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ardupilot/libraries/AP_Compass/CompassCalibrator.cpp

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/*
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
/*
* The intention of a magnetometer in a compass application is to measure
* Earth's magnetic field. Measurements other than those of Earth's magnetic
* field are considered errors. This algorithm computes a set of correction
* parameters that null out errors from various sources:
*
* - Sensor bias error
* - "Hard iron" error caused by materials fixed to the vehicle body that
* produce static magnetic fields.
* - Sensor scale-factor error
* - Sensor cross-axis sensitivity
* - "Soft iron" error caused by materials fixed to the vehicle body that
* distort magnetic fields.
*
* This is done by taking a set of samples that are assumed to be the product
* of rotation in earth's magnetic field and fitting an offset ellipsoid to
* them, determining the correction to be applied to adjust the samples into an
* origin-centered sphere.
*
* The state machine of this library is described entirely by the
* CompassCalibrator::Status enum, and all state transitions are managed by the
* set_status function. Normally, the library is in the NOT_STARTED state. When
* the start function is called, the state transitions to WAITING_TO_START,
* until two conditions are met: the delay as elapsed, and the memory for the
* sample buffer has been successfully allocated.
* Once these conditions are met, the state transitions to RUNNING_STEP_ONE, and
* samples are collected via calls to the new_sample function. These samples are
* accepted or rejected based on distance to the nearest sample. The samples are
* assumed to cover the surface of a sphere, and the radius of that sphere is
* initialized to a conservative value. Based on a circle-packing pattern, the
* minimum distance is set such that some percentage of the surface of that
* sphere must be covered by samples.
*
* Once the sample buffer is full, a sphere fitting algorithm is run, which
* computes a new sphere radius. The sample buffer is thinned of samples which
* no longer meet the acceptance criteria, and the state transitions to
* RUNNING_STEP_TWO. Samples continue to be collected until the buffer is full
* again, the full ellipsoid fit is run, and the state transitions to either
* SUCCESS or FAILED.
*
* The fitting algorithm used is Levenberg-Marquardt. See also:
* http://en.wikipedia.org/wiki/Levenberg%E2%80%93Marquardt_algorithm
*/
#include "CompassCalibrator.h"
#include <AP_HAL/AP_HAL.h>
#include <AP_Math/AP_GeodesicGrid.h>
#include <AP_AHRS/AP_AHRS.h>
#include <AP_GPS/AP_GPS.h>
#include <GCS_MAVLink/GCS.h>
#define FIELD_RADIUS_MIN 150
#define FIELD_RADIUS_MAX 950
extern const AP_HAL::HAL& hal;
////////////////////////////////////////////////////////////
///////////////////// PUBLIC INTERFACE /////////////////////
////////////////////////////////////////////////////////////
CompassCalibrator::CompassCalibrator()
{
stop();
}
void CompassCalibrator::stop()
{
set_status(Status::NOT_STARTED);
}
void CompassCalibrator::set_orientation(enum Rotation orientation, bool is_external, bool fix_orientation)
{
_check_orientation = true;
_orientation = orientation;
_orig_orientation = orientation;
_is_external = is_external;
_fix_orientation = fix_orientation;
}
void CompassCalibrator::start(bool retry, float delay, uint16_t offset_max, uint8_t compass_idx)
{
if (running()) {
return;
}
_offset_max = offset_max;
_attempt = 1;
_retry = retry;
_delay_start_sec = delay;
_start_time_ms = AP_HAL::millis();
_compass_idx = compass_idx;
set_status(Status::WAITING_TO_START);
}
void CompassCalibrator::get_calibration(Vector3f &offsets, Vector3f &diagonals, Vector3f &offdiagonals, float &scale_factor)
{
if (_status != Status::SUCCESS) {
return;
}
offsets = _params.offset;
diagonals = _params.diag;
offdiagonals = _params.offdiag;
scale_factor = _params.scale_factor;
}
float CompassCalibrator::get_completion_percent() const
{
// first sampling step is 1/3rd of the progress bar
// never return more than 99% unless _status is Status::SUCCESS
switch (_status) {
case Status::NOT_STARTED:
case Status::WAITING_TO_START:
return 0.0f;
case Status::RUNNING_STEP_ONE:
return 33.3f * _samples_collected/COMPASS_CAL_NUM_SAMPLES;
case Status::RUNNING_STEP_TWO:
return 33.3f + 65.7f*((float)(_samples_collected-_samples_thinned)/(COMPASS_CAL_NUM_SAMPLES-_samples_thinned));
case Status::SUCCESS:
return 100.0f;
case Status::FAILED:
case Status::BAD_ORIENTATION:
case Status::BAD_RADIUS:
return 0.0f;
};
// will not get here if the compiler is doing its job (no default clause)
return 0.0f;
}
// update completion mask based on latest sample
// used to ensure we have collected samples in all directions
void CompassCalibrator::update_completion_mask(const Vector3f& v)
{
Matrix3f softiron {
_params.diag.x, _params.offdiag.x, _params.offdiag.y,
_params.offdiag.x, _params.diag.y, _params.offdiag.z,
_params.offdiag.y, _params.offdiag.z, _params.diag.z
};
Vector3f corrected = softiron * (v + _params.offset);
int section = AP_GeodesicGrid::section(corrected, true);
if (section < 0) {
return;
}
_completion_mask[section / 8] |= 1 << (section % 8);
}
// reset and update the completion mask using all samples in the sample buffer
void CompassCalibrator::update_completion_mask()
{
memset(_completion_mask, 0, sizeof(_completion_mask));
for (int i = 0; i < _samples_collected; i++) {
update_completion_mask(_sample_buffer[i].get());
}
}
bool CompassCalibrator::check_for_timeout()
{
uint32_t tnow = AP_HAL::millis();
if (running() && tnow - _last_sample_ms > 1000) {
_retry = false;
set_status(Status::FAILED);
return true;
}
return false;
}
void CompassCalibrator::new_sample(const Vector3f& sample)
{
_last_sample_ms = AP_HAL::millis();
if (_status == Status::WAITING_TO_START) {
set_status(Status::RUNNING_STEP_ONE);
}
if (running() && _samples_collected < COMPASS_CAL_NUM_SAMPLES && accept_sample(sample)) {
update_completion_mask(sample);
_sample_buffer[_samples_collected].set(sample);
_sample_buffer[_samples_collected].att.set_from_ahrs();
_samples_collected++;
}
}
void CompassCalibrator::update(bool &failure)
{
failure = false;
// collect the minimum number of samples
if (!fitting()) {
return;
}
if (_status == Status::RUNNING_STEP_ONE) {
if (_fit_step >= 10) {
if (is_equal(_fitness, _initial_fitness) || isnan(_fitness)) { // if true, means that fitness is diverging instead of converging
set_status(Status::FAILED);
failure = true;
} else {
set_status(Status::RUNNING_STEP_TWO);
}
} else {
if (_fit_step == 0) {
calc_initial_offset();
}
run_sphere_fit();
_fit_step++;
}
} else if (_status == Status::RUNNING_STEP_TWO) {
if (_fit_step >= 35) {
if (fit_acceptable() && fix_radius() && calculate_orientation()) {
set_status(Status::SUCCESS);
} else {
set_status(Status::FAILED);
failure = true;
}
} else if (_fit_step < 15) {
run_sphere_fit();
_fit_step++;
} else {
run_ellipsoid_fit();
_fit_step++;
}
}
}
/////////////////////////////////////////////////////////////
////////////////////// PRIVATE METHODS //////////////////////
/////////////////////////////////////////////////////////////
bool CompassCalibrator::running() const
{
return _status == Status::RUNNING_STEP_ONE || _status == Status::RUNNING_STEP_TWO;
}
bool CompassCalibrator::fitting() const
{
return running() && (_samples_collected == COMPASS_CAL_NUM_SAMPLES);
}
// initialize fitness before starting a fit
void CompassCalibrator::initialize_fit()
{
if (_samples_collected != 0) {
_fitness = calc_mean_squared_residuals(_params);
} else {
_fitness = 1.0e30f;
}
_initial_fitness = _fitness;
_sphere_lambda = 1.0f;
_ellipsoid_lambda = 1.0f;
_fit_step = 0;
}
void CompassCalibrator::reset_state()
{
_samples_collected = 0;
_samples_thinned = 0;
_params.radius = 200;
_params.offset.zero();
_params.diag = Vector3f(1.0f,1.0f,1.0f);
_params.offdiag.zero();
_params.scale_factor = 0;
memset(_completion_mask, 0, sizeof(_completion_mask));
initialize_fit();
}
bool CompassCalibrator::set_status(CompassCalibrator::Status status)
{
if (status != Status::NOT_STARTED && _status == status) {
return true;
}
switch (status) {
case Status::NOT_STARTED:
reset_state();
_status = Status::NOT_STARTED;
if (_sample_buffer != nullptr) {
free(_sample_buffer);
_sample_buffer = nullptr;
}
return true;
case Status::WAITING_TO_START:
reset_state();
_status = Status::WAITING_TO_START;
set_status(Status::RUNNING_STEP_ONE);
return true;
case Status::RUNNING_STEP_ONE:
if (_status != Status::WAITING_TO_START) {
return false;
}
// on first attempt delay start if requested by caller
if (_attempt == 1 && (AP_HAL::millis()-_start_time_ms)*1.0e-3f < _delay_start_sec) {
return false;
}
if (_sample_buffer == nullptr) {
_sample_buffer = (CompassSample*)calloc(COMPASS_CAL_NUM_SAMPLES, sizeof(CompassSample));
}
if (_sample_buffer != nullptr) {
initialize_fit();
_status = Status::RUNNING_STEP_ONE;
return true;
}
return false;
case Status::RUNNING_STEP_TWO:
if (_status != Status::RUNNING_STEP_ONE) {
return false;
}
thin_samples();
initialize_fit();
_status = Status::RUNNING_STEP_TWO;
return true;
case Status::SUCCESS:
if (_status != Status::RUNNING_STEP_TWO) {
return false;
}
if (_sample_buffer != nullptr) {
free(_sample_buffer);
_sample_buffer = nullptr;
}
_status = Status::SUCCESS;
return true;
case Status::FAILED:
if (_status == Status::BAD_ORIENTATION ||
_status == Status::BAD_RADIUS) {
// don't overwrite bad orientation status
return false;
}
FALLTHROUGH;
case Status::BAD_ORIENTATION:
case Status::BAD_RADIUS:
if (_status == Status::NOT_STARTED) {
return false;
}
if (_retry && set_status(Status::WAITING_TO_START)) {
_attempt++;
return true;
}
if (_sample_buffer != nullptr) {
free(_sample_buffer);
_sample_buffer = nullptr;
}
_status = status;
return true;
default:
return false;
};
}
bool CompassCalibrator::fit_acceptable()
{
if (!isnan(_fitness) &&
_params.radius > FIELD_RADIUS_MIN && _params.radius < FIELD_RADIUS_MAX &&
fabsf(_params.offset.x) < _offset_max &&
fabsf(_params.offset.y) < _offset_max &&
fabsf(_params.offset.z) < _offset_max &&
_params.diag.x > 0.2f && _params.diag.x < 5.0f &&
_params.diag.y > 0.2f && _params.diag.y < 5.0f &&
_params.diag.z > 0.2f && _params.diag.z < 5.0f &&
fabsf(_params.offdiag.x) < 1.0f && //absolute of sine/cosine output cannot be greater than 1
fabsf(_params.offdiag.y) < 1.0f &&
fabsf(_params.offdiag.z) < 1.0f ) {
return _fitness <= sq(_tolerance);
}
return false;
}
void CompassCalibrator::thin_samples()
{
if (_sample_buffer == nullptr) {
return;
}
_samples_thinned = 0;
// shuffle the samples http://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle
// this is so that adjacent samples don't get sequentially eliminated
for (uint16_t i=_samples_collected-1; i>=1; i--) {
uint16_t j = get_random16() % (i+1);
CompassSample temp = _sample_buffer[i];
_sample_buffer[i] = _sample_buffer[j];
_sample_buffer[j] = temp;
}
// remove any samples that are close together
for (uint16_t i=0; i < _samples_collected; i++) {
if (!accept_sample(_sample_buffer[i], i)) {
_sample_buffer[i] = _sample_buffer[_samples_collected-1];
_samples_collected--;
_samples_thinned++;
}
}
update_completion_mask();
}
/*
* The sample acceptance distance is determined as follows:
* For any regular polyhedron with triangular faces, the angle theta subtended
* by two closest points is defined as
*
* theta = arccos(cos(A)/(1-cos(A)))
*
* Where:
* A = (4pi/F + pi)/3
* and
* F = 2V - 4 is the number of faces for the polyhedron in consideration,
* which depends on the number of vertices V
*
* The above equation was proved after solving for spherical triangular excess
* and related equations.
*/
bool CompassCalibrator::accept_sample(const Vector3f& sample, uint16_t skip_index)
{
static const uint16_t faces = (2 * COMPASS_CAL_NUM_SAMPLES - 4);
static const float a = (4.0f * M_PI / (3.0f * faces)) + M_PI / 3.0f;
static const float theta = 0.5f * acosf(cosf(a) / (1.0f - cosf(a)));
if (_sample_buffer == nullptr) {
return false;
}
float min_distance = _params.radius * 2*sinf(theta/2);
for (uint16_t i = 0; i<_samples_collected; i++) {
if (i != skip_index) {
float distance = (sample - _sample_buffer[i].get()).length();
if (distance < min_distance) {
return false;
}
}
}
return true;
}
bool CompassCalibrator::accept_sample(const CompassSample& sample, uint16_t skip_index)
{
return accept_sample(sample.get(), skip_index);
}
float CompassCalibrator::calc_residual(const Vector3f& sample, const param_t& params) const
{
Matrix3f softiron(
params.diag.x , params.offdiag.x , params.offdiag.y,
params.offdiag.x , params.diag.y , params.offdiag.z,
params.offdiag.y , params.offdiag.z , params.diag.z
);
return params.radius - (softiron*(sample+params.offset)).length();
}
// calc the fitness given a set of parameters (offsets, diagonals, off diagonals)
float CompassCalibrator::calc_mean_squared_residuals(const param_t& params) const
{
if (_sample_buffer == nullptr || _samples_collected == 0) {
return 1.0e30f;
}
float sum = 0.0f;
for (uint16_t i=0; i < _samples_collected; i++) {
Vector3f sample = _sample_buffer[i].get();
float resid = calc_residual(sample, params);
sum += sq(resid);
}
sum /= _samples_collected;
return sum;
}
// calculate initial offsets by simply taking the average values of the samples
void CompassCalibrator::calc_initial_offset()
{
// Set initial offset to the average value of the samples
_params.offset.zero();
for (uint16_t k = 0; k < _samples_collected; k++) {
_params.offset -= _sample_buffer[k].get();
}
_params.offset /= _samples_collected;
}
void CompassCalibrator::calc_sphere_jacob(const Vector3f& sample, const param_t& params, float* ret) const
{
const Vector3f &offset = params.offset;
const Vector3f &diag = params.diag;
const Vector3f &offdiag = params.offdiag;
Matrix3f softiron(
diag.x , offdiag.x , offdiag.y,
offdiag.x , diag.y , offdiag.z,
offdiag.y , offdiag.z , diag.z
);
float A = (diag.x * (sample.x + offset.x)) + (offdiag.x * (sample.y + offset.y)) + (offdiag.y * (sample.z + offset.z));
float B = (offdiag.x * (sample.x + offset.x)) + (diag.y * (sample.y + offset.y)) + (offdiag.z * (sample.z + offset.z));
float C = (offdiag.y * (sample.x + offset.x)) + (offdiag.z * (sample.y + offset.y)) + (diag.z * (sample.z + offset.z));
float length = (softiron*(sample+offset)).length();
// 0: partial derivative (radius wrt fitness fn) fn operated on sample
ret[0] = 1.0f;
// 1-3: partial derivative (offsets wrt fitness fn) fn operated on sample
ret[1] = -1.0f * (((diag.x * A) + (offdiag.x * B) + (offdiag.y * C))/length);
ret[2] = -1.0f * (((offdiag.x * A) + (diag.y * B) + (offdiag.z * C))/length);
ret[3] = -1.0f * (((offdiag.y * A) + (offdiag.z * B) + (diag.z * C))/length);
}
// run sphere fit to calculate diagonals and offdiagonals
void CompassCalibrator::run_sphere_fit()
{
if (_sample_buffer == nullptr) {
return;
}
const float lma_damping = 10.0f;
// take backup of fitness and parameters so we can determine later if this fit has improved the calibration
float fitness = _fitness;
float fit1, fit2;
param_t fit1_params, fit2_params;
fit1_params = fit2_params = _params;
float JTJ[COMPASS_CAL_NUM_SPHERE_PARAMS*COMPASS_CAL_NUM_SPHERE_PARAMS] = { };
float JTJ2[COMPASS_CAL_NUM_SPHERE_PARAMS*COMPASS_CAL_NUM_SPHERE_PARAMS] = { };
float JTFI[COMPASS_CAL_NUM_SPHERE_PARAMS] = { };
// Gauss Newton Part common for all kind of extensions including LM
for (uint16_t k = 0; k<_samples_collected; k++) {
Vector3f sample = _sample_buffer[k].get();
float sphere_jacob[COMPASS_CAL_NUM_SPHERE_PARAMS];
calc_sphere_jacob(sample, fit1_params, sphere_jacob);
for (uint8_t i = 0;i < COMPASS_CAL_NUM_SPHERE_PARAMS; i++) {
// compute JTJ
for (uint8_t j = 0; j < COMPASS_CAL_NUM_SPHERE_PARAMS; j++) {
JTJ[i*COMPASS_CAL_NUM_SPHERE_PARAMS+j] += sphere_jacob[i] * sphere_jacob[j];
JTJ2[i*COMPASS_CAL_NUM_SPHERE_PARAMS+j] += sphere_jacob[i] * sphere_jacob[j]; //a backup JTJ for LM
}
// compute JTFI
JTFI[i] += sphere_jacob[i] * calc_residual(sample, fit1_params);
}
}
//------------------------Levenberg-Marquardt-part-starts-here---------------------------------//
// refer: http://en.wikipedia.org/wiki/Levenberg%E2%80%93Marquardt_algorithm#Choice_of_damping_parameter
for (uint8_t i = 0; i < COMPASS_CAL_NUM_SPHERE_PARAMS; i++) {
JTJ[i*COMPASS_CAL_NUM_SPHERE_PARAMS+i] += _sphere_lambda;
JTJ2[i*COMPASS_CAL_NUM_SPHERE_PARAMS+i] += _sphere_lambda/lma_damping;
}
if (!inverse(JTJ, JTJ, 4)) {
return;
}
if (!inverse(JTJ2, JTJ2, 4)) {
return;
}
// extract radius, offset, diagonals and offdiagonal parameters
for (uint8_t row=0; row < COMPASS_CAL_NUM_SPHERE_PARAMS; row++) {
for (uint8_t col=0; col < COMPASS_CAL_NUM_SPHERE_PARAMS; col++) {
fit1_params.get_sphere_params()[row] -= JTFI[col] * JTJ[row*COMPASS_CAL_NUM_SPHERE_PARAMS+col];
fit2_params.get_sphere_params()[row] -= JTFI[col] * JTJ2[row*COMPASS_CAL_NUM_SPHERE_PARAMS+col];
}
}
// calculate fitness of two possible sets of parameters
fit1 = calc_mean_squared_residuals(fit1_params);
fit2 = calc_mean_squared_residuals(fit2_params);
// decide which of the two sets of parameters is best and store in fit1_params
if (fit1 > _fitness && fit2 > _fitness) {
// if neither set of parameters provided better results, increase lambda
_sphere_lambda *= lma_damping;
} else if (fit2 < _fitness && fit2 < fit1) {
// if fit2 was better we will use it. decrease lambda
_sphere_lambda /= lma_damping;
fit1_params = fit2_params;
fitness = fit2;
} else if (fit1 < _fitness) {
fitness = fit1;
}
//--------------------Levenberg-Marquardt-part-ends-here--------------------------------//
// store new parameters and update fitness
if (!isnan(fitness) && fitness < _fitness) {
_fitness = fitness;
_params = fit1_params;
update_completion_mask();
}
}
void CompassCalibrator::calc_ellipsoid_jacob(const Vector3f& sample, const param_t& params, float* ret) const
{
const Vector3f &offset = params.offset;
const Vector3f &diag = params.diag;
const Vector3f &offdiag = params.offdiag;
Matrix3f softiron(
diag.x , offdiag.x , offdiag.y,
offdiag.x , diag.y , offdiag.z,
offdiag.y , offdiag.z , diag.z
);
float A = (diag.x * (sample.x + offset.x)) + (offdiag.x * (sample.y + offset.y)) + (offdiag.y * (sample.z + offset.z));
float B = (offdiag.x * (sample.x + offset.x)) + (diag.y * (sample.y + offset.y)) + (offdiag.z * (sample.z + offset.z));
float C = (offdiag.y * (sample.x + offset.x)) + (offdiag.z * (sample.y + offset.y)) + (diag.z * (sample.z + offset.z));
float length = (softiron*(sample+offset)).length();
// 0-2: partial derivative (offset wrt fitness fn) fn operated on sample
ret[0] = -1.0f * (((diag.x * A) + (offdiag.x * B) + (offdiag.y * C))/length);
ret[1] = -1.0f * (((offdiag.x * A) + (diag.y * B) + (offdiag.z * C))/length);
ret[2] = -1.0f * (((offdiag.y * A) + (offdiag.z * B) + (diag.z * C))/length);
// 3-5: partial derivative (diag offset wrt fitness fn) fn operated on sample
ret[3] = -1.0f * ((sample.x + offset.x) * A)/length;
ret[4] = -1.0f * ((sample.y + offset.y) * B)/length;
ret[5] = -1.0f * ((sample.z + offset.z) * C)/length;
// 6-8: partial derivative (off-diag offset wrt fitness fn) fn operated on sample
ret[6] = -1.0f * (((sample.y + offset.y) * A) + ((sample.x + offset.x) * B))/length;
ret[7] = -1.0f * (((sample.z + offset.z) * A) + ((sample.x + offset.x) * C))/length;
ret[8] = -1.0f * (((sample.z + offset.z) * B) + ((sample.y + offset.y) * C))/length;
}
void CompassCalibrator::run_ellipsoid_fit()
{
if (_sample_buffer == nullptr) {
return;
}
const float lma_damping = 10.0f;
// take backup of fitness and parameters so we can determine later if this fit has improved the calibration
float fitness = _fitness;
float fit1, fit2;
param_t fit1_params, fit2_params;
fit1_params = fit2_params = _params;
float JTJ[COMPASS_CAL_NUM_ELLIPSOID_PARAMS*COMPASS_CAL_NUM_ELLIPSOID_PARAMS] = { };
float JTJ2[COMPASS_CAL_NUM_ELLIPSOID_PARAMS*COMPASS_CAL_NUM_ELLIPSOID_PARAMS] = { };
float JTFI[COMPASS_CAL_NUM_ELLIPSOID_PARAMS] = { };
// Gauss Newton Part common for all kind of extensions including LM
for (uint16_t k = 0; k<_samples_collected; k++) {
Vector3f sample = _sample_buffer[k].get();
float ellipsoid_jacob[COMPASS_CAL_NUM_ELLIPSOID_PARAMS];
calc_ellipsoid_jacob(sample, fit1_params, ellipsoid_jacob);
for (uint8_t i = 0;i < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; i++) {
// compute JTJ
for (uint8_t j = 0; j < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; j++) {
JTJ [i*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+j] += ellipsoid_jacob[i] * ellipsoid_jacob[j];
JTJ2[i*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+j] += ellipsoid_jacob[i] * ellipsoid_jacob[j];
}
// compute JTFI
JTFI[i] += ellipsoid_jacob[i] * calc_residual(sample, fit1_params);
}
}
//------------------------Levenberg-Marquardt-part-starts-here---------------------------------//
//refer: http://en.wikipedia.org/wiki/Levenberg%E2%80%93Marquardt_algorithm#Choice_of_damping_parameter
for (uint8_t i = 0; i < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; i++) {
JTJ[i*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+i] += _ellipsoid_lambda;
JTJ2[i*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+i] += _ellipsoid_lambda/lma_damping;
}
if (!inverse(JTJ, JTJ, 9)) {
return;
}
if (!inverse(JTJ2, JTJ2, 9)) {
return;
}
// extract radius, offset, diagonals and offdiagonal parameters
for (uint8_t row=0; row < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; row++) {
for (uint8_t col=0; col < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; col++) {
fit1_params.get_ellipsoid_params()[row] -= JTFI[col] * JTJ[row*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+col];
fit2_params.get_ellipsoid_params()[row] -= JTFI[col] * JTJ2[row*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+col];
}
}
// calculate fitness of two possible sets of parameters
fit1 = calc_mean_squared_residuals(fit1_params);
fit2 = calc_mean_squared_residuals(fit2_params);
// decide which of the two sets of parameters is best and store in fit1_params
if (fit1 > _fitness && fit2 > _fitness) {
// if neither set of parameters provided better results, increase lambda
_ellipsoid_lambda *= lma_damping;
} else if (fit2 < _fitness && fit2 < fit1) {
// if fit2 was better we will use it. decrease lambda
_ellipsoid_lambda /= lma_damping;
fit1_params = fit2_params;
fitness = fit2;
} else if (fit1 < _fitness) {
fitness = fit1;
}
//--------------------Levenberg-part-ends-here--------------------------------//
// store new parameters and update fitness
if (fitness < _fitness) {
_fitness = fitness;
_params = fit1_params;
update_completion_mask();
}
}
//////////////////////////////////////////////////////////
//////////// CompassSample public interface //////////////
//////////////////////////////////////////////////////////
#define COMPASS_CAL_SAMPLE_SCALE_TO_FIXED(__X) ((int16_t)constrain_float(roundf(__X*8.0f), INT16_MIN, INT16_MAX))
#define COMPASS_CAL_SAMPLE_SCALE_TO_FLOAT(__X) (__X/8.0f)
Vector3f CompassCalibrator::CompassSample::get() const
{
return Vector3f(COMPASS_CAL_SAMPLE_SCALE_TO_FLOAT(x),
COMPASS_CAL_SAMPLE_SCALE_TO_FLOAT(y),
COMPASS_CAL_SAMPLE_SCALE_TO_FLOAT(z));
}
void CompassCalibrator::CompassSample::set(const Vector3f &in)
{
x = COMPASS_CAL_SAMPLE_SCALE_TO_FIXED(in.x);
y = COMPASS_CAL_SAMPLE_SCALE_TO_FIXED(in.y);
z = COMPASS_CAL_SAMPLE_SCALE_TO_FIXED(in.z);
}
void CompassCalibrator::AttitudeSample::set_from_ahrs(void)
{
const Matrix3f &dcm = AP::ahrs().get_DCM_rotation_body_to_ned();
float roll_rad, pitch_rad, yaw_rad;
dcm.to_euler(&roll_rad, &pitch_rad, &yaw_rad);
roll = constrain_int16(127 * (roll_rad / M_PI), -127, 127);
pitch = constrain_int16(127 * (pitch_rad / M_PI_2), -127, 127);
yaw = constrain_int16(127 * (yaw_rad / M_PI), -127, 127);
}
Matrix3f CompassCalibrator::AttitudeSample::get_rotmat(void)
{
float roll_rad, pitch_rad, yaw_rad;
roll_rad = roll * (M_PI / 127);
pitch_rad = pitch * (M_PI_2 / 127);
yaw_rad = yaw * (M_PI / 127);
Matrix3f dcm;
dcm.from_euler(roll_rad, pitch_rad, yaw_rad);
return dcm;
}
/*
calculate the implied earth field for a compass sample and compass
rotation. This is used to check for consistency between
samples.
If the orientation is correct then when rotated the same (or
similar) earth field should be given for all samples.
Note that this earth field uses an arbitrary north reference, so it
may not match the true earth field.
*/
Vector3f CompassCalibrator::calculate_earth_field(CompassSample &sample, enum Rotation r)
{
Vector3f v = sample.get();
// convert the sample back to sensor frame
v.rotate_inverse(_orientation);
// rotate to body frame for this rotation
v.rotate(r);
// apply offsets, rotating them for the orientation we are testing
Vector3f rot_offsets = _params.offset;
rot_offsets.rotate_inverse(_orientation);
rot_offsets.rotate(r);
v += rot_offsets;
// rotate the sample from body frame back to earth frame
Matrix3f rot = sample.att.get_rotmat();
Vector3f efield = rot * v;
// earth field is the mag sample in earth frame
return efield;
}
/*
calculate compass orientation using the attitude estimate associated
with each sample, and fix orientation on external compasses if
the feature is enabled
*/
bool CompassCalibrator::calculate_orientation(void)
{
if (!_check_orientation) {
// we are not checking orientation
return true;
}
// this function is very slow
EXPECT_DELAY_MS(1000);
float variance[ROTATION_MAX] {};
for (enum Rotation r = ROTATION_NONE; r<ROTATION_MAX; r = (enum Rotation)(r+1)) {
// calculate the average implied earth field across all samples
Vector3f total_ef {};
for (uint32_t i=0; i<_samples_collected; i++) {
Vector3f efield = calculate_earth_field(_sample_buffer[i], r);
total_ef += efield;
}
Vector3f avg_efield = total_ef / _samples_collected;
// now calculate the square error for this rotation against the average earth field
for (uint32_t i=0; i<_samples_collected; i++) {
Vector3f efield = calculate_earth_field(_sample_buffer[i], r);
float err = (efield - avg_efield).length_squared();
// divide by number of samples collected to get the variance
variance[r] += err / _samples_collected;
}
}
// find the rotation with the lowest variance
enum Rotation besti = ROTATION_NONE;
float bestv = variance[0];
for (enum Rotation r = ROTATION_NONE; r<ROTATION_MAX; r = (enum Rotation)(r+1)) {
if (variance[r] < bestv) {
bestv = variance[r];
besti = r;
}
}
// consider this a pass if the best orientation is 2x better
// variance than 2nd best
const float variance_threshold = 2.0;
float second_best = besti==ROTATION_NONE?variance[1]:variance[0];
enum Rotation besti2 = ROTATION_NONE;
for (enum Rotation r = ROTATION_NONE; r<ROTATION_MAX; r = (enum Rotation)(r+1)) {
if (!rotation_equal(besti, r)) {
if (variance[r] < second_best) {
second_best = variance[r];
besti2 = r;
}
}
}
_orientation_confidence = second_best/bestv;
bool pass;
if (besti == _orientation) {
// if the orientation matched then allow for a low threshold
pass = true;
} else {
pass = _orientation_confidence > variance_threshold;
}
if (!pass) {
gcs().send_text(MAV_SEVERITY_CRITICAL, "Mag(%u) bad orientation: %u/%u %.1f", _compass_idx,
besti, besti2, (double)_orientation_confidence);
} else if (besti == _orientation) {
// no orientation change
gcs().send_text(MAV_SEVERITY_INFO, "Mag(%u) good orientation: %u %.1f", _compass_idx, besti, (double)_orientation_confidence);
} else if (!_is_external || !_fix_orientation) {
gcs().send_text(MAV_SEVERITY_CRITICAL, "Mag(%u) internal bad orientation: %u %.1f", _compass_idx, besti, (double)_orientation_confidence);
} else {
gcs().send_text(MAV_SEVERITY_INFO, "Mag(%u) new orientation: %u was %u %.1f", _compass_idx, besti, _orientation, (double)_orientation_confidence);
}
if (!pass) {
set_status(Status::BAD_ORIENTATION);
return false;
}
if (_orientation == besti) {
// no orientation change
return true;
}
if (!_is_external || !_fix_orientation) {
// we won't change the orientation, but we set _orientation
// for reporting purposes
_orientation = besti;
set_status(Status::BAD_ORIENTATION);
return false;
}
// correct the offsets for the new orientation
Vector3f rot_offsets = _params.offset;
rot_offsets.rotate_inverse(_orientation);
rot_offsets.rotate(besti);
_params.offset = rot_offsets;
// rotate the samples for the new orientation
for (uint32_t i=0; i<_samples_collected; i++) {
Vector3f s = _sample_buffer[i].get();
s.rotate_inverse(_orientation);
s.rotate(besti);
_sample_buffer[i].set(s);
}
_orientation = besti;
// re-run the fit to get the diagonals and off-diagonals for the
// new orientation
initialize_fit();
run_sphere_fit();
run_ellipsoid_fit();
return fit_acceptable();
}
/*
fix radius of the fit to compensate for sensor scale factor errors
return false if radius is outside acceptable range
*/
bool CompassCalibrator::fix_radius(void)
{
if (AP::gps().status() < AP_GPS::GPS_OK_FIX_2D) {
// we don't have a position, leave scale factor as 0. This
// will disable use of WMM in the EKF. Users can manually set
// scale factor after calibration if it is known
_params.scale_factor = 0;
return true;
}
const struct Location &loc = AP::gps().location();
float intensity;
float declination;
float inclination;
AP_Declination::get_mag_field_ef(loc.lat * 1e-7f, loc.lng * 1e-7f, intensity, declination, inclination);
float expected_radius = intensity * 1000; // mGauss
float correction = expected_radius / _params.radius;
if (correction > COMPASS_MAX_SCALE_FACTOR || correction < COMPASS_MIN_SCALE_FACTOR) {
// don't allow more than 30% scale factor correction
gcs().send_text(MAV_SEVERITY_ERROR, "Mag(%u) bad radius %.0f expected %.0f",
_compass_idx,
_params.radius,
expected_radius);
set_status(Status::BAD_RADIUS);
return false;
}
_params.scale_factor = correction;
return true;
}
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