// 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);
}
/* Event handler for the details form */
Boolean DetailsFormHandleEvent
(
EventType* event /* pointer to an EventType structure */
)
{
Boolean handled;
Boolean update;
handled = false;
update = false;
switch ( event->eType ) {
case ctlSelectEvent:
if ( event->data.ctlEnter.controlID == frmDetailsOK ) {
UInt16 reference;
Boolean oldStatus;
Boolean newStatus;
reference = GetHistoryCurrent();
oldStatus = ShowImages( reference );
newStatus = CtlGetValue( GetObjectPtr( frmDetailsShowImages ) );
update = oldStatus ^ newStatus;
if ( newStatus )
ShowImagesOn( reference );
else
ShowImagesOff( reference );
if ( CtlGetValue( GetObjectPtr( frmDetailsStatusRead ) ) )
SetVisitedLink( reference );
else
UnsetVisitedLink( reference );
}
else if ( event->data.ctlEnter.controlID == frmDetailsCopy ) {
FieldType* field;
field = GetObjectPtr( frmDetailsLink );
WriteTextFieldToMemo( field );
}
else if ( event->data.ctlEnter.controlID != frmDetailsCancel ) {
break;
}
FrmReturnToForm( PREVIOUS_FORM );
if ( update ) {
ResetHeight();
FrmUpdateForm( GetMainFormId(), frmRedrawUpdateCode );
}
handled = true;
break;
case winEnterEvent:
handled = ResizeHandleWinEnterEvent();
break;
case winDisplayChangedEvent:
handled = ResizeHandleWinDisplayChangedEvent();
break;
case winExitEvent:
handled = ResizeHandleWinExitEvent();
break;
case frmOpenEvent:
#ifdef HAVE_SILKSCREEN
ResizeHandleFrmOpenEvent();
#endif
DetailsFormInit();
handled = true;
break;
case frmCloseEvent:
#ifdef HAVE_SILKSCREEN
ResizeHandleFrmCloseEvent();
#endif
handled = false;
break;
default:
handled = false;
}
return handled;
}
// Set inertial navigation aiding mode
void NavEKF2_core::setAidingMode()
{
// Save the previous status so we can detect when it has changed
PV_AidingModePrev = PV_AidingMode;
// Determine if we should change aiding mode
switch (PV_AidingMode) {
case AID_NONE: {
// Don't allow filter to start position or velocity aiding until the tilt and yaw alignment is complete
// and IMU gyro bias estimates have stabilised
bool filterIsStable = tiltAlignComplete && yawAlignComplete && checkGyroCalStatus();
// If GPS usage has been prohiited then we use flow aiding provided optical flow data is present
// GPS aiding is the preferred option unless excluded by the user
bool canUseGPS = ((frontend->_fusionModeGPS) != 3 && readyToUseGPS() && filterIsStable && !gpsInhibit);
bool canUseRangeBeacon = readyToUseRangeBeacon() && filterIsStable;
bool canUseExtNav = readyToUseExtNav();
if(canUseGPS || canUseRangeBeacon || canUseExtNav) {
PV_AidingMode = AID_ABSOLUTE;
} else if (optFlowDataPresent() && filterIsStable) {
PV_AidingMode = AID_RELATIVE;
}
}
break;
case AID_RELATIVE: {
// Check if the optical flow sensor has timed out
bool flowSensorTimeout = ((imuSampleTime_ms - flowValidMeaTime_ms) > 5000);
// Check if the fusion has timed out (flow measurements have been rejected for too long)
bool flowFusionTimeout = ((imuSampleTime_ms - prevFlowFuseTime_ms) > 5000);
// Enable switch to absolute position mode if GPS is available
// If GPS is not available and flow fusion has timed out, then fall-back to no-aiding
if((frontend->_fusionModeGPS) != 3 && readyToUseGPS() && !gpsInhibit) {
PV_AidingMode = AID_ABSOLUTE;
} else if (flowSensorTimeout || flowFusionTimeout) {
PV_AidingMode = AID_NONE;
}
}
break;
case AID_ABSOLUTE: {
// Find the minimum time without data required to trigger any check
uint16_t minTestTime_ms = MIN(frontend->tiltDriftTimeMax_ms, MIN(frontend->posRetryTimeNoVel_ms,frontend->posRetryTimeUseVel_ms));
// Check if optical flow data is being used
bool optFlowUsed = (imuSampleTime_ms - prevFlowFuseTime_ms <= minTestTime_ms);
// Check if airspeed data is being used
bool airSpdUsed = (imuSampleTime_ms - lastTasPassTime_ms <= minTestTime_ms);
// Check if range beacon data is being used
bool rngBcnUsed = (imuSampleTime_ms - lastRngBcnPassTime_ms <= minTestTime_ms);
// Check if GPS is being used
bool posUsed = (imuSampleTime_ms - lastPosPassTime_ms <= minTestTime_ms);
bool gpsVelUsed = (imuSampleTime_ms - lastVelPassTime_ms <= minTestTime_ms);
// Check if attitude drift has been constrained by a measurement source
bool attAiding = posUsed || gpsVelUsed || optFlowUsed || airSpdUsed || rngBcnUsed;
// check if velocity drift has been constrained by a measurement source
bool velAiding = gpsVelUsed || airSpdUsed || optFlowUsed;
// check if position drift has been constrained by a measurement source
bool posAiding = posUsed || rngBcnUsed;
// Check if the loss of attitude aiding has become critical
bool attAidLossCritical = false;
if (!attAiding) {
attAidLossCritical = (imuSampleTime_ms - prevFlowFuseTime_ms > frontend->tiltDriftTimeMax_ms) &&
(imuSampleTime_ms - lastTasPassTime_ms > frontend->tiltDriftTimeMax_ms) &&
(imuSampleTime_ms - lastRngBcnPassTime_ms > frontend->tiltDriftTimeMax_ms) &&
(imuSampleTime_ms - lastPosPassTime_ms > frontend->tiltDriftTimeMax_ms) &&
(imuSampleTime_ms - lastVelPassTime_ms > frontend->tiltDriftTimeMax_ms);
}
// Check if the loss of position accuracy has become critical
bool posAidLossCritical = false;
if (!posAiding ) {
uint16_t maxLossTime_ms;
if (!velAiding) {
maxLossTime_ms = frontend->posRetryTimeNoVel_ms;
} else {
maxLossTime_ms = frontend->posRetryTimeUseVel_ms;
}
posAidLossCritical = (imuSampleTime_ms - lastRngBcnPassTime_ms > maxLossTime_ms) &&
(imuSampleTime_ms - lastPosPassTime_ms > maxLossTime_ms);
}
if (attAidLossCritical) {
// if the loss of attitude data is critical, then put the filter into a constant position mode
PV_AidingMode = AID_NONE;
posTimeout = true;
velTimeout = true;
rngBcnTimeout = true;
tasTimeout = true;
gpsNotAvailable = true;
} else if (posAidLossCritical) {
// if the loss of position is critical, declare all sources of position aiding as being timed out
posTimeout = true;
velTimeout = true;
rngBcnTimeout = true;
gpsNotAvailable = true;
}
break;
}
}
// check to see if we are starting or stopping aiding and set states and modes as required
if (PV_AidingMode != PV_AidingModePrev) {
// set various usage modes based on the condition when we start aiding. These are then held until aiding is stopped.
switch (PV_AidingMode) {
case AID_NONE:
// We have ceased aiding
gcs().send_text(MAV_SEVERITY_WARNING, "EKF2 IMU%u has stopped aiding",(unsigned)imu_index);
// When not aiding, estimate orientation & height fusing synthetic constant position and zero velocity measurement to constrain tilt errors
posTimeout = true;
velTimeout = true;
// Reset the normalised innovation to avoid false failing bad fusion tests
velTestRatio = 0.0f;
posTestRatio = 0.0f;
// store the current position to be used to keep reporting the last known position
lastKnownPositionNE.x = stateStruct.position.x;
lastKnownPositionNE.y = stateStruct.position.y;
// initialise filtered altitude used to provide a takeoff reference to current baro on disarm
// this reduces the time required for the baro noise filter to settle before the filtered baro data can be used
meaHgtAtTakeOff = baroDataDelayed.hgt;
// reset the vertical position state to faster recover from baro errors experienced during touchdown
stateStruct.position.z = -meaHgtAtTakeOff;
break;
case AID_RELATIVE:
// We have commenced aiding, but GPS usage has been prohibited so use optical flow only
gcs().send_text(MAV_SEVERITY_INFO, "EKF2 IMU%u is using optical flow",(unsigned)imu_index);
posTimeout = true;
velTimeout = true;
// Reset the last valid flow measurement time
flowValidMeaTime_ms = imuSampleTime_ms;
// Reset the last valid flow fusion time
prevFlowFuseTime_ms = imuSampleTime_ms;
break;
case AID_ABSOLUTE: {
bool canUseGPS = ((frontend->_fusionModeGPS) != 3 && readyToUseGPS() && !gpsInhibit);
bool canUseRangeBeacon = readyToUseRangeBeacon();
bool canUseExtNav = readyToUseExtNav();
// We have commenced aiding and GPS usage is allowed
if (canUseGPS) {
gcs().send_text(MAV_SEVERITY_INFO, "EKF2 IMU%u is using GPS",(unsigned)imu_index);
}
posTimeout = false;
velTimeout = false;
// We have commenced aiding and range beacon usage is allowed
if (canUseRangeBeacon) {
gcs().send_text(MAV_SEVERITY_INFO, "EKF2 IMU%u is using range beacons",(unsigned)imu_index);
gcs().send_text(MAV_SEVERITY_INFO, "EKF2 IMU%u initial pos NE = %3.1f,%3.1f (m)",(unsigned)imu_index,(double)receiverPos.x,(double)receiverPos.y);
gcs().send_text(MAV_SEVERITY_INFO, "EKF2 IMU%u initial beacon pos D offset = %3.1f (m)",(unsigned)imu_index,(double)bcnPosOffset);
}
// We have commenced aiding and external nav usage is allowed
if (canUseExtNav) {
gcs().send_text(MAV_SEVERITY_INFO, "EKF2 IMU%u is using external nav data",(unsigned)imu_index);
gcs().send_text(MAV_SEVERITY_INFO, "EKF2 IMU%u initial pos NED = %3.1f,%3.1f,%3.1f (m)",(unsigned)imu_index,(double)extNavDataDelayed.pos.x,(double)extNavDataDelayed.pos.y,(double)extNavDataDelayed.pos.z);
// handle yaw reset as special case
extNavYawResetRequest = true;
controlMagYawReset();
// handle height reset as special case
hgtMea = -extNavDataDelayed.pos.z;
posDownObsNoise = sq(constrain_float(extNavDataDelayed.posErr, 0.1f, 10.0f));
ResetHeight();
}
// reset the last fusion accepted times to prevent unwanted activation of timeout logic
lastPosPassTime_ms = imuSampleTime_ms;
lastVelPassTime_ms = imuSampleTime_ms;
lastRngBcnPassTime_ms = imuSampleTime_ms;
}
break;
}
// Always reset the position and velocity when changing mode
ResetVelocity();
ResetPosition();
}
}
