ardupilot/libraries/AP_Compass/Compass_learn.cpp

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/// -*- tab-width: 4; Mode: C++; c-basic-offset: 4; indent-tabs-mode: nil -*-
#include "Compass.h"
#include <math.h>
// don't allow any axis of the offset to go above 2000
#define COMPASS_OFS_LIMIT 2000
/*
* this offset learning algorithm is inspired by this paper from Bill Premerlani
*
* http://gentlenav.googlecode.com/files/MagnetometerOffsetNullingRevisited.pdf
*
* The base algorithm works well, but is quite sensitive to
* noise. After long discussions with Bill, the following changes were
* made:
*
* 1) we keep a history buffer that effectively divides the mag
* vectors into a set of N streams. The algorithm is run on the
* streams separately
*
* 2) within each stream we only calculate a change when the mag
* vector has changed by a significant amount.
*
* This gives us the property that we learn quickly if there is no
* noise, but still learn correctly (and slowly) in the face of lots of
* noise.
*/
void
Compass::learn_offsets(void)
{
if (_learn == 0) {
// auto-calibration is disabled
return;
}
// this gain is set so we converge on the offsets in about 5
// minutes with a 10Hz compass
const float gain = 0.01f;
const float max_change = 10.0f;
const float min_diff = 50.0f;
if (!_null_init_done) {
// first time through
_null_init_done = true;
for (uint8_t k=0; k<COMPASS_MAX_INSTANCES; k++) {
const Vector3f &field = _state[k].field;
const Vector3f &ofs = _state[k].offset.get();
for (uint8_t i=0; i<_mag_history_size; i++) {
// fill the history buffer with the current mag vector,
// with the offset removed
_state[k].mag_history[i] = Vector3i(roundf(field.x) - ofs.x,
roundf(field.y) - ofs.y,
roundf(field.z) - ofs.z);
}
_state[k].mag_history_index = 0;
}
return;
}
for (uint8_t k=0; k<COMPASS_MAX_INSTANCES; k++) {
const Vector3f &ofs = _state[k].offset.get();
const Vector3f &field = _state[k].field;
Vector3f b1, diff;
float length;
if (ofs.is_nan()) {
// offsets are bad possibly due to a past bug - zero them
_state[k].offset.set(Vector3f());
}
// get a past element
b1 = Vector3f(_state[k].mag_history[_state[k].mag_history_index].x,
_state[k].mag_history[_state[k].mag_history_index].y,
_state[k].mag_history[_state[k].mag_history_index].z);
// the history buffer doesn't have the offsets
b1 += ofs;
// get the current vector
const Vector3f &b2 = field;
// calculate the delta for this sample
diff = b2 - b1;
length = diff.length();
if (length < min_diff) {
// the mag vector hasn't changed enough - we don't get
// enough information from this vector to use it.
// Note that we don't put the current vector into the mag
// history here. We want to wait for a larger rotation to
// build up before calculating an offset change, as accuracy
// of the offset change is highly dependent on the size of the
// rotation.
_state[k].mag_history_index = (_state[k].mag_history_index + 1) % _mag_history_size;
continue;
}
// put the vector in the history
_state[k].mag_history[_state[k].mag_history_index] = Vector3i(roundf(field.x) - ofs.x,
roundf(field.y) - ofs.y,
roundf(field.z) - ofs.z);
_state[k].mag_history_index = (_state[k].mag_history_index + 1) % _mag_history_size;
// equation 6 of Bills paper
diff = diff * (gain * (b2.length() - b1.length()) / length);
// limit the change from any one reading. This is to prevent
// single crazy readings from throwing off the offsets for a long
// time
length = diff.length();
if (length > max_change) {
diff *= max_change / length;
}
Vector3f new_offsets = _state[k].offset.get() - diff;
if (new_offsets.is_nan()) {
// don't apply bad offsets
continue;
}
// constrain offsets
new_offsets.x = constrain_float(new_offsets.x, -COMPASS_OFS_LIMIT, COMPASS_OFS_LIMIT);
new_offsets.y = constrain_float(new_offsets.y, -COMPASS_OFS_LIMIT, COMPASS_OFS_LIMIT);
new_offsets.z = constrain_float(new_offsets.z, -COMPASS_OFS_LIMIT, COMPASS_OFS_LIMIT);
// set the new offsets
_state[k].offset.set(new_offsets);
}
}