forked from Archive/PX4-Autopilot
394 lines
17 KiB
C++
394 lines
17 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2015 Estimation and Control Library (ECL). All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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* 3. Neither the name ECL nor the names of its contributors may be
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* used to endorse or promote products derived from this software
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* without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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* OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
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* AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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****************************************************************************/
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/**
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* @file estimator_interface.h
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* Definition of base class for attitude estimators
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*
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* @author Roman Bast <bapstroman@gmail.com>
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*
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*/
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#include <stdint.h>
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#include <matrix/matrix/math.hpp>
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#include "RingBuffer.h"
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#include "geo.h"
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#include "common.h"
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#include "mathlib.h"
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using namespace estimator;
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class EstimatorInterface
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{
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public:
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EstimatorInterface();
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~EstimatorInterface() = default;
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virtual bool init(uint64_t timestamp) = 0;
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virtual bool update() = 0;
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// gets the innovations of velocity and position measurements
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// 0-2 vel, 3-5 pos
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virtual void get_vel_pos_innov(float vel_pos_innov[6]) = 0;
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// gets the innovations of the earth magnetic field measurements
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virtual void get_mag_innov(float mag_innov[3]) = 0;
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// gets the innovation of airspeed measurement
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virtual void get_airspeed_innov(float *airspeed_innov) = 0;
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// gets the innovation of the synthetic sideslip measurement
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virtual void get_beta_innov(float *beta_innov) = 0;
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// gets the innovations of the heading measurement
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virtual void get_heading_innov(float *heading_innov) = 0;
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// gets the innovation variances of velocity and position measurements
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// 0-2 vel, 3-5 pos
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virtual void get_vel_pos_innov_var(float vel_pos_innov_var[6]) = 0;
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// gets the innovation variances of the earth magnetic field measurements
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virtual void get_mag_innov_var(float mag_innov_var[3]) = 0;
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// gets the innovation variance of the airspeed measurement
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virtual void get_airspeed_innov_var(float *get_airspeed_innov_var) = 0;
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// gets the innovation variance of the synthetic sideslip measurement
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virtual void get_beta_innov_var(float *get_beta_innov_var) = 0;
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// gets the innovation variance of the heading measurement
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virtual void get_heading_innov_var(float *heading_innov_var) = 0;
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virtual void get_state_delayed(float *state) = 0;
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virtual void get_wind_velocity(float *wind) = 0;
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virtual void get_covariances(float *covariances) = 0;
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// gets the variances for the NED velocity states
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virtual void get_vel_var(Vector3f &vel_var) = 0;
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// gets the variances for the NED position states
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virtual void get_pos_var(Vector3f &pos_var) = 0;
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// gets the innovation variance of the flow measurement
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virtual void get_flow_innov_var(float flow_innov_var[2]) = 0;
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// gets the innovation of the flow measurement
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virtual void get_flow_innov(float flow_innov[2]) = 0;
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// gets the innovation variance of the HAGL measurement
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virtual void get_hagl_innov_var(float *flow_innov_var) = 0;
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// gets the innovation of the HAGL measurement
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virtual void get_hagl_innov(float *flow_innov_var) = 0;
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// return an array containing the output predictor angular, velocity and position tracking
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// error magnitudes (rad), (m/s), (m)
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virtual void get_output_tracking_error(float error[3]) = 0;
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/*
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Returns following IMU vibration metrics in the following array locations
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0 : Gyro delta angle coning metric = filtered length of (delta_angle x prev_delta_angle)
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1 : Gyro high frequency vibe = filtered length of (delta_angle - prev_delta_angle)
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2 : Accel high frequency vibe = filtered length of (delta_velocity - prev_delta_velocity)
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*/
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virtual void get_imu_vibe_metrics(float vibe[3]) = 0;
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// get the ekf WGS-84 origin position and height and the system time it was last set
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// return true if the origin is valid
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virtual bool get_ekf_origin(uint64_t *origin_time, map_projection_reference_s *origin_pos, float *origin_alt) = 0;
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// get the 1-sigma horizontal and vertical position uncertainty of the ekf WGS-84 position
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virtual void get_ekf_gpos_accuracy(float *ekf_eph, float *ekf_epv, bool *dead_reckoning) = 0;
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// get the 1-sigma horizontal and vertical position uncertainty of the ekf local position
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virtual void get_ekf_lpos_accuracy(float *ekf_eph, float *ekf_epv, bool *dead_reckoning) = 0;
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// get the 1-sigma horizontal and vertical velocity uncertainty
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virtual void get_ekf_vel_accuracy(float *ekf_evh, float *ekf_evv, bool *dead_reckoning) = 0;
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// ask estimator for sensor data collection decision and do any preprocessing if required, returns true if not defined
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virtual bool collect_gps(uint64_t time_usec, struct gps_message *gps) { return true; }
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// accumulate and downsample IMU data to the EKF prediction rate
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virtual bool collect_imu(imuSample &imu) { return true; }
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// set delta angle imu data
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void setIMUData(uint64_t time_usec, uint64_t delta_ang_dt, uint64_t delta_vel_dt, float (&delta_ang)[3], float (&delta_vel)[3]);
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// set magnetometer data
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void setMagData(uint64_t time_usec, float (&data)[3]);
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// set gps data
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void setGpsData(uint64_t time_usec, struct gps_message *gps);
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// set baro data
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void setBaroData(uint64_t time_usec, float data);
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// set airspeed data
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void setAirspeedData(uint64_t time_usec, float true_airspeed, float eas2tas);
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// set range data
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void setRangeData(uint64_t time_usec, float data);
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// set optical flow data
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void setOpticalFlowData(uint64_t time_usec, flow_message *flow);
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// set external vision position and attitude data
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void setExtVisionData(uint64_t time_usec, ext_vision_message *evdata);
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// return a address to the parameters struct
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// in order to give access to the application
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parameters *getParamHandle() {return &_params;}
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// set vehicle landed status data
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void set_in_air_status(bool in_air) {_control_status.flags.in_air = in_air;}
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// set flag if synthetic sideslip measurement should be fused
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void set_fuse_beta_flag(bool fuse_beta) {_control_status.flags.fuse_beta = fuse_beta;}
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// return true if the global position estimate is valid
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virtual bool global_position_is_valid() = 0;
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// return true if the EKF is dead reckoning the position using inertial data only
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virtual bool inertial_dead_reckoning() = 0;
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// return true if the estimate is valid
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// return the estimated terrain vertical position relative to the NED origin
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virtual bool get_terrain_vert_pos(float *ret) = 0;
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// return true if the local position estimate is valid
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bool local_position_is_valid();
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void copy_quaternion(float *quat)
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{
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for (unsigned i = 0; i < 4; i++) {
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quat[i] = _output_new.quat_nominal(i);
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}
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}
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// get the velocity of the body frame origin in local NED earth frame
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void get_velocity(float *vel)
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{
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// calculate the average angular rate across the last IMU update
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Vector3f ang_rate = _imu_sample_new.delta_ang * (1.0f/_imu_sample_new.delta_ang_dt);
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// calculate the velocity of the relative to the body origin
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// Note % operator has been overloaded to performa cross product
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Vector3f vel_imu_rel_body = cross_product(ang_rate , _params.imu_pos_body);
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// rotate the relative velocty into earth frame and subtract from the EKF velocity
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// (which is at the IMU) to get velocity of the body origin
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Vector3f vel_earth = _output_new.vel - _R_to_earth_now * vel_imu_rel_body;
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// copy to output
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for (unsigned i = 0; i < 3; i++) {
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vel[i] = vel_earth(i);
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}
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}
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// get the position of the body frame origin in local NED earth frame
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void get_position(float *pos)
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{
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// rotate the position of the IMU relative to the boy origin into earth frame
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Vector3f pos_offset_earth = _R_to_earth_now * _params.imu_pos_body;
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// subtract from the EKF position (which is at the IMU) to get position at the body origin
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for (unsigned i = 0; i < 3; i++) {
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pos[i] = _output_new.pos(i) - pos_offset_earth(i);
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}
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}
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void copy_timestamp(uint64_t *time_us)
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{
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*time_us = _time_last_imu;
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}
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// Copy the magnetic declination that we wish to save to the EKF2_MAG_DECL parameter for the next startup
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void copy_mag_decl_deg(float *val)
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{
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*val = _mag_declination_to_save_deg;
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}
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virtual void get_accel_bias(float bias[3]) = 0;
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virtual void get_gyro_bias(float bias[3]) = 0;
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// get EKF mode status
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void get_control_mode(uint16_t *val)
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{
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*val = _control_status.value;
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}
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// get EKF internal fault status
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void get_filter_fault_status(uint16_t *val)
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{
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*val = _fault_status.value;
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}
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// get GPS check status
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virtual void get_gps_check_status(uint16_t *val) = 0;
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// return the amount the local vertical position changed in the last reset and the number of reset events
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virtual void get_posD_reset(float *delta, uint8_t *counter) = 0;
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// return the amount the local vertical velocity changed in the last reset and the number of reset events
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virtual void get_velD_reset(float *delta, uint8_t *counter) = 0;
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// return the amount the local horizontal position changed in the last reset and the number of reset events
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virtual void get_posNE_reset(float delta[2], uint8_t *counter) = 0;
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// return the amount the local horizontal velocity changed in the last reset and the number of reset events
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virtual void get_velNE_reset(float delta[2], uint8_t *counter) = 0;
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// return the amount the quaternion has changed in the last reset and the number of reset events
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virtual void get_quat_reset(float delta_quat[4], uint8_t *counter) = 0;
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// get EKF innovation consistency check status information comprising of:
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// status - a bitmask integer containing the pass/fail status for each EKF measurement innovation consistency check
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// Innovation Test Ratios - these are the ratio of the innovation to the acceptance threshold.
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// A value > 1 indicates that the sensor measurement has exceeded the maximum acceptable level and has been rejected by the EKF
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// Where a measurement type is a vector quantity, eg magnetoemter, GPS position, etc, the maximum value is returned.
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virtual void get_innovation_test_status(uint16_t *status, float *mag, float *vel, float *pos, float *hgt, float *tas, float *hagl) = 0;
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// return a bitmask integer that describes which state estimates can be used for flight control
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virtual void get_ekf_soln_status(uint16_t *status) = 0;
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protected:
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parameters _params; // filter parameters
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/*
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OBS_BUFFER_LENGTH defines how many observations (non-IMU measurements) we can buffer
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which sets the maximum frequency at which we can process non-IMU measurements. Measurements that
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arrive too soon after the previous measurement will not be processed.
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max freq (Hz) = (OBS_BUFFER_LENGTH - 1) / (IMU_BUFFER_LENGTH * FILTER_UPDATE_PERIOD_MS * 0.001)
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This can be adjusted to match the max sensor data rate plus some margin for jitter.
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*/
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uint8_t _obs_buffer_length;
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/*
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IMU_BUFFER_LENGTH defines how many IMU samples we buffer which sets the time delay from current time to the
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EKF fusion time horizon and therefore the maximum sensor time offset relative to the IMU that we can compensate for.
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max sensor time offet (msec) = IMU_BUFFER_LENGTH * FILTER_UPDATE_PERIOD_MS
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This can be adjusted to a value that is FILTER_UPDATE_PERIOD_MS longer than the maximum observation time delay.
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*/
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uint8_t _imu_buffer_length;
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static const unsigned FILTER_UPDATE_PERIOD_MS = 10; // ekf prediction period in milliseconds
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unsigned _min_obs_interval_us; // minimum time interval between observations that will guarantee data is not lost (usec)
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float _dt_imu_avg; // average imu update period in s
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imuSample _imu_sample_delayed; // captures the imu sample on the delayed time horizon
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// measurement samples capturing measurements on the delayed time horizon
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magSample _mag_sample_delayed;
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baroSample _baro_sample_delayed;
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gpsSample _gps_sample_delayed;
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rangeSample _range_sample_delayed;
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airspeedSample _airspeed_sample_delayed;
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flowSample _flow_sample_delayed;
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extVisionSample _ev_sample_delayed;
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outputSample _output_sample_delayed; // filter output on the delayed time horizon
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outputSample _output_new; // filter output on the non-delayed time horizon
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imuSample _imu_sample_new; // imu sample capturing the newest imu data
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Matrix3f _R_to_earth_now; // rotation matrix from body to earth frame at current time
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uint64_t _imu_ticks; // counter for imu updates
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bool _imu_updated; // true if the ekf should update (completed downsampling process)
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bool _initialised; // true if the ekf interface instance (data buffering) is initialized
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bool _NED_origin_initialised;
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bool _gps_speed_valid;
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float _gps_origin_eph; // horizontal position uncertainty of the GPS origin
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float _gps_origin_epv; // vertical position uncertainty of the GPS origin
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struct map_projection_reference_s _pos_ref; // Contains WGS-84 position latitude and longitude (radians)
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// innovation consistency check monitoring ratios
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float _yaw_test_ratio; // yaw innovation consistency check ratio
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float _mag_test_ratio[3]; // magnetometer XYZ innovation consistency check ratios
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float _vel_pos_test_ratio[6]; // velocity and position innovation consistency check ratios
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float _tas_test_ratio; // tas innovation consistency check ratio
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float _terr_test_ratio; // height above terrain measurement innovation consistency check ratio
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float _beta_test_ratio; // sideslip innovation consistency check ratio
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innovation_fault_status_u _innov_check_fail_status{};
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// IMU vibration monitoring
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Vector3f _delta_ang_prev; // delta angle from the previous IMU measurement
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Vector3f _delta_vel_prev; // delta velocity from the previous IMU measurement
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float _vibe_metrics[3]; // IMU vibration metrics
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// [0] Level of coning vibration in the IMU delta angles (rad^2)
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// [1] high frequency vibraton level in the IMU delta angle data (rad)
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// [2] high frequency vibration level in the IMU delta velocity data (m/s)
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// data buffer instances
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RingBuffer<imuSample> _imu_buffer;
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RingBuffer<gpsSample> _gps_buffer;
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RingBuffer<magSample> _mag_buffer;
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RingBuffer<baroSample> _baro_buffer;
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RingBuffer<rangeSample> _range_buffer;
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RingBuffer<airspeedSample> _airspeed_buffer;
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RingBuffer<flowSample> _flow_buffer;
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RingBuffer<extVisionSample> _ext_vision_buffer;
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RingBuffer<outputSample> _output_buffer;
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uint64_t _time_last_imu; // timestamp of last imu sample in microseconds
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uint64_t _time_last_gps; // timestamp of last gps measurement in microseconds
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uint64_t _time_last_mag; // timestamp of last magnetometer measurement in microseconds
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uint64_t _time_last_baro; // timestamp of last barometer measurement in microseconds
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uint64_t _time_last_range; // timestamp of last range measurement in microseconds
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uint64_t _time_last_airspeed; // timestamp of last airspeed measurement in microseconds
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uint64_t _time_last_ext_vision; // timestamp of last external vision measurement in microseconds
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uint64_t _time_last_optflow;
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fault_status_u _fault_status{};
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// allocate data buffers and intialise interface variables
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bool initialise_interface(uint64_t timestamp);
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// free buffer memory
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void unallocate_buffers();
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float _mag_declination_gps; // magnetic declination returned by the geo library using the last valid GPS position (rad)
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float _mag_declination_to_save_deg; // magnetic declination to save to EKF2_MAG_DECL (deg)
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// this is the current status of the filter control modes
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filter_control_status_u _control_status{};
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// this is the previous status of the filter control modes - used to detect mode transitions
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filter_control_status_u _control_status_prev{};
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// perform a vector cross product
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Vector3f cross_product(const Vector3f &vecIn1, const Vector3f &vecIn2);
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// calculate the inverse rotation matrix from a quaternion rotation
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Matrix3f quat_to_invrotmat(const Quaternion& quat);
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};
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