2015-12-06 07:18:26 -04:00
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/****************************************************************************
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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 ekf_helper.cpp
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* Definition of ekf helper functions.
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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 "ekf.h"
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2015-12-19 04:40:32 -04:00
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#ifdef __PX4_POSIX
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2015-12-07 04:26:30 -04:00
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#include <iostream>
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#include <fstream>
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2015-12-19 04:40:32 -04:00
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#endif
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2015-12-07 04:26:30 -04:00
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#include <iomanip>
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#include <mathlib/mathlib.h>
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2015-12-06 07:18:26 -04:00
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2015-12-07 04:26:30 -04:00
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// Reset the velocity states. If we have a recent and valid
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// gps measurement then use for velocity initialisation
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2015-12-06 07:18:26 -04:00
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void Ekf::resetVelocity()
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{
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// if we have a valid GPS measurement use it to initialise velocity states
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gpsSample gps_newest = _gps_buffer.get_newest();
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if (_time_last_imu - gps_newest.time_us < 100000) {
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_state.vel = gps_newest.vel;
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} else {
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_state.vel.setZero();
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}
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}
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2015-12-07 04:26:30 -04:00
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// Reset position states. If we have a recent and valid
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// gps measurement then use for position initialisation
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2015-12-06 07:18:26 -04:00
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void Ekf::resetPosition()
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{
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// if we have a valid GPS measurement use it to initialise position states
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gpsSample gps_newest = _gps_buffer.get_newest();
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if (_time_last_imu - gps_newest.time_us < 100000) {
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_state.pos(0) = gps_newest.pos(0);
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_state.pos(1) = gps_newest.pos(1);
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} else {
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// XXX use the value of the last known position
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}
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baroSample baro_newest = _baro_buffer.get_newest();
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2016-01-05 02:44:37 -04:00
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_state.pos(2) = -baro_newest.hgt;
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2015-12-06 07:18:26 -04:00
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}
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2015-12-07 04:26:30 -04:00
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2016-01-07 18:54:55 -04:00
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#if defined(__PX4_POSIX) && !defined(__PX4_QURT)
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2015-12-07 04:26:30 -04:00
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void Ekf::printCovToFile(char const *filename)
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{
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std::ofstream myfile;
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myfile.open(filename);
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myfile << "Covariance matrix\n";
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myfile << std::setprecision(1);
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for (int i = 0; i < _k_num_states; i++) {
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for (int j = 0; j < _k_num_states; j++) {
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myfile << std::to_string(P[i][j]) << std::setprecision(1) << " ";
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}
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myfile << "\n\n\n\n\n\n\n\n\n\n";
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}
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}
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2015-12-19 04:40:32 -04:00
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#endif
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2015-12-07 04:26:30 -04:00
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// This checks if the diagonal of the covariance matrix is non-negative
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// and that the matrix is symmetric
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void Ekf::assertCovNiceness()
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{
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for (int row = 0; row < _k_num_states; row++) {
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for (int column = 0; column < row; column++) {
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assert(fabsf(P[row][column] - P[column][row]) < 0.00001f);
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}
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}
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for (int i = 0; i < _k_num_states; i++) {
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assert(P[i][i] > -0.000001f);
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}
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}
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// This function forces the covariance matrix to be symmetric
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void Ekf::makeSymmetrical()
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{
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for (unsigned row = 0; row < _k_num_states; row++) {
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for (unsigned column = 0; column < row; column++) {
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float tmp = (P[row][column] + P[column][row]) / 2;
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P[row][column] = tmp;
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P[column][row] = tmp;
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}
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}
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}
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void Ekf::constrainStates()
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{
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2016-01-12 02:30:53 -04:00
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for (int i = 0; i < 3; i++) {
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2015-12-07 04:26:30 -04:00
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_state.ang_error(i) = math::constrain(_state.ang_error(i), -1.0f, 1.0f);
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}
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2016-01-12 02:30:53 -04:00
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for (int i = 0; i < 3; i++) {
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2015-12-07 04:26:30 -04:00
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_state.vel(i) = math::constrain(_state.vel(i), -1000.0f, 1000.0f);
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}
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2016-01-12 02:30:53 -04:00
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for (int i = 0; i < 3; i++) {
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2015-12-07 04:26:30 -04:00
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_state.pos(i) = math::constrain(_state.pos(i), -1.e6f, 1.e6f);
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}
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2016-01-12 02:30:53 -04:00
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for (int i = 0; i < 3; i++) {
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2015-12-07 04:26:30 -04:00
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_state.gyro_bias(i) = math::constrain(_state.gyro_bias(i), -0.349066f * _dt_imu_avg, 0.349066f * _dt_imu_avg);
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}
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2016-01-12 02:30:53 -04:00
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for (int i = 0; i < 3; i++) {
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2015-12-07 04:26:30 -04:00
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_state.gyro_scale(i) = math::constrain(_state.gyro_scale(i), 0.95f, 1.05f);
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}
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_state.accel_z_bias = math::constrain(_state.accel_z_bias, -1.0f * _dt_imu_avg, 1.0f * _dt_imu_avg);
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2016-01-12 02:30:53 -04:00
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for (int i = 0; i < 3; i++) {
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2015-12-07 04:26:30 -04:00
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_state.mag_I(i) = math::constrain(_state.mag_I(i), -1.0f, 1.0f);
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}
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2016-01-12 02:30:53 -04:00
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for (int i = 0; i < 3; i++) {
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2015-12-07 04:26:30 -04:00
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_state.mag_B(i) = math::constrain(_state.mag_B(i), -0.5f, 0.5f);
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}
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2016-01-19 22:25:22 -04:00
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for (int i = 0; i < 2; i++) {
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2015-12-07 04:26:30 -04:00
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_state.wind_vel(i) = math::constrain(_state.wind_vel(i), -100.0f, 100.0f);
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}
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}
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// calculate the earth rotation vector
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void Ekf::calcEarthRateNED(Vector3f &omega, double lat_rad) const
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{
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omega(0) = _k_earth_rate * cosf((float)lat_rad);
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omega(1) = 0.0f;
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omega(2) = -_k_earth_rate * sinf((float)lat_rad);
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}
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2016-01-12 02:30:53 -04:00
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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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void Ekf::get_vel_pos_innov(float vel_pos_innov[6])
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{
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memcpy(vel_pos_innov, _vel_pos_innov, sizeof(float) * 6);
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}
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// writes the innovations of the earth magnetic field measurements
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void Ekf::get_mag_innov(float mag_innov[3])
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{
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memcpy(mag_innov, _mag_innov, 3 * sizeof(float));
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}
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// gets the innovations of the heading measurement
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void Ekf::get_heading_innov(float *heading_innov)
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{
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memcpy(heading_innov, &_heading_innov, sizeof(float));
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}
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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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void Ekf::get_vel_pos_innov_var(float vel_pos_innov_var[6])
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{
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memcpy(vel_pos_innov_var, _vel_pos_innov_var, sizeof(float) * 6);
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}
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// gets the innovation variances of the earth magnetic field measurements
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void Ekf::get_mag_innov_var(float mag_innov_var[3])
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{
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memcpy(mag_innov_var, _mag_innov_var, sizeof(float) * 3);
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}
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// gets the innovation variance of the heading measurement
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void Ekf::get_heading_innov_var(float *heading_innov_var)
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{
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memcpy(heading_innov_var, &_heading_innov_var, sizeof(float));
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}
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// get the state vector at the delayed time horizon
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void Ekf::get_state_delayed(float *state)
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{
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for (int i = 0; i < 3; i++) {
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state[i] = _state.ang_error(i);
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}
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for (int i = 0; i < 3; i++) {
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state[i + 3] = _state.vel(i);
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}
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for (int i = 0; i < 3; i++) {
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state[i + 6] = _state.pos(i);
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}
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for (int i = 0; i < 3; i++) {
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state[i + 9] = _state.gyro_bias(i);
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}
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for (int i = 0; i < 3; i++) {
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state[i + 12] = _state.gyro_scale(i);
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}
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state[15] = _state.accel_z_bias;
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for (int i = 0; i < 3; i++) {
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state[i + 16] = _state.mag_I(i);
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}
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for (int i = 0; i < 3; i++) {
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state[i + 19] = _state.mag_B(i);
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}
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for (int i = 0; i < 2; i++) {
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state[i + 22] = _state.wind_vel(i);
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}
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}
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// get the diagonal elements of the covariance matrix
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void Ekf::get_covariances(float *covariances)
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{
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for (unsigned i = 0; i < _k_num_states; i++) {
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covariances[i] = P[i][i];
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}
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}
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