/**************************************************************************** * * 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 ekf.h * Class for core functions for ekf attitude and position estimator. * * @author Roman Bast * @author Paul Riseborough * */ #include "estimator_interface.h" #include "geo.h" class Ekf : public EstimatorInterface { public: Ekf(); ~Ekf(); // initialise variables to sane values (also interface class) bool init(uint64_t timestamp); // should be called every time new data is pushed into the filter bool update(); // gets the innovations of velocity and position measurements // 0-2 vel, 3-5 pos void get_vel_pos_innov(float vel_pos_innov[6]); // gets the innovations of the earth magnetic field measurements void get_mag_innov(float mag_innov[3]); // gets the innovations of the heading measurement void get_heading_innov(float *heading_innov); // gets the innovation variances of velocity and position measurements // 0-2 vel, 3-5 pos void get_vel_pos_innov_var(float vel_pos_innov_var[6]); // gets the innovation variances of the earth magnetic field measurements void get_mag_innov_var(float mag_innov_var[3]); // gets the innovations of airspeed measurement void get_airspeed_innov(float *airspeed_innov); // gets the innovation variance of the airspeed measurement void get_airspeed_innov_var(float *airspeed_innov_var); // gets the innovation variance of the heading measurement void get_heading_innov_var(float *heading_innov_var); // gets the innovation variance of the flow measurement void get_flow_innov_var(float flow_innov_var[2]); // gets the innovation of the flow measurement void get_flow_innov(float flow_innov[2]); // gets the innovation variance of the HAGL measurement void get_hagl_innov_var(float *hagl_innov_var); // gets the innovation of the HAGL measurement void get_hagl_innov(float *hagl_innov); // get the state vector at the delayed time horizon void get_state_delayed(float *state); // get the diagonal elements of the covariance matrix void get_covariances(float *covariances); // ask estimator for sensor data collection decision and do any preprocessing if required, returns true if not defined bool collect_gps(uint64_t time_usec, struct gps_message *gps); bool collect_imu(imuSample &imu); // get the ekf WGS-84 origin position and height and the system time it was last set void get_ekf_origin(uint64_t *origin_time, map_projection_reference_s *origin_pos, float *origin_alt); // get the 1-sigma horizontal and vertical position uncertainty of the ekf WGS-84 position void get_ekf_accuracy(float *ekf_eph, float *ekf_epv, bool *dead_reckoning); void get_vel_var(Vector3f &vel_var); void get_pos_var(Vector3f &pos_var); // return true if the global position estimate is valid bool global_position_is_valid(); // return true if the etimate is valid // return the estimated terrain vertical position relative to the NED origin bool get_terrain_vert_pos(float *ret); // get the accerometer bias in m/s/s void get_accel_bias(float bias[3]); // get GPS check status void get_gps_check_status(uint16_t *_gps_check_fail_status); // return the amount the local vertical position changed in the last height reset and the time of the reset void get_vert_pos_reset(float *delta, uint64_t *time_us) {*delta = _state_reset_status.posD_change; *time_us = _state_reset_status.posD_time_us;} private: static const uint8_t _k_num_states = 24; static const float _k_earth_rate; static const float _gravity_mss; float _dt_ekf_avg; // average update rate of the ekf stateSample _state; // state struct of the ekf running at the delayed time horizon bool _filter_initialised; // true when the EKF sttes and covariances been initialised bool _earth_rate_initialised; // true when we know the earth rotatin rate (requires GPS) bool _fuse_height; // baro height data should be fused bool _fuse_pos; // gps position data should be fused bool _fuse_hor_vel; // gps horizontal velocity measurement should be fused bool _fuse_vert_vel; // gps vertical velocity measurement should be fused bool _fuse_flow; // flow measurement should be fused bool _fuse_hagl_data; // if true then range data will be fused to estimate terrain height uint64_t _time_last_fake_gps; // last time in us at which we have faked gps measurement for static mode uint64_t _time_last_pos_fuse; // time the last fusion of horizontal position measurements was performed (usec) uint64_t _time_last_vel_fuse; // time the last fusion of velocity measurements was performed (usec) uint64_t _time_last_hgt_fuse; // time the last fusion of height measurements was performed (usec) uint64_t _time_last_of_fuse; // time the last fusion of optical flow measurements were performed (usec) uint64_t _time_last_arsp_fuse; // time the last fusion of airspeed measurements were performed (usec) Vector2f _last_known_posNE; // last known local NE position vector (m) float _last_disarmed_posD; // vertical position recorded at arming (m) float _last_dt_overrun; // the amount of time the last IMU collection over-ran the target set by FILTER_UPDATE_PERIOD_MS (sec) Vector3f _earth_rate_NED; // earth rotation vector (NED) in rad/s matrix::Dcm _R_to_earth; // transformation matrix from body frame to earth frame from last EKF predition float P[_k_num_states][_k_num_states]; // state covariance matrix float KH[_k_num_states][_k_num_states]; // intermediate variable for the covariance update float KHP[_k_num_states][_k_num_states]; // intermediate variable for the covariance update float _vel_pos_innov[6]; // innovations: 0-2 vel, 3-5 pos float _vel_pos_innov_var[6]; // innovation variances: 0-2 vel, 3-5 pos float _mag_innov[3]; // earth magnetic field innovations float _mag_innov_var[3]; // earth magnetic field innovation variance float _airspeed_innov; // airspeed measurement innovation float _airspeed_innov_var; // airspeed measurement innovation variance float _heading_innov; // heading measurement innovation float _heading_innov_var; // heading measurement innovation variance // optical flow processing float _flow_innov[2]; // flow measurement innovation float _flow_innov_var[2]; // flow innovation variance Vector3f _flow_gyro_bias; // bias errors in optical flow sensor rate gyro outputs Vector3f _imu_del_ang_of; // bias corrected delta angle measurements accumulated across the same time frame as the optical flow rates float _delta_time_of; // time in sec that _imu_del_ang_of was accumulated over float _mag_declination; // magnetic declination used by reset and fusion functions (rad) // complementary filter states Vector3f _delta_angle_corr; // delta angle correction vector imuSample _imu_down_sampled; // down sampled imu data (sensor rate -> filter update rate) Quaternion _q_down_sampled; // down sampled quaternion (tracking delta angles between ekf update steps) // variables used for the GPS quality checks float _gpsDriftVelN; // GPS north position derivative (m/s) float _gpsDriftVelE; // GPS east position derivative (m/s) float _gps_drift_velD; // GPS down position derivative (m/s) float _gps_velD_diff_filt; // GPS filtered Down velocity (m/s) float _gps_velN_filt; // GPS filtered North velocity (m/s) float _gps_velE_filt; // GPS filtered East velocity (m/s) uint64_t _last_gps_fail_us; // last system time in usec that the GPS failed it's checks // Variables used to publish the WGS-84 location of the EKF local NED origin uint64_t _last_gps_origin_time_us; // time the origin was last set (uSec) float _gps_alt_ref; // WGS-84 height (m) // Variables used to initialise the filter states uint32_t _hgt_counter; // number of height samples read during initialisation float _rng_filt_state; // filtered height measurement uint32_t _mag_counter; // number of magnetometer samples read during initialisation uint32_t _ev_counter; // number of exgernal vision samples read during initialisation uint64_t _time_last_mag; // measurement time of last magnetomter sample Vector3f _mag_filt_state; // filtered magnetometer measurement Vector3f _delVel_sum; // summed delta velocity float _hgt_sensor_offset; // set as necessary if desired to maintain the same height after a height reset (m) gps_check_fail_status_u _gps_check_fail_status; // Terrain height state estimation float _terrain_vpos; // estimated vertical position of the terrain underneath the vehicle in local NED frame (m) float _terrain_var; // variance of terrain position estimate (m^2) float _hagl_innov; // innovation of the last height above terrain measurement (m) float _hagl_innov_var; // innovation variance for the last height above terrain measurement (m^2) uint64_t _time_last_hagl_fuse; // last system time in usec that the hagl measurement failed it's checks bool _terrain_initialised; // true when the terrain estimator has been intialised // height sensor fault status bool _baro_hgt_faulty; // true if valid baro data is unavailable for use bool _gps_hgt_faulty; // true if valid gps height data is unavailable for use bool _rng_hgt_faulty; // true if valid rnage finder height data is unavailable for use int _primary_hgt_source; // priary source of height data set at initialisation float _baro_hgt_offset; // baro height reading at the local NED origin (m) // imu fault status uint64_t _time_bad_vert_accel; // last time a bad vertical accel was detected (usec) // update the real time complementary filter states. This includes the prediction // and the correction step void calculateOutputStates(); // initialise filter states of both the delayed ekf and the real time complementary filter bool initialiseFilter(void); // initialise ekf covariance matrix void initialiseCovariance(); // predict ekf state void predictState(); // predict ekf covariance void predictCovariance(); // ekf sequential fusion of magnetometer measurements void fuseMag(); // fuse the first euler angle from either a 321 or 312 rotation sequence as the observation (currently measures yaw using the magnetometer) void fuseHeading(); // fuse magnetometer declination measurement void fuseDeclination(); // fuse airspeed measurement void fuseAirspeed(); // fuse velocity and position measurements (also barometer height) void fuseVelPosHeight(); // reset velocity states of the ekf bool resetVelocity(); // fuse optical flow line of sight rate measurements void fuseOptFlow(); // calculate optical flow bias errors void calcOptFlowBias(); // initialise the terrain vertical position estimator // return true if the initialisation is successful bool initHagl(); // predict the terrain vertical position state and variance void predictHagl(); // update the terrain vertical position estimate using a height above ground measurement from the range finder void fuseHagl(); // reset the heading and magnetic field states using the declination and magnetometer measurements // return true if successful bool resetMagHeading(Vector3f &mag_init); // calculate the magnetic declination to be used by the alignment and fusion processing void calcMagDeclination(); // reset position states of the ekf (only vertical position) bool resetPosition(); // reset height state of the ekf void resetHeight(); // modify output filter to match the the EKF state at the fusion time horizon void alignOutputFilter(); // limit the diagonal of the covariance matrix void fixCovarianceErrors(); // make ekf covariance matrix symmetric between a nominated state indexe range void makeSymmetrical(float (&cov_mat)[_k_num_states][_k_num_states], uint8_t first, uint8_t last); // constrain the ekf states void constrainStates(); // generic function which will perform a fusion step given a kalman gain K // and a scalar innovation value void fuse(float *K, float innovation); // calculate the earth rotation vector from a given latitude void calcEarthRateNED(Vector3f &omega, double lat_rad) const; // return true id the GPS quality is good enough to set an origin and start aiding bool gps_is_good(struct gps_message *gps); // Control the filter fusion modes void controlFusionModes(); // control fusion of external vision observations void controlExternalVisionAiding(); // control fusion of optical flow observtions void controlOpticalFlowAiding(); // control fusion of GPS observations void controlGpsAiding(); // control fusion of height position observations void controlHeightAiding(); // control fusion of magnetometer observations void controlMagAiding(); // control for height sensor timeouts, sensor changes and state resets void controlHeightSensorTimeouts(); // return the square of two floating point numbers - used in auto coded sections inline float sq(float var) { return var * var; } // zero the specified range of rows in the state covariance matrix void zeroRows(float (&cov_mat)[_k_num_states][_k_num_states], uint8_t first, uint8_t last); // zero the specified range of columns in the state covariance matrix void zeroCols(float (&cov_mat)[_k_num_states][_k_num_states], uint8_t first, uint8_t last); // calculate the measurement variance for the optical flow sensor float calcOptFlowMeasVar(); // rotate quaternion covariances into variances for an equivalent rotation vector Vector3f calcRotVecVariances(); // initialise the quaternion covariances using rotation vector variances void initialiseQuatCovariances(Vector3f &rot_vec_var); };