do a reset unless permitted by the EK2_GSF_USE_MASK and EKF@_GSF_RUN_MASK parameter masks if ((yawEstimator == nullptr) || !(frontend->_gsfUseMask & (1U<= frontend->_gsfResetMaxCount) { return false; }; ftype yawEKFGSF, yawVarianceEKFGSF, velInnovLength; if (yawEstimator->getYawData(yawEKFGSF, yawVarianceEKFGSF) && is_positive(yawVarianceEKFGSF) && yawVarianceEKFGSF < sq(radians(15.0f)) && (assume_zero_sideslip() || (yawEstimator->getVelInnovLength(velInnovLength) && velInnovLength < frontend->maxYawEstVelInnov))) { // keep roll and pitch and reset yaw resetQuatStateYawOnly(yawEKFGSF, yawVarianceEKFGSF, false); // record the emergency reset event EKFGSF_yaw_reset_request_ms = 0; EKFGSF_yaw_reset_ms = imuSampleTime_ms; EKFGSF_yaw_reset_count++; if (!use_compass()) { GCS_SEND_TEXT(MAV_SEVERITY_INFO, "EKF2 IMU%u yaw aligned using GPS",(unsigned)imu_index); } else { GCS_SEND_TEXT(MAV_SEVERITY_WARNING, "EKF2 IMU%u emergency yaw reset",(unsigned)imu_index); } // Fail the magnetomer so it doesn't get used and pull the yaw away from the correct value allMagSensorsFailed = true; // reset velocity and position states to GPS - if yaw is fixed then the filter should start to operate correctly ResetVelocity(); ResetPosition(); // reset test ratios that are reported to prevent a race condition with the external state machine requesting the reset velTestRatio = 0.0f; posTestRatio = 0.0f; return true; } return false; } void NavEKF2_core::resetQuatStateYawOnly(ftype yaw, ftype yawVariance, bool isDeltaYaw) { QuaternionF quatBeforeReset = stateStruct.quat; // check if we should use a 321 or 312 Rotation sequence and update the quaternion // states using the preferred yaw definition stateStruct.quat.inverse().rotation_matrix(prevTnb); Vector3F eulerAngles; if (fabsF(prevTnb[2][0]) < fabsF(prevTnb[2][1])) { // rolled more than pitched so use 321 rotation order stateStruct.quat.to_euler(eulerAngles.x, eulerAngles.y, eulerAngles.z); if (isDeltaYaw) { yaw = wrap_PI(yaw + eulerAngles.z); } stateStruct.quat.from_euler(eulerAngles.x, eulerAngles.y, yaw); } else { // pitched more than rolled so use 312 rotation order eulerAngles = stateStruct.quat.to_vector312(); if (isDeltaYaw) { yaw = wrap_PI(yaw + eulerAngles.z); } stateStruct.quat.from_vector312(eulerAngles.x, eulerAngles.y, yaw); } // Update the rotation matrix stateStruct.quat.inverse().rotation_matrix(prevTnb); ftype deltaYaw = wrap_PI(yaw - eulerAngles.z); // calculate the change in the quaternion state and apply it to the output history buffer QuaternionF quat_delta = stateStruct.quat / quatBeforeReset; StoreQuatRotate(quat_delta); // rotate attitude error variances into earth frame Vector3F bf_variances = Vector3F(P[0][0], P[1][1], P[2][2]); Vector3F ef_variances = prevTnb.transposed() * bf_variances; // reset vertical component to supplied value ef_variances.z = yawVariance; // rotate back into body frame bf_variances = prevTnb * ef_variances; // Reset all attitude error state covariances zeroRows(P, 0, 2); zeroCols(P, 0, 2); // Initialise variances P[0][0] = bf_variances.x; P[1][1] = bf_variances.y; P[2][2] = bf_variances.z; // record the yaw reset event yawResetAngle += deltaYaw; lastYawReset_ms = imuSampleTime_ms; recordYawReset(); // clear all pending yaw reset requests gpsYawResetRequest = false; magYawResetRequest = false; }