/**************************************************************************** * * Copyright (c) 2015 Estimation and Control Library (ECL). All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in * the documentation and/or other materials provided with the * distribution. * 3. Neither the name ECL nor the names of its contributors may be * used to endorse or promote products derived from this software * without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS * OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED * AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE * POSSIBILITY OF SUCH DAMAGE. * ****************************************************************************/ /** * @file airspeed_fusion.cpp * airspeed fusion methods. * * @author Carl Olsson * @author Roman Bast * @author Paul Riseborough * */ #include "../ecl.h" #include "ekf.h" #include void Ekf::fuseAirspeed() { // Initialize variables float vn; // Velocity in north direction float ve; // Velocity in east direction float vd; // Velocity in downwards direction float vwn; // Wind speed in north direction float vwe; // Wind speed in east direction float v_tas_pred; // Predicted measurement float R_TAS = sq(math::constrain(_params.eas_noise, 0.5f, 5.0f) * math::constrain(_airspeed_sample_delayed.eas2tas, 0.9f, 10.0f)); // Variance for true airspeed measurement - (m/sec)^2 float SH_TAS[3] = {}; // Variable used to optimise calculations of measurement jacobian float H_TAS[24] = {}; // Observation Jacobian float SK_TAS[2] = {}; // Variable used to optimise calculations of the Kalman gain vector float Kfusion[24] = {}; // Kalman gain vector // Copy required states to local variable names vn = _state.vel(0); ve = _state.vel(1); vd = _state.vel(2); vwn = _state.wind_vel(0); vwe = _state.wind_vel(1); // Calculate the predicted airspeed v_tas_pred = sqrtf((ve - vwe) * (ve - vwe) + (vn - vwn) * (vn - vwn) + vd * vd); // Perform fusion of True Airspeed measurement if (v_tas_pred > 1.0f) { // determine if we need the sideslip fusion to correct states other than wind bool update_wind_only = !_is_wind_dead_reckoning; // Calculate the observation jacobian // intermediate variable from algebraic optimisation SH_TAS[0] = 1.0f/v_tas_pred; SH_TAS[1] = (SH_TAS[0]*(2.0f*ve - 2.0f*vwe))*0.5f; SH_TAS[2] = (SH_TAS[0]*(2.0f*vn - 2.0f*vwn))*0.5f; for (uint8_t i = 0; i < _k_num_states; i++) { H_TAS[i] = 0.0f; } H_TAS[4] = SH_TAS[2]; H_TAS[5] = SH_TAS[1]; H_TAS[6] = vd*SH_TAS[0]; H_TAS[22] = -SH_TAS[2]; H_TAS[23] = -SH_TAS[1]; // We don't want to update the innovation variance if the calculation is ill conditioned float _airspeed_innov_var_temp = (R_TAS + SH_TAS[2]*(P[4][4]*SH_TAS[2] + P[5][4]*SH_TAS[1] - P[22][4]*SH_TAS[2] - P[23][4]*SH_TAS[1] + P[6][4]*vd*SH_TAS[0]) + SH_TAS[1]*(P[4][5]*SH_TAS[2] + P[5][5]*SH_TAS[1] - P[22][5]*SH_TAS[2] - P[23][5]*SH_TAS[1] + P[6][5]*vd*SH_TAS[0]) - SH_TAS[2]*(P[4][22]*SH_TAS[2] + P[5][22]*SH_TAS[1] - P[22][22]*SH_TAS[2] - P[23][22]*SH_TAS[1] + P[6][22]*vd*SH_TAS[0]) - SH_TAS[1]*(P[4][23]*SH_TAS[2] + P[5][23]*SH_TAS[1] - P[22][23]*SH_TAS[2] - P[23][23]*SH_TAS[1] + P[6][23]*vd*SH_TAS[0]) + vd*SH_TAS[0]*(P[4][6]*SH_TAS[2] + P[5][6]*SH_TAS[1] - P[22][6]*SH_TAS[2] - P[23][6]*SH_TAS[1] + P[6][6]*vd*SH_TAS[0])); if (_airspeed_innov_var_temp >= R_TAS) { // Check for badly conditioned calculation SK_TAS[0] = 1.0f / _airspeed_innov_var_temp; _fault_status.flags.bad_airspeed = false; } else { // Reset the estimator covariance matrix _fault_status.flags.bad_airspeed = true; // if we are getting aiding from other sources, warn and reset the wind states and covariances only if (update_wind_only) { resetWindStates(); resetWindCovariance(); ECL_ERR_TIMESTAMPED("EKF airspeed fusion badly conditioned - wind covariance reset"); } else { initialiseCovariance(); _state.wind_vel.setZero(); ECL_ERR_TIMESTAMPED("EKF airspeed fusion badly conditioned - full covariance reset"); } return; } SK_TAS[1] = SH_TAS[1]; if (update_wind_only) { // If we are getting aiding from other sources, then don't allow the airspeed measurements to affect the non-windspeed states for (unsigned row = 0; row <= 21; row++) { Kfusion[row] = 0.0f; } } else { // we have no other source of aiding, so use airspeed measurements to correct states Kfusion[0] = SK_TAS[0]*(P[0][4]*SH_TAS[2] - P[0][22]*SH_TAS[2] + P[0][5]*SK_TAS[1] - P[0][23]*SK_TAS[1] + P[0][6]*vd*SH_TAS[0]); Kfusion[1] = SK_TAS[0]*(P[1][4]*SH_TAS[2] - P[1][22]*SH_TAS[2] + P[1][5]*SK_TAS[1] - P[1][23]*SK_TAS[1] + P[1][6]*vd*SH_TAS[0]); Kfusion[2] = SK_TAS[0]*(P[2][4]*SH_TAS[2] - P[2][22]*SH_TAS[2] + P[2][5]*SK_TAS[1] - P[2][23]*SK_TAS[1] + P[2][6]*vd*SH_TAS[0]); Kfusion[3] = SK_TAS[0]*(P[3][4]*SH_TAS[2] - P[3][22]*SH_TAS[2] + P[3][5]*SK_TAS[1] - P[3][23]*SK_TAS[1] + P[3][6]*vd*SH_TAS[0]); Kfusion[4] = SK_TAS[0]*(P[4][4]*SH_TAS[2] - P[4][22]*SH_TAS[2] + P[4][5]*SK_TAS[1] - P[4][23]*SK_TAS[1] + P[4][6]*vd*SH_TAS[0]); Kfusion[5] = SK_TAS[0]*(P[5][4]*SH_TAS[2] - P[5][22]*SH_TAS[2] + P[5][5]*SK_TAS[1] - P[5][23]*SK_TAS[1] + P[5][6]*vd*SH_TAS[0]); Kfusion[6] = SK_TAS[0]*(P[6][4]*SH_TAS[2] - P[6][22]*SH_TAS[2] + P[6][5]*SK_TAS[1] - P[6][23]*SK_TAS[1] + P[6][6]*vd*SH_TAS[0]); Kfusion[7] = SK_TAS[0]*(P[7][4]*SH_TAS[2] - P[7][22]*SH_TAS[2] + P[7][5]*SK_TAS[1] - P[7][23]*SK_TAS[1] + P[7][6]*vd*SH_TAS[0]); Kfusion[8] = SK_TAS[0]*(P[8][4]*SH_TAS[2] - P[8][22]*SH_TAS[2] + P[8][5]*SK_TAS[1] - P[8][23]*SK_TAS[1] + P[8][6]*vd*SH_TAS[0]); Kfusion[9] = SK_TAS[0]*(P[9][4]*SH_TAS[2] - P[9][22]*SH_TAS[2] + P[9][5]*SK_TAS[1] - P[9][23]*SK_TAS[1] + P[9][6]*vd*SH_TAS[0]); Kfusion[10] = SK_TAS[0]*(P[10][4]*SH_TAS[2] - P[10][22]*SH_TAS[2] + P[10][5]*SK_TAS[1] - P[10][23]*SK_TAS[1] + P[10][6]*vd*SH_TAS[0]); Kfusion[11] = SK_TAS[0]*(P[11][4]*SH_TAS[2] - P[11][22]*SH_TAS[2] + P[11][5]*SK_TAS[1] - P[11][23]*SK_TAS[1] + P[11][6]*vd*SH_TAS[0]); Kfusion[12] = SK_TAS[0]*(P[12][4]*SH_TAS[2] - P[12][22]*SH_TAS[2] + P[12][5]*SK_TAS[1] - P[12][23]*SK_TAS[1] + P[12][6]*vd*SH_TAS[0]); Kfusion[13] = SK_TAS[0]*(P[13][4]*SH_TAS[2] - P[13][22]*SH_TAS[2] + P[13][5]*SK_TAS[1] - P[13][23]*SK_TAS[1] + P[13][6]*vd*SH_TAS[0]); Kfusion[14] = SK_TAS[0]*(P[14][4]*SH_TAS[2] - P[14][22]*SH_TAS[2] + P[14][5]*SK_TAS[1] - P[14][23]*SK_TAS[1] + P[14][6]*vd*SH_TAS[0]); Kfusion[15] = SK_TAS[0]*(P[15][4]*SH_TAS[2] - P[15][22]*SH_TAS[2] + P[15][5]*SK_TAS[1] - P[15][23]*SK_TAS[1] + P[15][6]*vd*SH_TAS[0]); Kfusion[16] = SK_TAS[0]*(P[16][4]*SH_TAS[2] - P[16][22]*SH_TAS[2] + P[16][5]*SK_TAS[1] - P[16][23]*SK_TAS[1] + P[16][6]*vd*SH_TAS[0]); Kfusion[17] = SK_TAS[0]*(P[17][4]*SH_TAS[2] - P[17][22]*SH_TAS[2] + P[17][5]*SK_TAS[1] - P[17][23]*SK_TAS[1] + P[17][6]*vd*SH_TAS[0]); Kfusion[18] = SK_TAS[0]*(P[18][4]*SH_TAS[2] - P[18][22]*SH_TAS[2] + P[18][5]*SK_TAS[1] - P[18][23]*SK_TAS[1] + P[18][6]*vd*SH_TAS[0]); Kfusion[19] = SK_TAS[0]*(P[19][4]*SH_TAS[2] - P[19][22]*SH_TAS[2] + P[19][5]*SK_TAS[1] - P[19][23]*SK_TAS[1] + P[19][6]*vd*SH_TAS[0]); Kfusion[20] = SK_TAS[0]*(P[20][4]*SH_TAS[2] - P[20][22]*SH_TAS[2] + P[20][5]*SK_TAS[1] - P[20][23]*SK_TAS[1] + P[20][6]*vd*SH_TAS[0]); Kfusion[21] = SK_TAS[0]*(P[21][4]*SH_TAS[2] - P[21][22]*SH_TAS[2] + P[21][5]*SK_TAS[1] - P[21][23]*SK_TAS[1] + P[21][6]*vd*SH_TAS[0]); } Kfusion[22] = SK_TAS[0]*(P[22][4]*SH_TAS[2] - P[22][22]*SH_TAS[2] + P[22][5]*SK_TAS[1] - P[22][23]*SK_TAS[1] + P[22][6]*vd*SH_TAS[0]); Kfusion[23] = SK_TAS[0]*(P[23][4]*SH_TAS[2] - P[23][22]*SH_TAS[2] + P[23][5]*SK_TAS[1] - P[23][23]*SK_TAS[1] + P[23][6]*vd*SH_TAS[0]); // Calculate measurement innovation _airspeed_innov = v_tas_pred - _airspeed_sample_delayed.true_airspeed; // Calculate the innovation variance _airspeed_innov_var = 1.0f / SK_TAS[0]; // Compute the ratio of innovation to gate size _tas_test_ratio = sq(_airspeed_innov) / (sq(fmaxf(_params.tas_innov_gate, 1.0f)) * _airspeed_innov_var); // If the innovation consistency check fails then don't fuse the sample and indicate bad airspeed health if (_tas_test_ratio > 1.0f) { _innov_check_fail_status.flags.reject_airspeed = true; return; } else { _innov_check_fail_status.flags.reject_airspeed = false; } // Airspeed measurement sample has passed check so record it _time_last_arsp_fuse = _time_last_imu; // apply covariance correction via P_new = (I -K*H)*P // first calculate expression for KHP // then calculate P - KHP float KHP[_k_num_states][_k_num_states]; float KH[5]; for (unsigned row = 0; row < _k_num_states; row++) { KH[0] = Kfusion[row] * H_TAS[4]; KH[1] = Kfusion[row] * H_TAS[5]; KH[2] = Kfusion[row] * H_TAS[6]; KH[3] = Kfusion[row] * H_TAS[22]; KH[4] = Kfusion[row] * H_TAS[23]; for (unsigned column = 0; column < _k_num_states; column++) { float tmp = KH[0] * P[4][column]; tmp += KH[1] * P[5][column]; tmp += KH[2] * P[6][column]; tmp += KH[3] * P[22][column]; tmp += KH[4] * P[23][column]; KHP[row][column] = tmp; } } // if the covariance correction will result in a negative variance, then // the covariance matrix is unhealthy and must be corrected bool healthy = true; _fault_status.flags.bad_airspeed = false; for (int i = 0; i < _k_num_states; i++) { if (P[i][i] < KHP[i][i]) { // zero rows and columns zeroRows(P, i, i); zeroCols(P, i, i); //flag as unhealthy healthy = false; // update individual measurement health status _fault_status.flags.bad_airspeed = true; } } // only apply covariance and state corrections if healthy if (healthy) { // apply the covariance corrections for (unsigned row = 0; row < _k_num_states; row++) { for (unsigned column = 0; column < _k_num_states; column++) { P[row][column] = P[row][column] - KHP[row][column]; } } // correct the covariance matrix for gross errors fixCovarianceErrors(); // apply the state corrections fuse(Kfusion, _airspeed_innov); } } } void Ekf::get_wind_velocity(float *wind) { wind[0] = _state.wind_vel(0); wind[1] = _state.wind_vel(1); } void Ekf::get_wind_velocity_var(float *wind_var) { wind_var[0] = P[22][22]; wind_var[1] = P[23][23]; } void Ekf::get_true_airspeed(float *tas) { float tempvar = sqrtf(sq(_state.vel(0) - _state.wind_vel(0)) + sq(_state.vel(1) - _state.wind_vel(1)) + sq(_state.vel(2))); memcpy(tas, &tempvar, sizeof(float)); } /* * Reset the wind states using the current airspeed measurement, ground relative nav velocity, yaw angle and assumption of zero sideslip */ void Ekf::resetWindStates() { // get euler yaw angle Eulerf euler321(_state.quat_nominal); float euler_yaw = euler321(2); if (_tas_data_ready && (_imu_sample_delayed.time_us - _airspeed_sample_delayed.time_us < (uint64_t)5e5)) { // estimate wind using zero sideslip assumption and airspeed measurement if airspeed available _state.wind_vel(0) = _state.vel(0) - _airspeed_sample_delayed.true_airspeed * cosf(euler_yaw); _state.wind_vel(1) = _state.vel(1) - _airspeed_sample_delayed.true_airspeed * sinf(euler_yaw); } else { // If we don't have an airspeed measurement, then assume the wind is zero _state.wind_vel(0) = 0.0f; _state.wind_vel(1) = 0.0f; } }