px4-firmware/EKF/ekf.cpp

526 lines
14 KiB
C++

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/**
* @file ekf.cpp
* Core functions for ekf attitude and position estimator.
*
* @author Roman Bast <bapstroman@gmail.com>
*
*/
#include "ekf.h"
#include <drivers/drv_hrt.h>
Ekf::Ekf():
_control_status{},
_filter_initialised(false),
_earth_rate_initialised(false),
_fuse_height(false),
_fuse_pos(false),
_fuse_hor_vel(false),
_fuse_vert_vel(false),
_time_last_fake_gps(0),
_time_last_pos_fuse(0),
_time_last_vel_fuse(0),
_time_last_hgt_fuse(0),
_time_last_of_fuse(0),
_vel_pos_innov{},
_mag_innov{},
_heading_innov{},
_vel_pos_innov_var{},
_mag_innov_var{},
_heading_innov_var{}
{
_earth_rate_NED.setZero();
_R_prev = matrix::Dcm<float>();
_delta_angle_corr.setZero();
_delta_vel_corr.setZero();
_vel_corr.setZero();
_last_known_posNE.setZero();
}
Ekf::~Ekf()
{
}
bool Ekf::init(uint64_t timestamp)
{
bool ret = initialise_interface(timestamp);
_state.ang_error.setZero();
_state.vel.setZero();
_state.pos.setZero();
_state.gyro_bias.setZero();
_state.gyro_scale(0) = 1.0f;
_state.gyro_scale(1) = 1.0f;
_state.gyro_scale(2) = 1.0f;
_state.accel_z_bias = 0.0f;
_state.mag_I.setZero();
_state.mag_B.setZero();
_state.wind_vel.setZero();
_state.quat_nominal.setZero();
_state.quat_nominal(0) = 1.0f;
_output_new.vel.setZero();
_output_new.pos.setZero();
_output_new.quat_nominal = matrix::Quaternion<float>();
_imu_down_sampled.delta_ang.setZero();
_imu_down_sampled.delta_vel.setZero();
_imu_down_sampled.delta_ang_dt = 0.0f;
_imu_down_sampled.delta_vel_dt = 0.0f;
_imu_down_sampled.time_us = timestamp;
_q_down_sampled(0) = 1.0f;
_q_down_sampled(1) = 0.0f;
_q_down_sampled(2) = 0.0f;
_q_down_sampled(3) = 0.0f;
_imu_updated = false;
_NED_origin_initialised = false;
_gps_speed_valid = false;
_mag_healthy = false;
return ret;
}
bool Ekf::update()
{
bool ret = false; // indicates if there has been an update
if (!_filter_initialised) {
_filter_initialised = initialiseFilter();
if (!_filter_initialised) {
return false;
}
}
//printStates();
//printStatesFast();
// prediction
if (_imu_updated) {
ret = true;
predictState();
predictCovariance();
}
// control logic
controlFusionModes();
// measurement updates
// Fuse magnetometer data using the selected fuson method and only if angular alignment is complete
if (_mag_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_mag_sample_delayed)) {
if (_control_status.flags.mag_3D && _control_status.flags.angle_align) {
fuseMag();
if (_control_status.flags.mag_dec) {
fuseDeclination();
}
} else if (_control_status.flags.mag_hdg && _control_status.flags.angle_align) {
fuseHeading();
}
}
if (_baro_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_baro_sample_delayed)) {
_fuse_height = true;
}
// If we are using GPS aiding and data has fallen behind the fusion time horizon then fuse it
// if we aren't doing any aiding, fake GPS measurements at the last known position to constrain drift
// Coincide fake measurements with baro data for efficiency with a minimum fusion rate of 5Hz
if (_gps_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_gps_sample_delayed) && _control_status.flags.gps) {
_fuse_pos = true;
_fuse_vert_vel = true;
_fuse_hor_vel = true;
} else if (!_control_status.flags.gps && !_control_status.flags.opt_flow
&& ((_time_last_imu - _time_last_fake_gps > 2e5) || _fuse_height)) {
_fuse_pos = true;
_gps_sample_delayed.pos(0) = _last_known_posNE(0);
_gps_sample_delayed.pos(1) = _last_known_posNE(1);
_time_last_fake_gps = _time_last_imu;
}
if (_fuse_height || _fuse_pos || _fuse_hor_vel || _fuse_vert_vel) {
fuseVelPosHeight();
_fuse_hor_vel = _fuse_vert_vel = _fuse_pos = _fuse_height = false;
}
if (_range_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_range_sample_delayed)) {
fuseRange();
}
if (_airspeed_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_airspeed_sample_delayed)) {
fuseAirspeed();
}
calculateOutputStates();
return ret;
}
bool Ekf::initialiseFilter(void)
{
// Keep accumulating measurements until we have a minimum of 10 samples for the baro and magnetoemter
// Sum the IMU delta angle measurements
_delVel_sum += _imu_down_sampled.delta_vel;
// Sum the magnetometer measurements
magSample mag_init = _mag_buffer.get_newest();
if (mag_init.time_us != 0) {
_mag_counter ++;
_mag_sum += mag_init.mag;
}
// Sum the barometer measurements
// initialize vertical position with newest baro measurement
baroSample baro_init = _baro_buffer.get_newest();
if (baro_init.time_us != 0) {
_baro_counter ++;
_baro_sum += baro_init.hgt;
}
// check to see if we have enough measruements and return false if not
if (_baro_counter < 10 || _mag_counter < 10) {
return false;
} else {
// Zero all of the states
_state.ang_error.setZero();
_state.vel.setZero();
_state.pos.setZero();
_state.gyro_bias.setZero();
_state.gyro_scale(0) = _state.gyro_scale(1) = _state.gyro_scale(2) = 1.0f;
_state.accel_z_bias = 0.0f;
_state.mag_I.setZero();
_state.mag_B.setZero();
_state.wind_vel.setZero();
// get initial roll and pitch estimate from delta velocity vector, assuming vehicle is static
float pitch = 0.0f;
float roll = 0.0f;
if (_delVel_sum.norm() > 0.001f) {
_delVel_sum.normalize();
pitch = asinf(_delVel_sum(0));
roll = -asinf(_delVel_sum(1) / cosf(pitch));
} else {
return false;
}
// calculate the averaged magnetometer reading
Vector3f mag_init = _mag_sum * (1.0f / (float(_mag_counter)));
// rotate magnetic field into earth frame assuming zero yaw and estimate yaw angle assuming zero declination
// TODO use declination if available
matrix::Euler<float> euler_init(roll, pitch, 0.0f);
matrix::Dcm<float> R_to_earth_zeroyaw(euler_init);
Vector3f mag_ef_zeroyaw = R_to_earth_zeroyaw * mag_init;
float declination = 0.0f;
euler_init(2) = declination - atan2f(mag_ef_zeroyaw(1), mag_ef_zeroyaw(0));
// calculate initial quaternion states
_state.quat_nominal = Quaternion(euler_init);
_output_new.quat_nominal = _state.quat_nominal;
// TODO replace this with a conditional test based on fitered angle error states.
_control_status.flags.angle_align = true;
// calculate initial earth magnetic field states
matrix::Dcm<float> R_to_earth(euler_init);
_state.mag_I = R_to_earth * mag_init;
// calculate the averaged barometer reading
_baro_at_alignment = _baro_sum / (float)_baro_counter;
// set the velocity to the GPS measurement (by definition, the initial position and height is at the origin)
resetVelocity();
// initialise the state covariance matrix
initialiseCovariance();
return true;
}
}
void Ekf::predictState()
{
if (!_earth_rate_initialised) {
if (_NED_origin_initialised) {
calcEarthRateNED(_earth_rate_NED, _pos_ref.lat_rad);
_earth_rate_initialised = true;
}
}
// attitude error state prediciton
matrix::Dcm<float> R_to_earth(_state.quat_nominal); // transformation matrix from body to world frame
Vector3f corrected_delta_ang = _imu_sample_delayed.delta_ang - _R_prev * _earth_rate_NED *
_imu_sample_delayed.delta_ang_dt;
Quaternion dq; // delta quaternion since last update
dq.from_axis_angle(corrected_delta_ang);
_state.quat_nominal = dq * _state.quat_nominal;
_state.quat_nominal.normalize();
_R_prev = R_to_earth.transpose();
Vector3f vel_last = _state.vel;
// predict velocity states
_state.vel += R_to_earth * _imu_sample_delayed.delta_vel;
_state.vel(2) += 9.81f * _imu_sample_delayed.delta_vel_dt;
// predict position states via trapezoidal integration of velocity
_state.pos += (vel_last + _state.vel) * _imu_sample_delayed.delta_vel_dt * 0.5f;
constrainStates();
}
bool Ekf::collect_imu(imuSample &imu)
{
imu.delta_ang(0) = imu.delta_ang(0) * _state.gyro_scale(0);
imu.delta_ang(1) = imu.delta_ang(1) * _state.gyro_scale(1);
imu.delta_ang(2) = imu.delta_ang(2) * _state.gyro_scale(2);
imu.delta_ang -= _state.gyro_bias * imu.delta_ang_dt / (_dt_imu_avg > 0 ? _dt_imu_avg : 0.01f);
imu.delta_vel(2) -= _state.accel_z_bias * imu.delta_vel_dt / (_dt_imu_avg > 0 ? _dt_imu_avg : 0.01f);;
// store the new sample for the complementary filter prediciton
_imu_sample_new = {
.delta_ang = imu.delta_ang,
.delta_vel = imu.delta_vel,
.delta_ang_dt = imu.delta_ang_dt,
.delta_vel_dt = imu.delta_vel_dt,
.time_us = imu.time_us
};
_imu_down_sampled.delta_ang_dt += imu.delta_ang_dt;
_imu_down_sampled.delta_vel_dt += imu.delta_vel_dt;
Quaternion delta_q;
delta_q.rotate(imu.delta_ang);
_q_down_sampled = _q_down_sampled * delta_q;
_q_down_sampled.normalize();
matrix::Dcm<float> delta_R(delta_q.inversed());
_imu_down_sampled.delta_vel = delta_R * _imu_down_sampled.delta_vel;
_imu_down_sampled.delta_vel += imu.delta_vel;
if ((_dt_imu_avg * _imu_ticks >= (float)(FILTER_UPDATE_PERRIOD_MS) / 1000) ||
_dt_imu_avg * _imu_ticks >= 0.02f) {
imu = {
.delta_ang = _q_down_sampled.to_axis_angle(),
.delta_vel = _imu_down_sampled.delta_vel,
.delta_ang_dt = _imu_down_sampled.delta_ang_dt,
.delta_vel_dt = _imu_down_sampled.delta_vel_dt,
.time_us = imu.time_us
};
_imu_down_sampled.delta_ang.setZero();
_imu_down_sampled.delta_vel.setZero();
_imu_down_sampled.delta_ang_dt = 0.0f;
_imu_down_sampled.delta_vel_dt = 0.0f;
_q_down_sampled(0) = 1.0f;
_q_down_sampled(1) = _q_down_sampled(2) = _q_down_sampled(3) = 0.0f;
return true;
}
return false;
}
void Ekf::calculateOutputStates()
{
imuSample imu_new = _imu_sample_new;
Vector3f delta_angle;
// Note: We do no not need to consider any bias or scale correction here
// since the base class has already corrected the imu sample
delta_angle(0) = imu_new.delta_ang(0);
delta_angle(1) = imu_new.delta_ang(1);
delta_angle(2) = imu_new.delta_ang(2);
Vector3f delta_vel = imu_new.delta_vel;
delta_angle += _delta_angle_corr;
Quaternion dq;
dq.from_axis_angle(delta_angle);
_output_new.time_us = imu_new.time_us;
_output_new.quat_nominal = dq * _output_new.quat_nominal;
_output_new.quat_nominal.normalize();
matrix::Dcm<float> R_to_earth(_output_new.quat_nominal);
Vector3f delta_vel_NED = R_to_earth * delta_vel + _delta_vel_corr;
delta_vel_NED(2) += 9.81f * imu_new.delta_vel_dt;
Vector3f vel_last = _output_new.vel;
_output_new.vel += delta_vel_NED;
_output_new.pos += (_output_new.vel + vel_last) * (imu_new.delta_vel_dt * 0.5f) + _vel_corr * imu_new.delta_vel_dt;
if (_imu_updated) {
_output_buffer.push(_output_new);
_imu_updated = false;
}
_output_sample_delayed = _output_buffer.get_oldest();
Quaternion quat_inv = _state.quat_nominal.inversed();
Quaternion q_error = _output_sample_delayed.quat_nominal * quat_inv;
q_error.normalize();
Vector3f delta_ang_error;
float scalar;
if (q_error(0) >= 0.0f) {
scalar = -2.0f;
} else {
scalar = 2.0f;
}
delta_ang_error(0) = scalar * q_error(1);
delta_ang_error(1) = scalar * q_error(2);
delta_ang_error(2) = scalar * q_error(3);
_delta_angle_corr = delta_ang_error * imu_new.delta_ang_dt;
_delta_vel_corr = (_state.vel - _output_sample_delayed.vel) * imu_new.delta_vel_dt;
_vel_corr = (_state.pos - _output_sample_delayed.pos);
}
void Ekf::fuseAirspeed()
{
}
void Ekf::fuseRange()
{
}
void Ekf::printStates()
{
static int counter = 0;
if (counter % 50 == 0) {
printf("quaternion\n");
for (int i = 0; i < 4; i++) {
printf("quat %i %.5f\n", i, (double)_state.quat_nominal(i));
}
matrix::Euler<float> euler(_state.quat_nominal);
printf("yaw pitch roll %.5f %.5f %.5f\n", (double)euler(2), (double)euler(1), (double)euler(0));
printf("vel\n");
for (int i = 0; i < 3; i++) {
printf("v %i %.5f\n", i, (double)_state.vel(i));
}
printf("pos\n");
for (int i = 0; i < 3; i++) {
printf("p %i %.5f\n", i, (double)_state.pos(i));
}
printf("gyro_scale\n");
for (int i = 0; i < 3; i++) {
printf("gs %i %.5f\n", i, (double)_state.gyro_scale(i));
}
printf("mag earth\n");
for (int i = 0; i < 3; i++) {
printf("mI %i %.5f\n", i, (double)_state.mag_I(i));
}
printf("mag bias\n");
for (int i = 0; i < 3; i++) {
printf("mB %i %.5f\n", i, (double)_state.mag_B(i));
}
counter = 0;
}
counter++;
}
void Ekf::printStatesFast()
{
static int counter_fast = 0;
if (counter_fast % 50 == 0) {
printf("quaternion\n");
for (int i = 0; i < 4; i++) {
printf("quat %i %.5f\n", i, (double)_output_new.quat_nominal(i));
}
printf("vel\n");
for (int i = 0; i < 3; i++) {
printf("v %i %.5f\n", i, (double)_output_new.vel(i));
}
printf("pos\n");
for (int i = 0; i < 3; i++) {
printf("p %i %.5f\n", i, (double)_output_new.pos(i));
}
counter_fast = 0;
}
counter_fast++;
}