// select the height measurement to be fused from the available baro, range finder and GPS sources
void NavEKF2_core::selectHeightForFusion()
{
// Read range finder data and check for new data in the buffer
// This data is used by both height and optical flow fusion processing
readRangeFinder();
rangeDataToFuse = RecallRange();
// read baro height data from the sensor and check for new data in the buffer
readBaroData();
baroDataToFuse = RecallBaro();
// determine if we should be using a height source other than baro
bool usingRangeForHgt = (frontend->_altSource == 1 && imuSampleTime_ms - rngValidMeaTime_ms < 500 && frontend->_fusionModeGPS == 3);
bool usingGpsForHgt = (frontend->_altSource == 2 && imuSampleTime_ms - lastTimeGpsReceived_ms < 500 && validOrigin);
// if there is new baro data to fuse, calculate filterred baro data required by other processes
if (baroDataToFuse) {
// calculate offset to baro data that enables baro to be used as a backup if we are using other height sources
if (usingRangeForHgt || usingGpsForHgt) {
calcFiltBaroOffset();
}
// filtered baro data used to provide a reference for takeoff
// it is is reset to last height measurement on disarming in performArmingChecks()
if (!getTakeoffExpected()) {
const float gndHgtFiltTC = 0.5f;
const float dtBaro = frontend->hgtAvg_ms*1.0e-3f;
float alpha = constrain_float(dtBaro / (dtBaro+gndHgtFiltTC),0.0f,1.0f);
meaHgtAtTakeOff += (baroDataDelayed.hgt-meaHgtAtTakeOff)*alpha;
}
}
// Select the height measurement source
if (rangeDataToFuse && usingRangeForHgt) {
// using range finder data
// correct for tilt using a flat earth model
if (prevTnb.c.z >= 0.7) {
hgtMea = max(rangeDataDelayed.rng * prevTnb.c.z, rngOnGnd);
// enable fusion
fuseHgtData = true;
// set the observation noise
posDownObsNoise = sq(constrain_float(frontend->_rngNoise, 0.1f, 10.0f));
} else {
// disable fusion if tilted too far
fuseHgtData = false;
}
} else if (gpsDataToFuse && usingGpsForHgt) {
// using GPS data
hgtMea = gpsDataDelayed.hgt;
// enable fusion
fuseHgtData = true;
// set the observation noise to the horizontal GPS noise plus a scaler becasue GPS vertical position is usually less accurate
// TODO use VDOP/HDOP, reported accuracy or a separate parameter
posDownObsNoise = sq(constrain_float(frontend->_gpsHorizPosNoise * 1.5f, 0.1f, 10.0f));
} else if (baroDataToFuse && !usingRangeForHgt && !usingGpsForHgt) {
// using Baro data
hgtMea = baroDataDelayed.hgt - baroHgtOffset;
// enable fusion
fuseHgtData = true;
// set the observation noise
posDownObsNoise = sq(constrain_float(frontend->_baroAltNoise, 0.1f, 10.0f));
// reduce weighting (increase observation noise) on baro if we are likely to be in ground effect
if (getTakeoffExpected() || getTouchdownExpected()) {
posDownObsNoise *= frontend->gndEffectBaroScaler;
}
} else {
fuseHgtData = false;
}
// If we haven't fused height data for a while, then declare the height data as being timed out
// set timeout period based on whether we have vertical GPS velocity available to constrain drift
hgtRetryTime_ms = (useGpsVertVel && !velTimeout) ? frontend->hgtRetryTimeMode0_ms : frontend->hgtRetryTimeMode12_ms;
if (imuSampleTime_ms - lastHgtPassTime_ms > hgtRetryTime_ms) {
hgtTimeout = true;
} else {
hgtTimeout = false;
}
}
// select the height measurement to be fused from the available baro, range finder and GPS sources
void NavEKF2_core::selectHeightForFusion()
{
// Read range finder data and check for new data in the buffer
// This data is used by both height and optical flow fusion processing
readRangeFinder();
rangeDataToFuse = storedRange.recall(rangeDataDelayed,imuDataDelayed.time_ms);
// read baro height data from the sensor and check for new data in the buffer
readBaroData();
baroDataToFuse = storedBaro.recall(baroDataDelayed, imuDataDelayed.time_ms);
// select height source
if (((frontend->_useRngSwHgt > 0) || (frontend->_altSource == 1)) && (imuSampleTime_ms - rngValidMeaTime_ms < 500)) {
if (frontend->_altSource == 1) {
// always use range finder
activeHgtSource = HGT_SOURCE_RNG;
} else {
// determine if we are above or below the height switch region
float rangeMaxUse = 1e-4f * (float)frontend->_rng.max_distance_cm() * (float)frontend->_useRngSwHgt;
bool aboveUpperSwHgt = (terrainState - stateStruct.position.z) > rangeMaxUse;
bool belowLowerSwHgt = (terrainState - stateStruct.position.z) < 0.7f * rangeMaxUse;
// If the terrain height is consistent and we are moving slowly, then it can be
// used as a height reference in combination with a range finder
float horizSpeed = norm(stateStruct.velocity.x, stateStruct.velocity.y);
bool dontTrustTerrain = (horizSpeed > 2.0f) || !terrainHgtStable;
bool trustTerrain = (horizSpeed < 1.0f) && terrainHgtStable;
/*
* Switch between range finder and primary height source using height above ground and speed thresholds with
* hysteresis to avoid rapid switching. Using range finder for height requires a consistent terrain height
* which cannot be assumed if the vehicle is moving horizontally.
*/
if ((aboveUpperSwHgt || dontTrustTerrain) && (activeHgtSource == HGT_SOURCE_RNG)) {
// cannot trust terrain or range finder so stop using range finder height
if (frontend->_altSource == 0) {
activeHgtSource = HGT_SOURCE_BARO;
} else if (frontend->_altSource == 2) {
activeHgtSource = HGT_SOURCE_GPS;
}
} else if (belowLowerSwHgt && trustTerrain && (activeHgtSource != HGT_SOURCE_RNG)) {
// reliable terrain and range finder so start using range finder height
activeHgtSource = HGT_SOURCE_RNG;
}
}
} else if ((frontend->_altSource == 2) && ((imuSampleTime_ms - lastTimeGpsReceived_ms) < 500) && validOrigin && gpsAccuracyGood) {
activeHgtSource = HGT_SOURCE_GPS;
} else {
activeHgtSource = HGT_SOURCE_BARO;
}
// Use Baro alt as a fallback if we lose range finder or GPS
bool lostRngHgt = ((activeHgtSource == HGT_SOURCE_RNG) && ((imuSampleTime_ms - rngValidMeaTime_ms) > 500));
bool lostGpsHgt = ((activeHgtSource == HGT_SOURCE_GPS) && ((imuSampleTime_ms - lastTimeGpsReceived_ms) > 2000));
if (lostRngHgt || lostGpsHgt) {
activeHgtSource = HGT_SOURCE_BARO;
}
// if there is new baro data to fuse, calculate filtered baro data required by other processes
if (baroDataToFuse) {
// calculate offset to baro data that enables us to switch to Baro height use during operation
if (activeHgtSource != HGT_SOURCE_BARO) {
calcFiltBaroOffset();
}
// filtered baro data used to provide a reference for takeoff
// it is is reset to last height measurement on disarming in performArmingChecks()
if (!getTakeoffExpected()) {
const float gndHgtFiltTC = 0.5f;
const float dtBaro = frontend->hgtAvg_ms*1.0e-3f;
float alpha = constrain_float(dtBaro / (dtBaro+gndHgtFiltTC),0.0f,1.0f);
meaHgtAtTakeOff += (baroDataDelayed.hgt-meaHgtAtTakeOff)*alpha;
}
}
// calculate offset to GPS height data that enables us to switch to GPS height during operation
if (gpsDataToFuse && (activeHgtSource != HGT_SOURCE_GPS)) {
calcFiltGpsHgtOffset();
}
// Select the height measurement source
if (rangeDataToFuse && (activeHgtSource == HGT_SOURCE_RNG)) {
// using range finder data
// correct for tilt using a flat earth model
if (prevTnb.c.z >= 0.7) {
// calculate height above ground
hgtMea = MAX(rangeDataDelayed.rng * prevTnb.c.z, rngOnGnd);
// correct for terrain position relative to datum
hgtMea -= terrainState;
// enable fusion
fuseHgtData = true;
// set the observation noise
posDownObsNoise = sq(constrain_float(frontend->_rngNoise, 0.1f, 10.0f));
// add uncertainty created by terrain gradient and vehicle tilt
posDownObsNoise += sq(rangeDataDelayed.rng * frontend->_terrGradMax) * MAX(0.0f , (1.0f - sq(prevTnb.c.z)));
} else {
// disable fusion if tilted too far
fuseHgtData = false;
}
} else if (gpsDataToFuse && (activeHgtSource == HGT_SOURCE_GPS)) {
// using GPS data
hgtMea = gpsDataDelayed.hgt;
// enable fusion
fuseHgtData = true;
// set the observation noise using receiver reported accuracy or the horizontal noise scaled for typical VDOP/HDOP ratio
if (gpsHgtAccuracy > 0.0f) {
posDownObsNoise = sq(constrain_float(gpsHgtAccuracy, 1.5f * frontend->_gpsHorizPosNoise, 100.0f));
} else {
posDownObsNoise = sq(constrain_float(1.5f * frontend->_gpsHorizPosNoise, 0.1f, 10.0f));
}
} else if (baroDataToFuse && (activeHgtSource == HGT_SOURCE_BARO)) {
// using Baro data
hgtMea = baroDataDelayed.hgt - baroHgtOffset;
// enable fusion
fuseHgtData = true;
// set the observation noise
posDownObsNoise = sq(constrain_float(frontend->_baroAltNoise, 0.1f, 10.0f));
// reduce weighting (increase observation noise) on baro if we are likely to be in ground effect
if (getTakeoffExpected() || getTouchdownExpected()) {
posDownObsNoise *= frontend->gndEffectBaroScaler;
}
// If we are in takeoff mode, the height measurement is limited to be no less than the measurement at start of takeoff
// This prevents negative baro disturbances due to copter downwash corrupting the EKF altitude during initial ascent
if (motorsArmed && getTakeoffExpected()) {
hgtMea = MAX(hgtMea, meaHgtAtTakeOff);
}
} else {
fuseHgtData = false;
}
// If we haven't fused height data for a while, then declare the height data as being timed out
// set timeout period based on whether we have vertical GPS velocity available to constrain drift
hgtRetryTime_ms = (useGpsVertVel && !velTimeout) ? frontend->hgtRetryTimeMode0_ms : frontend->hgtRetryTimeMode12_ms;
if (imuSampleTime_ms - lastHgtPassTime_ms > hgtRetryTime_ms) {
hgtTimeout = true;
} else {
hgtTimeout = false;
}
}
// fuse selected position, velocity and height measurements
void NavEKF2_core::FuseVelPosNED()
{
// start performance timer
hal.util->perf_begin(_perf_FuseVelPosNED);
// health is set bad until test passed
velHealth = false;
posHealth = false;
hgtHealth = false;
// declare variables used to check measurement errors
Vector3f velInnov;
// declare variables used to control access to arrays
bool fuseData[6] = {false,false,false,false,false,false};
uint8_t stateIndex;
uint8_t obsIndex;
// declare variables used by state and covariance update calculations
float posErr;
Vector6 R_OBS; // Measurement variances used for fusion
Vector6 R_OBS_DATA_CHECKS; // Measurement variances used for data checks only
Vector6 observation;
float SK;
// perform sequential fusion of GPS measurements. This assumes that the
// errors in the different velocity and position components are
// uncorrelated which is not true, however in the absence of covariance
// data from the GPS receiver it is the only assumption we can make
// so we might as well take advantage of the computational efficiencies
// associated with sequential fusion
if (fuseVelData || fusePosData || fuseHgtData) {
// set the GPS data timeout depending on whether airspeed data is present
uint32_t gpsRetryTime;
if (useAirspeed()) gpsRetryTime = frontend->gpsRetryTimeUseTAS_ms;
else gpsRetryTime = frontend->gpsRetryTimeNoTAS_ms;
// form the observation vector
observation[0] = gpsDataDelayed.vel.x;
observation[1] = gpsDataDelayed.vel.y;
observation[2] = gpsDataDelayed.vel.z;
observation[3] = gpsDataDelayed.pos.x;
observation[4] = gpsDataDelayed.pos.y;
observation[5] = -hgtMea;
// calculate additional error in GPS position caused by manoeuvring
posErr = frontend->gpsPosVarAccScale * accNavMag;
// estimate the GPS Velocity, GPS horiz position and height measurement variances.
// if the GPS is able to report a speed error, we use it to adjust the observation noise for GPS velocity
// otherwise we scale it using manoeuvre acceleration
// Use different errors if flying without GPS using synthetic position and velocity data
if (PV_AidingMode == AID_NONE && inFlight) {
// Assume the vehicle will be flown with velocity changes less than 10 m/s in this mode (realistic for indoor use)
// This is a compromise between corrections for gyro errors and reducing angular errors due to maneouvres
R_OBS[0] = sq(10.0f);
R_OBS[1] = R_OBS[0];
R_OBS[2] = R_OBS[0];
// Assume a large position uncertainty so as to contrain position states in this mode but minimise angular errors due to manoeuvres
R_OBS[3] = sq(25.0f);
R_OBS[4] = R_OBS[3];
} else {
if (gpsSpdAccuracy > 0.0f) {
// use GPS receivers reported speed accuracy if available and floor at value set by gps noise parameter
R_OBS[0] = sq(constrain_float(gpsSpdAccuracy, frontend->_gpsHorizVelNoise, 50.0f));
R_OBS[2] = sq(constrain_float(gpsSpdAccuracy, frontend->_gpsVertVelNoise, 50.0f));
} else {
// calculate additional error in GPS velocity caused by manoeuvring
R_OBS[0] = sq(constrain_float(frontend->_gpsHorizVelNoise, 0.05f, 5.0f)) + sq(frontend->gpsNEVelVarAccScale * accNavMag);
R_OBS[2] = sq(constrain_float(frontend->_gpsVertVelNoise, 0.05f, 5.0f)) + sq(frontend->gpsDVelVarAccScale * accNavMag);
}
R_OBS[1] = R_OBS[0];
R_OBS[3] = sq(constrain_float(frontend->_gpsHorizPosNoise, 0.1f, 10.0f)) + sq(posErr);
R_OBS[4] = R_OBS[3];
}
R_OBS[5] = posDownObsNoise;
// For data integrity checks we use the same measurement variances as used to calculate the Kalman gains for all measurements except GPS horizontal velocity
// For horizontal GPs velocity we don't want the acceptance radius to increase with reported GPS accuracy so we use a value based on best GPs perfomrance
// plus a margin for manoeuvres. It is better to reject GPS horizontal velocity errors early
for (uint8_t i=0; i<=1; i++) R_OBS_DATA_CHECKS[i] = sq(constrain_float(frontend->_gpsHorizVelNoise, 0.05f, 5.0f)) + sq(frontend->gpsNEVelVarAccScale * accNavMag);
for (uint8_t i=2; i<=5; i++) R_OBS_DATA_CHECKS[i] = R_OBS[i];
// if vertical GPS velocity data and an independant height source is being used, check to see if the GPS vertical velocity and altimeter
// innovations have the same sign and are outside limits. If so, then it is likely aliasing is affecting
// the accelerometers and we should disable the GPS and barometer innovation consistency checks.
if (useGpsVertVel && fuseVelData && (frontend->_altSource != 2)) {
// calculate innovations for height and vertical GPS vel measurements
float hgtErr = stateStruct.position.z - observation[5];
float velDErr = stateStruct.velocity.z - observation[2];
// check if they are the same sign and both more than 3-sigma out of bounds
if ((hgtErr*velDErr > 0.0f) && (sq(hgtErr) > 9.0f * (P[8][8] + R_OBS_DATA_CHECKS[5])) && (sq(velDErr) > 9.0f * (P[5][5] + R_OBS_DATA_CHECKS[2]))) {
badIMUdata = true;
} else {
badIMUdata = false;
}
}
// calculate innovations and check GPS data validity using an innovation consistency check
// test position measurements
if (fusePosData) {
// test horizontal position measurements
innovVelPos[3] = stateStruct.position.x - observation[3];
innovVelPos[4] = stateStruct.position.y - observation[4];
varInnovVelPos[3] = P[6][6] + R_OBS_DATA_CHECKS[3];
varInnovVelPos[4] = P[7][7] + R_OBS_DATA_CHECKS[4];
// apply an innovation consistency threshold test, but don't fail if bad IMU data
float maxPosInnov2 = sq(max(0.01f * (float)frontend->_gpsPosInnovGate, 1.0f))*(varInnovVelPos[3] + varInnovVelPos[4]);
posTestRatio = (sq(innovVelPos[3]) + sq(innovVelPos[4])) / maxPosInnov2;
posHealth = ((posTestRatio < 1.0f) || badIMUdata);
// declare a timeout condition if we have been too long without data or not aiding
posTimeout = (((imuSampleTime_ms - lastPosPassTime_ms) > gpsRetryTime) || PV_AidingMode == AID_NONE);
// use position data if healthy, timed out, or in constant position mode
if (posHealth || posTimeout || (PV_AidingMode == AID_NONE)) {
posHealth = true;
// only reset the failed time and do glitch timeout checks if we are doing full aiding
if (PV_AidingMode == AID_ABSOLUTE) {
lastPosPassTime_ms = imuSampleTime_ms;
// if timed out or outside the specified uncertainty radius, reset to the GPS
if (posTimeout || ((P[6][6] + P[7][7]) > sq(float(frontend->_gpsGlitchRadiusMax)))) {
// reset the position to the current GPS position
ResetPosition();
// reset the velocity to the GPS velocity
ResetVelocity();
// don't fuse GPS data on this time step
fusePosData = false;
fuseVelData = false;
// Reset the position variances and corresponding covariances to a value that will pass the checks
zeroRows(P,6,7);
zeroCols(P,6,7);
P[6][6] = sq(float(0.5f*frontend->_gpsGlitchRadiusMax));
P[7][7] = P[6][6];
// Reset the normalised innovation to avoid failing the bad fusion tests
posTestRatio = 0.0f;
velTestRatio = 0.0f;
}
}
} else {
posHealth = false;
}
}
// test velocity measurements
if (fuseVelData) {
// test velocity measurements
uint8_t imax = 2;
// Don't fuse vertical velocity observations if inhibited by the user or if we are using synthetic data
if (frontend->_fusionModeGPS >= 1 || PV_AidingMode != AID_ABSOLUTE) {
imax = 1;
}
float innovVelSumSq = 0; // sum of squares of velocity innovations
float varVelSum = 0; // sum of velocity innovation variances
for (uint8_t i = 0; i<=imax; i++) {
// velocity states start at index 3
stateIndex = i + 3;
// calculate innovations using blended and single IMU predicted states
velInnov[i] = stateStruct.velocity[i] - observation[i]; // blended
// calculate innovation variance
varInnovVelPos[i] = P[stateIndex][stateIndex] + R_OBS_DATA_CHECKS[i];
// sum the innovation and innovation variances
innovVelSumSq += sq(velInnov[i]);
varVelSum += varInnovVelPos[i];
}
// apply an innovation consistency threshold test, but don't fail if bad IMU data
// calculate the test ratio
velTestRatio = innovVelSumSq / (varVelSum * sq(max(0.01f * (float)frontend->_gpsVelInnovGate, 1.0f)));
// fail if the ratio is greater than 1
velHealth = ((velTestRatio < 1.0f) || badIMUdata);
// declare a timeout if we have not fused velocity data for too long or not aiding
velTimeout = (((imuSampleTime_ms - lastVelPassTime_ms) > gpsRetryTime) || PV_AidingMode == AID_NONE);
// use velocity data if healthy, timed out, or in constant position mode
if (velHealth || velTimeout) {
velHealth = true;
// restart the timeout count
lastVelPassTime_ms = imuSampleTime_ms;
// If we are doing full aiding and velocity fusion times out, reset to the GPS velocity
if (PV_AidingMode == AID_ABSOLUTE && velTimeout) {
// reset the velocity to the GPS velocity
ResetVelocity();
// don't fuse GPS velocity data on this time step
fuseVelData = false;
// Reset the normalised innovation to avoid failing the bad fusion tests
velTestRatio = 0.0f;
}
} else {
velHealth = false;
}
}
// test height measurements
if (fuseHgtData) {
// calculate height innovations
innovVelPos[5] = stateStruct.position.z - observation[5];
varInnovVelPos[5] = P[8][8] + R_OBS_DATA_CHECKS[5];
// calculate the innovation consistency test ratio
hgtTestRatio = sq(innovVelPos[5]) / (sq(max(0.01f * (float)frontend->_hgtInnovGate, 1.0f)) * varInnovVelPos[5]);
// fail if the ratio is > 1, but don't fail if bad IMU data
hgtHealth = ((hgtTestRatio < 1.0f) || badIMUdata);
// Fuse height data if healthy or timed out or in constant position mode
if (hgtHealth || hgtTimeout || (PV_AidingMode == AID_NONE && onGround)) {
// Calculate a filtered value to be used by pre-flight health checks
// We need to filter because wind gusts can generate significant baro noise and we want to be able to detect bias errors in the inertial solution
if (onGround) {
float dtBaro = (imuSampleTime_ms - lastHgtPassTime_ms)*1.0e-3f;
const float hgtInnovFiltTC = 2.0f;
float alpha = constrain_float(dtBaro/(dtBaro+hgtInnovFiltTC),0.0f,1.0f);
hgtInnovFiltState += (innovVelPos[5]-hgtInnovFiltState)*alpha;
} else {
hgtInnovFiltState = 0.0f;
}
// if timed out, reset the height
if (hgtTimeout) {
ResetHeight();
hgtTimeout = false;
}
// If we have got this far then declare the height data as healthy and reset the timeout counter
hgtHealth = true;
lastHgtPassTime_ms = imuSampleTime_ms;
}
}
// set range for sequential fusion of velocity and position measurements depending on which data is available and its health
if (fuseVelData && velHealth) {
fuseData[0] = true;
fuseData[1] = true;
if (useGpsVertVel) {
fuseData[2] = true;
}
tiltErrVec.zero();
}
if (fusePosData && posHealth) {
fuseData[3] = true;
fuseData[4] = true;
tiltErrVec.zero();
}
if (fuseHgtData && hgtHealth) {
fuseData[5] = true;
}
// fuse measurements sequentially
for (obsIndex=0; obsIndex<=5; obsIndex++) {
if (fuseData[obsIndex]) {
stateIndex = 3 + obsIndex;
// calculate the measurement innovation, using states from a different time coordinate if fusing height data
// adjust scaling on GPS measurement noise variances if not enough satellites
if (obsIndex <= 2)
{
innovVelPos[obsIndex] = stateStruct.velocity[obsIndex] - observation[obsIndex];
R_OBS[obsIndex] *= sq(gpsNoiseScaler);
}
else if (obsIndex == 3 || obsIndex == 4) {
innovVelPos[obsIndex] = stateStruct.position[obsIndex-3] - observation[obsIndex];
R_OBS[obsIndex] *= sq(gpsNoiseScaler);
} else if (obsIndex == 5) {
innovVelPos[obsIndex] = stateStruct.position[obsIndex-3] - observation[obsIndex];
const float gndMaxBaroErr = 4.0f;
const float gndBaroInnovFloor = -0.5f;
if(getTouchdownExpected()) {
// when a touchdown is expected, floor the barometer innovation at gndBaroInnovFloor
// constrain the correction between 0 and gndBaroInnovFloor+gndMaxBaroErr
// this function looks like this:
// |/
//---------|---------
// ____/|
// / |
// / |
innovVelPos[5] += constrain_float(-innovVelPos[5]+gndBaroInnovFloor, 0.0f, gndBaroInnovFloor+gndMaxBaroErr);
}
}
// calculate the Kalman gain and calculate innovation variances
varInnovVelPos[obsIndex] = P[stateIndex][stateIndex] + R_OBS[obsIndex];
SK = 1.0f/varInnovVelPos[obsIndex];
for (uint8_t i= 0; i<=15; i++) {
Kfusion[i] = P[i][stateIndex]*SK;
}
// inhibit magnetic field state estimation by setting Kalman gains to zero
if (!inhibitMagStates) {
for (uint8_t i = 16; i<=21; i++) {
Kfusion[i] = P[i][stateIndex]*SK;
}
} else {
for (uint8_t i = 16; i<=21; i++) {
Kfusion[i] = 0.0f;
}
}
// inhibit wind state estimation by setting Kalman gains to zero
if (!inhibitWindStates) {
Kfusion[22] = P[22][stateIndex]*SK;
Kfusion[23] = P[23][stateIndex]*SK;
} else {
Kfusion[22] = 0.0f;
Kfusion[23] = 0.0f;
}
// zero the attitude error state - by definition it is assumed to be zero before each observaton fusion
stateStruct.angErr.zero();
// calculate state corrections and re-normalise the quaternions for states predicted using the blended IMU data
for (uint8_t i = 0; i<=stateIndexLim; i++) {
statesArray[i] = statesArray[i] - Kfusion[i] * innovVelPos[obsIndex];
}
// the first 3 states represent the angular misalignment vector. This is
// is used to correct the estimated quaternion
stateStruct.quat.rotate(stateStruct.angErr);
// sum the attitude error from velocity and position fusion only
// used as a metric for convergence monitoring
if (obsIndex != 5) {
tiltErrVec += stateStruct.angErr;
}
// update the covariance - take advantage of direct observation of a single state at index = stateIndex to reduce computations
// this is a numerically optimised implementation of standard equation P = (I - K*H)*P;
for (uint8_t i= 0; i<=stateIndexLim; i++) {
for (uint8_t j= 0; j<=stateIndexLim; j++)
{
KHP[i][j] = Kfusion[i] * P[stateIndex][j];
}
}
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();
// stop performance timer
hal.util->perf_end(_perf_FuseVelPosNED);
}
// select the height measurement to be fused from the available baro, range finder and GPS sources
void NavEKF2_core::selectHeightForFusion()
{
// Read range finder data and check for new data in the buffer
// This data is used by both height and optical flow fusion processing
readRangeFinder();
rangeDataToFuse = storedRange.recall(rangeDataDelayed,imuDataDelayed.time_ms);
// correct range data for the body frame position offset relative to the IMU
// the corrected reading is the reading that would have been taken if the sensor was
// co-located with the IMU
if (rangeDataToFuse) {
AP_RangeFinder_Backend *sensor = frontend->_rng.get_backend(rangeDataDelayed.sensor_idx);
if (sensor != nullptr) {
Vector3f posOffsetBody = sensor->get_pos_offset() - accelPosOffset;
if (!posOffsetBody.is_zero()) {
Vector3f posOffsetEarth = prevTnb.mul_transpose(posOffsetBody);
rangeDataDelayed.rng += posOffsetEarth.z / prevTnb.c.z;
}
}
}
// read baro height data from the sensor and check for new data in the buffer
readBaroData();
baroDataToFuse = storedBaro.recall(baroDataDelayed, imuDataDelayed.time_ms);
// select height source
if (extNavUsedForPos) {
// always use external vision as the hight source if using for position.
activeHgtSource = HGT_SOURCE_EV;
} else if (((frontend->_useRngSwHgt > 0) || (frontend->_altSource == 1)) && (imuSampleTime_ms - rngValidMeaTime_ms < 500)) {
if (frontend->_altSource == 1) {
// always use range finder
activeHgtSource = HGT_SOURCE_RNG;
} else {
// determine if we are above or below the height switch region
float rangeMaxUse = 1e-4f * (float)frontend->_rng.max_distance_cm_orient(ROTATION_PITCH_270) * (float)frontend->_useRngSwHgt;
bool aboveUpperSwHgt = (terrainState - stateStruct.position.z) > rangeMaxUse;
bool belowLowerSwHgt = (terrainState - stateStruct.position.z) < 0.7f * rangeMaxUse;
// If the terrain height is consistent and we are moving slowly, then it can be
// used as a height reference in combination with a range finder
// apply a hysteresis to the speed check to prevent rapid switching
float horizSpeed = norm(stateStruct.velocity.x, stateStruct.velocity.y);
bool dontTrustTerrain = ((horizSpeed > frontend->_useRngSwSpd) && filterStatus.flags.horiz_vel) || !terrainHgtStable;
float trust_spd_trigger = MAX((frontend->_useRngSwSpd - 1.0f),(frontend->_useRngSwSpd * 0.5f));
bool trustTerrain = (horizSpeed < trust_spd_trigger) && terrainHgtStable;
/*
* Switch between range finder and primary height source using height above ground and speed thresholds with
* hysteresis to avoid rapid switching. Using range finder for height requires a consistent terrain height
* which cannot be assumed if the vehicle is moving horizontally.
*/
if ((aboveUpperSwHgt || dontTrustTerrain) && (activeHgtSource == HGT_SOURCE_RNG)) {
// cannot trust terrain or range finder so stop using range finder height
if (frontend->_altSource == 0) {
activeHgtSource = HGT_SOURCE_BARO;
} else if (frontend->_altSource == 2) {
activeHgtSource = HGT_SOURCE_GPS;
}
} else if (belowLowerSwHgt && trustTerrain && (activeHgtSource != HGT_SOURCE_RNG)) {
// reliable terrain and range finder so start using range finder height
activeHgtSource = HGT_SOURCE_RNG;
}
}
} else if ((frontend->_altSource == 2) && ((imuSampleTime_ms - lastTimeGpsReceived_ms) < 500) && validOrigin && gpsAccuracyGood) {
activeHgtSource = HGT_SOURCE_GPS;
} else if ((frontend->_altSource == 3) && validOrigin && rngBcnGoodToAlign) {
activeHgtSource = HGT_SOURCE_BCN;
} else {
activeHgtSource = HGT_SOURCE_BARO;
}
// Use Baro alt as a fallback if we lose range finder, GPS or external nav
bool lostRngHgt = ((activeHgtSource == HGT_SOURCE_RNG) && ((imuSampleTime_ms - rngValidMeaTime_ms) > 500));
bool lostGpsHgt = ((activeHgtSource == HGT_SOURCE_GPS) && ((imuSampleTime_ms - lastTimeGpsReceived_ms) > 2000));
bool lostExtNavHgt = ((activeHgtSource == HGT_SOURCE_EV) && ((imuSampleTime_ms - extNavMeasTime_ms) > 2000));
if (lostRngHgt || lostGpsHgt || lostExtNavHgt) {
activeHgtSource = HGT_SOURCE_BARO;
}
// if there is new baro data to fuse, calculate filtered baro data required by other processes
if (baroDataToFuse) {
// calculate offset to baro data that enables us to switch to Baro height use during operation
if (activeHgtSource != HGT_SOURCE_BARO) {
calcFiltBaroOffset();
}
// filtered baro data used to provide a reference for takeoff
// it is is reset to last height measurement on disarming in performArmingChecks()
if (!getTakeoffExpected()) {
const float gndHgtFiltTC = 0.5f;
const float dtBaro = frontend->hgtAvg_ms*1.0e-3f;
float alpha = constrain_float(dtBaro / (dtBaro+gndHgtFiltTC),0.0f,1.0f);
meaHgtAtTakeOff += (baroDataDelayed.hgt-meaHgtAtTakeOff)*alpha;
}
}
// If we are not using GPS as the primary height sensor, correct EKF origin height so that
// combined local NED position height and origin height remains consistent with the GPS altitude
// This also enables the GPS height to be used as a backup height source
if (gpsDataToFuse &&
(((frontend->_originHgtMode & (1 << 0)) && (activeHgtSource == HGT_SOURCE_BARO)) ||
((frontend->_originHgtMode & (1 << 1)) && (activeHgtSource == HGT_SOURCE_RNG)))
) {
correctEkfOriginHeight();
}
// Select the height measurement source
if (extNavDataToFuse && (activeHgtSource == HGT_SOURCE_EV)) {
hgtMea = -extNavDataDelayed.pos.z;
posDownObsNoise = sq(constrain_float(extNavDataDelayed.posErr, 0.1f, 10.0f));
} else if (rangeDataToFuse && (activeHgtSource == HGT_SOURCE_RNG)) {
// using range finder data
// correct for tilt using a flat earth model
if (prevTnb.c.z >= 0.7) {
// calculate height above ground
hgtMea = MAX(rangeDataDelayed.rng * prevTnb.c.z, rngOnGnd);
// correct for terrain position relative to datum
hgtMea -= terrainState;
// enable fusion
fuseHgtData = true;
velPosObs[5] = -hgtMea;
// set the observation noise
posDownObsNoise = sq(constrain_float(frontend->_rngNoise, 0.1f, 10.0f));
// add uncertainty created by terrain gradient and vehicle tilt
posDownObsNoise += sq(rangeDataDelayed.rng * frontend->_terrGradMax) * MAX(0.0f , (1.0f - sq(prevTnb.c.z)));
} else {
// disable fusion if tilted too far
fuseHgtData = false;
}
} else if (gpsDataToFuse && (activeHgtSource == HGT_SOURCE_GPS)) {
// using GPS data
hgtMea = gpsDataDelayed.hgt;
// enable fusion
velPosObs[5] = -hgtMea;
fuseHgtData = true;
// set the observation noise using receiver reported accuracy or the horizontal noise scaled for typical VDOP/HDOP ratio
if (gpsHgtAccuracy > 0.0f) {
posDownObsNoise = sq(constrain_float(gpsHgtAccuracy, 1.5f * frontend->_gpsHorizPosNoise, 100.0f));
} else {
posDownObsNoise = sq(constrain_float(1.5f * frontend->_gpsHorizPosNoise, 0.1f, 10.0f));
}
} else if (baroDataToFuse && (activeHgtSource == HGT_SOURCE_BARO)) {
// using Baro data
hgtMea = baroDataDelayed.hgt - baroHgtOffset;
// enable fusion
velPosObs[5] = -hgtMea;
fuseHgtData = true;
// set the observation noise
posDownObsNoise = sq(constrain_float(frontend->_baroAltNoise, 0.1f, 10.0f));
// reduce weighting (increase observation noise) on baro if we are likely to be in ground effect
if (getTakeoffExpected() || getTouchdownExpected()) {
posDownObsNoise *= frontend->gndEffectBaroScaler;
}
// If we are in takeoff mode, the height measurement is limited to be no less than the measurement at start of takeoff
// This prevents negative baro disturbances due to copter downwash corrupting the EKF altitude during initial ascent
if (motorsArmed && getTakeoffExpected()) {
hgtMea = MAX(hgtMea, meaHgtAtTakeOff);
}
} else {
fuseHgtData = false;
}
// If we haven't fused height data for a while, then declare the height data as being timed out
// set timeout period based on whether we have vertical GPS velocity available to constrain drift
hgtRetryTime_ms = (useGpsVertVel && !velTimeout) ? frontend->hgtRetryTimeMode0_ms : frontend->hgtRetryTimeMode12_ms;
if (imuSampleTime_ms - lastHgtPassTime_ms > hgtRetryTime_ms) {
hgtTimeout = true;
} else {
hgtTimeout = false;
}
}
