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ekf2: refactor wind reset functions
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@ -96,8 +96,7 @@ void Ekf::fuseAirspeed()
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const char *action_string = nullptr;
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if (update_wind_only) {
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resetWindStates();
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resetWindCovariance();
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resetWindUsingAirspeed();
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action_string = "wind";
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} else {
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@ -173,22 +172,38 @@ float Ekf::getTrueAirspeed() const
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return (_state.vel - Vector3f(_state.wind_vel(0), _state.wind_vel(1), 0.f)).norm();
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}
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void Ekf::resetWind()
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{
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if (_control_status.flags.fuse_aspd) {
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resetWindUsingAirspeed();
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} else {
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resetWindToZero();
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}
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}
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/*
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* Reset the wind states using the current airspeed measurement, ground relative nav velocity, yaw angle and assumption of zero sideslip
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*/
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void Ekf::resetWindStates()
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void Ekf::resetWindUsingAirspeed()
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{
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const float euler_yaw = shouldUse321RotationSequence(_R_to_earth)
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? getEuler321Yaw(_state.quat_nominal)
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: getEuler312Yaw(_state.quat_nominal);
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if (_tas_data_ready && (_imu_sample_delayed.time_us - _airspeed_sample_delayed.time_us < (uint64_t)5e5)) {
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// estimate wind using zero sideslip assumption and airspeed measurement if airspeed available
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_state.wind_vel(0) = _state.vel(0) - _airspeed_sample_delayed.true_airspeed * cosf(euler_yaw);
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_state.wind_vel(1) = _state.vel(1) - _airspeed_sample_delayed.true_airspeed * sinf(euler_yaw);
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// estimate wind using zero sideslip assumption and airspeed measurement if airspeed available
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_state.wind_vel(0) = _state.vel(0) - _airspeed_sample_delayed.true_airspeed * cosf(euler_yaw);
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_state.wind_vel(1) = _state.vel(1) - _airspeed_sample_delayed.true_airspeed * sinf(euler_yaw);
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} else {
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// If we don't have an airspeed measurement, then assume the wind is zero
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_state.wind_vel.setZero();
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}
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resetWindCovarianceUsingAirspeed();
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_time_last_arsp_fuse = _time_last_imu;
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}
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void Ekf::resetWindToZero()
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{
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// If we don't have an airspeed measurement, then assume the wind is zero
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_state.wind_vel.setZero();
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// start with a small initial uncertainty to improve the initial estimate
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P.uncorrelateCovarianceSetVariance<2>(22, _params.initial_wind_uncertainty);
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}
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@ -1333,17 +1333,7 @@ void Ekf::controlAirDataFusion()
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}
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} else if (starting_conditions_passing) {
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// If starting wind state estimation, reset the wind states and covariances before fusing any data
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if (!_control_status.flags.wind) {
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// activate the wind states
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_control_status.flags.wind = true;
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// reset the wind speed states and corresponding covariances
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resetWindStates();
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resetWindCovariance();
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}
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startAirspeedFusion();
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_time_last_arsp_fuse = _time_last_imu;
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}
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} else if (_control_status.flags.fuse_aspd && (_imu_sample_delayed.time_us - _airspeed_sample_delayed.time_us > (uint64_t) 1e6)) {
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@ -1370,9 +1360,7 @@ void Ekf::controlBetaFusion()
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_control_status.flags.wind = true;
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// reset the timeout timers to prevent repeated resets
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_time_last_beta_fuse = _time_last_imu;
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// reset the wind speed states and corresponding covariances
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resetWindStates();
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resetWindCovariance();
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resetWind();
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}
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fuseSideslip();
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@ -1389,8 +1377,7 @@ void Ekf::controlDragFusion()
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if (!_control_status.flags.wind) {
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// reset the wind states and covariances when starting drag accel fusion
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_control_status.flags.wind = true;
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resetWindStates();
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resetWindCovariance();
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resetWind();
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} else if (_drag_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_drag_sample_delayed)) {
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fuseDrag();
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@ -1140,39 +1140,33 @@ void Ekf::resetZDeltaAngBiasCov()
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P.uncorrelateCovarianceSetVariance<1>(12, init_delta_ang_bias_var);
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}
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void Ekf::resetWindCovariance()
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void Ekf::resetWindCovarianceUsingAirspeed()
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{
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if (_tas_data_ready && (_imu_sample_delayed.time_us - _airspeed_sample_delayed.time_us < (uint64_t)5e5)) {
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// Derived using EKF/matlab/scripts/Inertial Nav EKF/wind_cov.py
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// TODO: explicitly include the sideslip angle in the derivation
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const float euler_yaw = getEuler321Yaw(_state.quat_nominal);
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const float R_TAS = sq(math::constrain(_params.eas_noise, 0.5f, 5.0f) * math::constrain(_airspeed_sample_delayed.eas2tas, 0.9f, 10.0f));
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constexpr float initial_sideslip_uncertainty = math::radians(15.0f);
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const float initial_wind_var_body_y = sq(_airspeed_sample_delayed.true_airspeed * sinf(initial_sideslip_uncertainty));
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constexpr float R_yaw = sq(math::radians(10.0f));
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// Derived using EKF/matlab/scripts/Inertial Nav EKF/wind_cov.py
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// TODO: explicitly include the sideslip angle in the derivation
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const float euler_yaw = getEuler321Yaw(_state.quat_nominal);
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const float R_TAS = sq(math::constrain(_params.eas_noise, 0.5f, 5.0f) * math::constrain(_airspeed_sample_delayed.eas2tas, 0.9f, 10.0f));
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constexpr float initial_sideslip_uncertainty = math::radians(15.0f);
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const float initial_wind_var_body_y = sq(_airspeed_sample_delayed.true_airspeed * sinf(initial_sideslip_uncertainty));
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constexpr float R_yaw = sq(math::radians(10.0f));
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const float cos_yaw = cosf(euler_yaw);
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const float sin_yaw = sinf(euler_yaw);
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const float cos_yaw = cosf(euler_yaw);
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const float sin_yaw = sinf(euler_yaw);
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// rotate wind velocity into earth frame aligned with vehicle yaw
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const float Wx = _state.wind_vel(0) * cos_yaw + _state.wind_vel(1) * sin_yaw;
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const float Wy = -_state.wind_vel(0) * sin_yaw + _state.wind_vel(1) * cos_yaw;
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// rotate wind velocity into earth frame aligned with vehicle yaw
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const float Wx = _state.wind_vel(0) * cos_yaw + _state.wind_vel(1) * sin_yaw;
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const float Wy = -_state.wind_vel(0) * sin_yaw + _state.wind_vel(1) * cos_yaw;
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// it is safer to remove all existing correlations to other states at this time
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P.uncorrelateCovarianceSetVariance<2>(22, 0.0f);
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// it is safer to remove all existing correlations to other states at this time
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P.uncorrelateCovarianceSetVariance<2>(22, 0.0f);
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P(22, 22) = R_TAS * sq(cos_yaw) + R_yaw * sq(-Wx * sin_yaw - Wy * cos_yaw) + initial_wind_var_body_y * sq(sin_yaw);
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P(22, 23) = R_TAS * sin_yaw * cos_yaw + R_yaw * (-Wx * sin_yaw - Wy * cos_yaw) * (Wx * cos_yaw - Wy * sin_yaw) -
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initial_wind_var_body_y * sin_yaw * cos_yaw;
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P(23, 22) = P(22, 23);
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P(23, 23) = R_TAS * sq(sin_yaw) + R_yaw * sq(Wx * cos_yaw - Wy * sin_yaw) + initial_wind_var_body_y * sq(cos_yaw);
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P(22, 22) = R_TAS * sq(cos_yaw) + R_yaw * sq(-Wx * sin_yaw - Wy * cos_yaw) + initial_wind_var_body_y * sq(sin_yaw);
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P(22, 23) = R_TAS * sin_yaw * cos_yaw + R_yaw * (-Wx * sin_yaw - Wy * cos_yaw) * (Wx * cos_yaw - Wy * sin_yaw) -
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initial_wind_var_body_y * sin_yaw * cos_yaw;
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P(23, 22) = P(22, 23);
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P(23, 23) = R_TAS * sq(sin_yaw) + R_yaw * sq(Wx * cos_yaw - Wy * sin_yaw) + initial_wind_var_body_y * sq(cos_yaw);
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// Now add the variance due to uncertainty in vehicle velocity that was used to calculate the initial wind speed
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P(22, 22) += P(4, 4);
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P(23, 23) += P(5, 5);
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} else {
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// without airspeed, start with a small initial uncertainty to improve the initial estimate
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P.uncorrelateCovarianceSetVariance<2>(22, _params.initial_wind_uncertainty);
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}
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// Now add the variance due to uncertainty in vehicle velocity that was used to calculate the initial wind speed
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P(22, 22) += P(4, 4);
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P(23, 23) += P(5, 5);
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}
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@ -917,10 +917,12 @@ private:
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void resetMagCov();
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// perform a limited reset of the wind state covariances
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void resetWindCovariance();
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void resetWindCovarianceUsingAirspeed();
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// perform a reset of the wind states
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void resetWindStates();
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// perform a reset of the wind states and related covariances
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void resetWind();
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void resetWindUsingAirspeed();
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void resetWindToZero();
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// check that the range finder data is continuous
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void updateRangeDataContinuity();
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@ -1480,11 +1480,21 @@ void Ekf::loadMagCovData()
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P.slice<2, 2>(16, 16) = _saved_mag_ef_covmat;
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}
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void Ekf::startAirspeedFusion() {
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void Ekf::startAirspeedFusion()
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{
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// If starting wind state estimation, reset the wind states and covariances before fusing any data
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if (!_control_status.flags.wind) {
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// activate the wind states
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_control_status.flags.wind = true;
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// reset the wind speed states and corresponding covariances
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resetWindUsingAirspeed();
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}
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_control_status.flags.fuse_aspd = true;
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}
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void Ekf::stopAirspeedFusion() {
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void Ekf::stopAirspeedFusion()
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{
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_control_status.flags.fuse_aspd = false;
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}
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@ -140,8 +140,7 @@ void Ekf::fuseSideslip()
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const char *action_string = nullptr;
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if (update_wind_only) {
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resetWindStates();
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resetWindCovariance();
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resetWind();
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action_string = "wind";
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} else {
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