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AP_GPS: move blended-GPS functions into AP_GPS_Blended 

collects all of these together in preparation for making a backend
This commit is contained in:
Peter Barker 2024-03-19 19:00:55 +11:00 committed by Andrew Tridgell
parent 456c1bf39c
commit f487a25e09
2 changed files with 380 additions and 379 deletions
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379
libraries/AP_GPS/AP_GPS.cpp
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@ -66,10 +66,6 @@
#define GPS_BAUD_TIME_MS 1200 #define GPS_BAUD_TIME_MS 1200
#define GPS_TIMEOUT_MS 4000u #define GPS_TIMEOUT_MS 4000u
// defines used to specify the mask position for use of different accuracy metrics in the blending algorithm
#define BLEND_MASK_USE_HPOS_ACC 1
#define BLEND_MASK_USE_VPOS_ACC 2
#define BLEND_MASK_USE_SPD_ACC 4
#define BLEND_COUNTER_FAILURE_INCREMENT 10 #define BLEND_COUNTER_FAILURE_INCREMENT 10
extern const AP_HAL::HAL &hal; extern const AP_HAL::HAL &hal;
@ -1494,14 +1490,6 @@ bool AP_GPS::all_consistent(float &distance) const
return (distance < 50); return (distance < 50);
} }
#if defined(GPS_BLENDED_INSTANCE)
// pre-arm check of GPS blending. True means healthy or that blending is not being used
bool AP_GPS::blend_health_check() const
{
return (_blend_health_counter < 50);
}
#endif
/* /*
re-assemble fragmented RTCM data re-assemble fragmented RTCM data
*/ */
@ -1764,373 +1752,6 @@ uint16_t AP_GPS::get_rate_ms(uint8_t instance) const
return MIN(params[instance].rate_ms, GPS_MAX_RATE_MS); return MIN(params[instance].rate_ms, GPS_MAX_RATE_MS);
} }
#if defined(GPS_BLENDED_INSTANCE)
/*
calculate the weightings used to blend GPSs location and velocity data
*/
bool AP_GPS::calc_blend_weights(void)
{
// zero the blend weights
memset(&_blend_weights, 0, sizeof(_blend_weights));
static_assert(GPS_MAX_RECEIVERS == 2, "GPS blending only currently works with 2 receivers");
// Note that the early quit below relies upon exactly 2 instances
// The time delta calculations below also rely upon every instance being currently detected and being parsed
// exit immediately if not enough receivers to do blending
if (state[0].status <= NO_FIX || state[1].status <= NO_FIX) {
return false;
}
// Use the oldest non-zero time, but if time difference is excessive, use newest to prevent a disconnected receiver from blocking updates
uint32_t max_ms = 0; // newest non-zero system time of arrival of a GPS message
uint32_t min_ms = -1; // oldest non-zero system time of arrival of a GPS message
uint32_t max_rate_ms = 0; // largest update interval of a GPS receiver
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
// Find largest and smallest times
if (state[i].last_gps_time_ms > max_ms) {
max_ms = state[i].last_gps_time_ms;
}
if ((state[i].last_gps_time_ms < min_ms) && (state[i].last_gps_time_ms > 0)) {
min_ms = state[i].last_gps_time_ms;
}
max_rate_ms = MAX(get_rate_ms(i), max_rate_ms);
if (isinf(state[i].speed_accuracy) ||
isinf(state[i].horizontal_accuracy) ||
isinf(state[i].vertical_accuracy)) {
return false;
}
}
if ((max_ms - min_ms) < (2 * max_rate_ms)) {
// data is not too delayed so use the oldest time_stamp to give a chance for data from that receiver to be updated
state[GPS_BLENDED_INSTANCE].last_gps_time_ms = min_ms;
} else {
// receiver data has timed out so fail out of blending
return false;
}
// calculate the sum squared speed accuracy across all GPS sensors
float speed_accuracy_sum_sq = 0.0f;
if (_blend_mask & BLEND_MASK_USE_SPD_ACC) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_3D) {
if (state[i].have_speed_accuracy && state[i].speed_accuracy > 0.0f) {
speed_accuracy_sum_sq += sq(state[i].speed_accuracy);
} else {
// not all receivers support this metric so set it to zero and don't use it
speed_accuracy_sum_sq = 0.0f;
break;
}
}
}
}
// calculate the sum squared horizontal position accuracy across all GPS sensors
float horizontal_accuracy_sum_sq = 0.0f;
if (_blend_mask & BLEND_MASK_USE_HPOS_ACC) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_2D) {
if (state[i].have_horizontal_accuracy && state[i].horizontal_accuracy > 0.0f) {
horizontal_accuracy_sum_sq += sq(state[i].horizontal_accuracy);
} else {
// not all receivers support this metric so set it to zero and don't use it
horizontal_accuracy_sum_sq = 0.0f;
break;
}
}
}
}
// calculate the sum squared vertical position accuracy across all GPS sensors
float vertical_accuracy_sum_sq = 0.0f;
if (_blend_mask & BLEND_MASK_USE_VPOS_ACC) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_3D) {
if (state[i].have_vertical_accuracy && state[i].vertical_accuracy > 0.0f) {
vertical_accuracy_sum_sq += sq(state[i].vertical_accuracy);
} else {
// not all receivers support this metric so set it to zero and don't use it
vertical_accuracy_sum_sq = 0.0f;
break;
}
}
}
}
// Check if we can do blending using reported accuracy
bool can_do_blending = (horizontal_accuracy_sum_sq > 0.0f || vertical_accuracy_sum_sq > 0.0f || speed_accuracy_sum_sq > 0.0f);
// if we can't do blending using reported accuracy, return false and hard switch logic will be used instead
if (!can_do_blending) {
return false;
}
float sum_of_all_weights = 0.0f;
// calculate a weighting using the reported horizontal position
float hpos_blend_weights[GPS_MAX_RECEIVERS] = {};
if (horizontal_accuracy_sum_sq > 0.0f) {
// calculate the weights using the inverse of the variances
float sum_of_hpos_weights = 0.0f;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_2D && state[i].horizontal_accuracy >= 0.001f) {
hpos_blend_weights[i] = horizontal_accuracy_sum_sq / sq(state[i].horizontal_accuracy);
sum_of_hpos_weights += hpos_blend_weights[i];
}
}
// normalise the weights
if (sum_of_hpos_weights > 0.0f) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
hpos_blend_weights[i] = hpos_blend_weights[i] / sum_of_hpos_weights;
}
sum_of_all_weights += 1.0f;
}
}
// calculate a weighting using the reported vertical position accuracy
float vpos_blend_weights[GPS_MAX_RECEIVERS] = {};
if (vertical_accuracy_sum_sq > 0.0f) {
// calculate the weights using the inverse of the variances
float sum_of_vpos_weights = 0.0f;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_3D && state[i].vertical_accuracy >= 0.001f) {
vpos_blend_weights[i] = vertical_accuracy_sum_sq / sq(state[i].vertical_accuracy);
sum_of_vpos_weights += vpos_blend_weights[i];
}
}
// normalise the weights
if (sum_of_vpos_weights > 0.0f) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
vpos_blend_weights[i] = vpos_blend_weights[i] / sum_of_vpos_weights;
}
sum_of_all_weights += 1.0f;
};
}
// calculate a weighting using the reported speed accuracy
float spd_blend_weights[GPS_MAX_RECEIVERS] = {};
if (speed_accuracy_sum_sq > 0.0f) {
// calculate the weights using the inverse of the variances
float sum_of_spd_weights = 0.0f;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_3D && state[i].speed_accuracy >= 0.001f) {
spd_blend_weights[i] = speed_accuracy_sum_sq / sq(state[i].speed_accuracy);
sum_of_spd_weights += spd_blend_weights[i];
}
}
// normalise the weights
if (sum_of_spd_weights > 0.0f) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
spd_blend_weights[i] = spd_blend_weights[i] / sum_of_spd_weights;
}
sum_of_all_weights += 1.0f;
}
}
if (!is_positive(sum_of_all_weights)) {
return false;
}
// calculate an overall weight
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
_blend_weights[i] = (hpos_blend_weights[i] + vpos_blend_weights[i] + spd_blend_weights[i]) / sum_of_all_weights;
}
return true;
}
/*
calculate a blended GPS state
*/
void AP_GPS::calc_blended_state(void)
{
// initialise the blended states so we can accumulate the results using the weightings for each GPS receiver
state[GPS_BLENDED_INSTANCE].instance = GPS_BLENDED_INSTANCE;
state[GPS_BLENDED_INSTANCE].status = NO_FIX;
state[GPS_BLENDED_INSTANCE].time_week_ms = 0;
state[GPS_BLENDED_INSTANCE].time_week = 0;
state[GPS_BLENDED_INSTANCE].ground_speed = 0.0f;
state[GPS_BLENDED_INSTANCE].ground_course = 0.0f;
state[GPS_BLENDED_INSTANCE].hdop = GPS_UNKNOWN_DOP;
state[GPS_BLENDED_INSTANCE].vdop = GPS_UNKNOWN_DOP;
state[GPS_BLENDED_INSTANCE].num_sats = 0;
state[GPS_BLENDED_INSTANCE].velocity.zero();
state[GPS_BLENDED_INSTANCE].speed_accuracy = 1e6f;
state[GPS_BLENDED_INSTANCE].horizontal_accuracy = 1e6f;
state[GPS_BLENDED_INSTANCE].vertical_accuracy = 1e6f;
state[GPS_BLENDED_INSTANCE].have_vertical_velocity = false;
state[GPS_BLENDED_INSTANCE].have_speed_accuracy = false;
state[GPS_BLENDED_INSTANCE].have_horizontal_accuracy = false;
state[GPS_BLENDED_INSTANCE].have_vertical_accuracy = false;
state[GPS_BLENDED_INSTANCE].location = {};
_blended_antenna_offset.zero();
_blended_lag_sec = 0;
#if HAL_LOGGING_ENABLED
const uint32_t last_blended_message_time_ms = timing[GPS_BLENDED_INSTANCE].last_message_time_ms;
#endif
timing[GPS_BLENDED_INSTANCE].last_fix_time_ms = 0;
timing[GPS_BLENDED_INSTANCE].last_message_time_ms = 0;
if (state[0].have_undulation) {
state[GPS_BLENDED_INSTANCE].have_undulation = true;
state[GPS_BLENDED_INSTANCE].undulation = state[0].undulation;
} else if (state[1].have_undulation) {
state[GPS_BLENDED_INSTANCE].have_undulation = true;
state[GPS_BLENDED_INSTANCE].undulation = state[1].undulation;
} else {
state[GPS_BLENDED_INSTANCE].have_undulation = false;
}
// combine the states into a blended solution
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
// use the highest status
if (state[i].status > state[GPS_BLENDED_INSTANCE].status) {
state[GPS_BLENDED_INSTANCE].status = state[i].status;
}
// calculate a blended average velocity
state[GPS_BLENDED_INSTANCE].velocity += state[i].velocity * _blend_weights[i];
// report the best valid accuracies and DOP metrics
if (state[i].have_horizontal_accuracy && state[i].horizontal_accuracy > 0.0f && state[i].horizontal_accuracy < state[GPS_BLENDED_INSTANCE].horizontal_accuracy) {
state[GPS_BLENDED_INSTANCE].have_horizontal_accuracy = true;
state[GPS_BLENDED_INSTANCE].horizontal_accuracy = state[i].horizontal_accuracy;
}
if (state[i].have_vertical_accuracy && state[i].vertical_accuracy > 0.0f && state[i].vertical_accuracy < state[GPS_BLENDED_INSTANCE].vertical_accuracy) {
state[GPS_BLENDED_INSTANCE].have_vertical_accuracy = true;
state[GPS_BLENDED_INSTANCE].vertical_accuracy = state[i].vertical_accuracy;
}
if (state[i].have_vertical_velocity) {
state[GPS_BLENDED_INSTANCE].have_vertical_velocity = true;
}
if (state[i].have_speed_accuracy && state[i].speed_accuracy > 0.0f && state[i].speed_accuracy < state[GPS_BLENDED_INSTANCE].speed_accuracy) {
state[GPS_BLENDED_INSTANCE].have_speed_accuracy = true;
state[GPS_BLENDED_INSTANCE].speed_accuracy = state[i].speed_accuracy;
}
if (state[i].hdop > 0 && state[i].hdop < state[GPS_BLENDED_INSTANCE].hdop) {
state[GPS_BLENDED_INSTANCE].hdop = state[i].hdop;
}
if (state[i].vdop > 0 && state[i].vdop < state[GPS_BLENDED_INSTANCE].vdop) {
state[GPS_BLENDED_INSTANCE].vdop = state[i].vdop;
}
if (state[i].num_sats > 0 && state[i].num_sats > state[GPS_BLENDED_INSTANCE].num_sats) {
state[GPS_BLENDED_INSTANCE].num_sats = state[i].num_sats;
}
// report a blended average GPS antenna position
Vector3f temp_antenna_offset = params[i].antenna_offset;
temp_antenna_offset *= _blend_weights[i];
_blended_antenna_offset += temp_antenna_offset;
// blend the timing data
if (timing[i].last_fix_time_ms > timing[GPS_BLENDED_INSTANCE].last_fix_time_ms) {
timing[GPS_BLENDED_INSTANCE].last_fix_time_ms = timing[i].last_fix_time_ms;
}
if (timing[i].last_message_time_ms > timing[GPS_BLENDED_INSTANCE].last_message_time_ms) {
timing[GPS_BLENDED_INSTANCE].last_message_time_ms = timing[i].last_message_time_ms;
}
}
/*
* Calculate an instantaneous weighted/blended average location from the available GPS instances and store in the _output_state.
* This will be statistically the most likely location, but will be not stable enough for direct use by the autopilot.
*/
// Use the GPS with the highest weighting as the reference position
float best_weight = 0.0f;
uint8_t best_index = 0;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (_blend_weights[i] > best_weight) {
best_weight = _blend_weights[i];
best_index = i;
state[GPS_BLENDED_INSTANCE].location = state[i].location;
}
}
// Calculate the weighted sum of horizontal and vertical position offsets relative to the reference position
Vector2f blended_NE_offset_m;
float blended_alt_offset_cm = 0.0f;
blended_NE_offset_m.zero();
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (_blend_weights[i] > 0.0f && i != best_index) {
blended_NE_offset_m += state[GPS_BLENDED_INSTANCE].location.get_distance_NE(state[i].location) * _blend_weights[i];
blended_alt_offset_cm += (float)(state[i].location.alt - state[GPS_BLENDED_INSTANCE].location.alt) * _blend_weights[i];
}
}
// Add the sum of weighted offsets to the reference location to obtain the blended location
state[GPS_BLENDED_INSTANCE].location.offset(blended_NE_offset_m.x, blended_NE_offset_m.y);
state[GPS_BLENDED_INSTANCE].location.alt += (int)blended_alt_offset_cm;
// Calculate ground speed and course from blended velocity vector
state[GPS_BLENDED_INSTANCE].ground_speed = state[GPS_BLENDED_INSTANCE].velocity.xy().length();
state[GPS_BLENDED_INSTANCE].ground_course = wrap_360(degrees(atan2f(state[GPS_BLENDED_INSTANCE].velocity.y, state[GPS_BLENDED_INSTANCE].velocity.x)));
// If the GPS week is the same then use a blended time_week_ms
// If week is different, then use time stamp from GPS with largest weighting
// detect inconsistent week data
uint8_t last_week_instance = 0;
bool weeks_consistent = true;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (last_week_instance == 0 && _blend_weights[i] > 0) {
// this is our first valid sensor week data
last_week_instance = state[i].time_week;
} else if (last_week_instance != 0 && _blend_weights[i] > 0 && last_week_instance != state[i].time_week) {
// there is valid sensor week data that is inconsistent
weeks_consistent = false;
}
}
// calculate output
if (!weeks_consistent) {
// use data from highest weighted sensor
state[GPS_BLENDED_INSTANCE].time_week = state[best_index].time_week;
state[GPS_BLENDED_INSTANCE].time_week_ms = state[best_index].time_week_ms;
} else {
// use week number from highest weighting GPS (they should all have the same week number)
state[GPS_BLENDED_INSTANCE].time_week = state[best_index].time_week;
// calculate a blended value for the number of ms lapsed in the week
double temp_time_0 = 0.0;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (_blend_weights[i] > 0.0f) {
temp_time_0 += (double)state[i].time_week_ms * (double)_blend_weights[i];
}
}
state[GPS_BLENDED_INSTANCE].time_week_ms = (uint32_t)temp_time_0;
}
// calculate a blended value for the timing data and lag
double temp_time_1 = 0.0;
double temp_time_2 = 0.0;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (_blend_weights[i] > 0.0f) {
temp_time_1 += (double)timing[i].last_fix_time_ms * (double) _blend_weights[i];
temp_time_2 += (double)timing[i].last_message_time_ms * (double)_blend_weights[i];
float gps_lag_sec = 0;
get_lag(i, gps_lag_sec);
_blended_lag_sec += gps_lag_sec * _blend_weights[i];
}
}
timing[GPS_BLENDED_INSTANCE].last_fix_time_ms = (uint32_t)temp_time_1;
timing[GPS_BLENDED_INSTANCE].last_message_time_ms = (uint32_t)temp_time_2;
#if HAL_LOGGING_ENABLED
if (timing[GPS_BLENDED_INSTANCE].last_message_time_ms > last_blended_message_time_ms &&
should_log()) {
Write_GPS(GPS_BLENDED_INSTANCE);
}
#endif
}
#endif // GPS_BLENDED_INSTANCE
bool AP_GPS::is_healthy(uint8_t instance) const bool AP_GPS::is_healthy(uint8_t instance) const
{ {
if (instance >= GPS_MAX_INSTANCES) { if (instance >= GPS_MAX_INSTANCES) {

380
libraries/AP_GPS/AP_GPS_Blended.cpp Normal file
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@ -0,0 +1,380 @@
#include "AP_GPS.h"
#if defined(GPS_BLENDED_INSTANCE)
// defines used to specify the mask position for use of different accuracy metrics in the blending algorithm
#define BLEND_MASK_USE_HPOS_ACC 1
#define BLEND_MASK_USE_VPOS_ACC 2
#define BLEND_MASK_USE_SPD_ACC 4
// pre-arm check of GPS blending. True means healthy or that blending is not being used
bool AP_GPS::blend_health_check() const
{
return (_blend_health_counter < 50);
}
/*
calculate the weightings used to blend GPSs location and velocity data
*/
bool AP_GPS::calc_blend_weights(void)
{
// zero the blend weights
memset(&_blend_weights, 0, sizeof(_blend_weights));
static_assert(GPS_MAX_RECEIVERS == 2, "GPS blending only currently works with 2 receivers");
// Note that the early quit below relies upon exactly 2 instances
// The time delta calculations below also rely upon every instance being currently detected and being parsed
// exit immediately if not enough receivers to do blending
if (state[0].status <= NO_FIX || state[1].status <= NO_FIX) {
return false;
}
// Use the oldest non-zero time, but if time difference is excessive, use newest to prevent a disconnected receiver from blocking updates
uint32_t max_ms = 0; // newest non-zero system time of arrival of a GPS message
uint32_t min_ms = -1; // oldest non-zero system time of arrival of a GPS message
uint32_t max_rate_ms = 0; // largest update interval of a GPS receiver
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
// Find largest and smallest times
if (state[i].last_gps_time_ms > max_ms) {
max_ms = state[i].last_gps_time_ms;
}
if ((state[i].last_gps_time_ms < min_ms) && (state[i].last_gps_time_ms > 0)) {
min_ms = state[i].last_gps_time_ms;
}
max_rate_ms = MAX(get_rate_ms(i), max_rate_ms);
if (isinf(state[i].speed_accuracy) ||
isinf(state[i].horizontal_accuracy) ||
isinf(state[i].vertical_accuracy)) {
return false;
}
}
if ((max_ms - min_ms) < (2 * max_rate_ms)) {
// data is not too delayed so use the oldest time_stamp to give a chance for data from that receiver to be updated
state[GPS_BLENDED_INSTANCE].last_gps_time_ms = min_ms;
} else {
// receiver data has timed out so fail out of blending
return false;
}
// calculate the sum squared speed accuracy across all GPS sensors
float speed_accuracy_sum_sq = 0.0f;
if (_blend_mask & BLEND_MASK_USE_SPD_ACC) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_3D) {
if (state[i].have_speed_accuracy && state[i].speed_accuracy > 0.0f) {
speed_accuracy_sum_sq += sq(state[i].speed_accuracy);
} else {
// not all receivers support this metric so set it to zero and don't use it
speed_accuracy_sum_sq = 0.0f;
break;
}
}
}
}
// calculate the sum squared horizontal position accuracy across all GPS sensors
float horizontal_accuracy_sum_sq = 0.0f;
if (_blend_mask & BLEND_MASK_USE_HPOS_ACC) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_2D) {
if (state[i].have_horizontal_accuracy && state[i].horizontal_accuracy > 0.0f) {
horizontal_accuracy_sum_sq += sq(state[i].horizontal_accuracy);
} else {
// not all receivers support this metric so set it to zero and don't use it
horizontal_accuracy_sum_sq = 0.0f;
break;
}
}
}
}
// calculate the sum squared vertical position accuracy across all GPS sensors
float vertical_accuracy_sum_sq = 0.0f;
if (_blend_mask & BLEND_MASK_USE_VPOS_ACC) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_3D) {
if (state[i].have_vertical_accuracy && state[i].vertical_accuracy > 0.0f) {
vertical_accuracy_sum_sq += sq(state[i].vertical_accuracy);
} else {
// not all receivers support this metric so set it to zero and don't use it
vertical_accuracy_sum_sq = 0.0f;
break;
}
}
}
}
// Check if we can do blending using reported accuracy
bool can_do_blending = (horizontal_accuracy_sum_sq > 0.0f || vertical_accuracy_sum_sq > 0.0f || speed_accuracy_sum_sq > 0.0f);
// if we can't do blending using reported accuracy, return false and hard switch logic will be used instead
if (!can_do_blending) {
return false;
}
float sum_of_all_weights = 0.0f;
// calculate a weighting using the reported horizontal position
float hpos_blend_weights[GPS_MAX_RECEIVERS] = {};
if (horizontal_accuracy_sum_sq > 0.0f) {
// calculate the weights using the inverse of the variances
float sum_of_hpos_weights = 0.0f;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_2D && state[i].horizontal_accuracy >= 0.001f) {
hpos_blend_weights[i] = horizontal_accuracy_sum_sq / sq(state[i].horizontal_accuracy);
sum_of_hpos_weights += hpos_blend_weights[i];
}
}
// normalise the weights
if (sum_of_hpos_weights > 0.0f) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
hpos_blend_weights[i] = hpos_blend_weights[i] / sum_of_hpos_weights;
}
sum_of_all_weights += 1.0f;
}
}
// calculate a weighting using the reported vertical position accuracy
float vpos_blend_weights[GPS_MAX_RECEIVERS] = {};
if (vertical_accuracy_sum_sq > 0.0f) {
// calculate the weights using the inverse of the variances
float sum_of_vpos_weights = 0.0f;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_3D && state[i].vertical_accuracy >= 0.001f) {
vpos_blend_weights[i] = vertical_accuracy_sum_sq / sq(state[i].vertical_accuracy);
sum_of_vpos_weights += vpos_blend_weights[i];
}
}
// normalise the weights
if (sum_of_vpos_weights > 0.0f) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
vpos_blend_weights[i] = vpos_blend_weights[i] / sum_of_vpos_weights;
}
sum_of_all_weights += 1.0f;
};
}
// calculate a weighting using the reported speed accuracy
float spd_blend_weights[GPS_MAX_RECEIVERS] = {};
if (speed_accuracy_sum_sq > 0.0f) {
// calculate the weights using the inverse of the variances
float sum_of_spd_weights = 0.0f;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (state[i].status >= GPS_OK_FIX_3D && state[i].speed_accuracy >= 0.001f) {
spd_blend_weights[i] = speed_accuracy_sum_sq / sq(state[i].speed_accuracy);
sum_of_spd_weights += spd_blend_weights[i];
}
}
// normalise the weights
if (sum_of_spd_weights > 0.0f) {
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
spd_blend_weights[i] = spd_blend_weights[i] / sum_of_spd_weights;
}
sum_of_all_weights += 1.0f;
}
}
if (!is_positive(sum_of_all_weights)) {
return false;
}
// calculate an overall weight
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
_blend_weights[i] = (hpos_blend_weights[i] + vpos_blend_weights[i] + spd_blend_weights[i]) / sum_of_all_weights;
}
return true;
}
/*
calculate a blended GPS state
*/
void AP_GPS::calc_blended_state(void)
{
// initialise the blended states so we can accumulate the results using the weightings for each GPS receiver
state[GPS_BLENDED_INSTANCE].instance = GPS_BLENDED_INSTANCE;
state[GPS_BLENDED_INSTANCE].status = NO_FIX;
state[GPS_BLENDED_INSTANCE].time_week_ms = 0;
state[GPS_BLENDED_INSTANCE].time_week = 0;
state[GPS_BLENDED_INSTANCE].ground_speed = 0.0f;
state[GPS_BLENDED_INSTANCE].ground_course = 0.0f;
state[GPS_BLENDED_INSTANCE].hdop = GPS_UNKNOWN_DOP;
state[GPS_BLENDED_INSTANCE].vdop = GPS_UNKNOWN_DOP;
state[GPS_BLENDED_INSTANCE].num_sats = 0;
state[GPS_BLENDED_INSTANCE].velocity.zero();
state[GPS_BLENDED_INSTANCE].speed_accuracy = 1e6f;
state[GPS_BLENDED_INSTANCE].horizontal_accuracy = 1e6f;
state[GPS_BLENDED_INSTANCE].vertical_accuracy = 1e6f;
state[GPS_BLENDED_INSTANCE].have_vertical_velocity = false;
state[GPS_BLENDED_INSTANCE].have_speed_accuracy = false;
state[GPS_BLENDED_INSTANCE].have_horizontal_accuracy = false;
state[GPS_BLENDED_INSTANCE].have_vertical_accuracy = false;
state[GPS_BLENDED_INSTANCE].location = {};
_blended_antenna_offset.zero();
_blended_lag_sec = 0;
#if HAL_LOGGING_ENABLED
const uint32_t last_blended_message_time_ms = timing[GPS_BLENDED_INSTANCE].last_message_time_ms;
#endif
timing[GPS_BLENDED_INSTANCE].last_fix_time_ms = 0;
timing[GPS_BLENDED_INSTANCE].last_message_time_ms = 0;
if (state[0].have_undulation) {
state[GPS_BLENDED_INSTANCE].have_undulation = true;
state[GPS_BLENDED_INSTANCE].undulation = state[0].undulation;
} else if (state[1].have_undulation) {
state[GPS_BLENDED_INSTANCE].have_undulation = true;
state[GPS_BLENDED_INSTANCE].undulation = state[1].undulation;
} else {
state[GPS_BLENDED_INSTANCE].have_undulation = false;
}
// combine the states into a blended solution
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
// use the highest status
if (state[i].status > state[GPS_BLENDED_INSTANCE].status) {
state[GPS_BLENDED_INSTANCE].status = state[i].status;
}
// calculate a blended average velocity
state[GPS_BLENDED_INSTANCE].velocity += state[i].velocity * _blend_weights[i];
// report the best valid accuracies and DOP metrics
if (state[i].have_horizontal_accuracy && state[i].horizontal_accuracy > 0.0f && state[i].horizontal_accuracy < state[GPS_BLENDED_INSTANCE].horizontal_accuracy) {
state[GPS_BLENDED_INSTANCE].have_horizontal_accuracy = true;
state[GPS_BLENDED_INSTANCE].horizontal_accuracy = state[i].horizontal_accuracy;
}
if (state[i].have_vertical_accuracy && state[i].vertical_accuracy > 0.0f && state[i].vertical_accuracy < state[GPS_BLENDED_INSTANCE].vertical_accuracy) {
state[GPS_BLENDED_INSTANCE].have_vertical_accuracy = true;
state[GPS_BLENDED_INSTANCE].vertical_accuracy = state[i].vertical_accuracy;
}
if (state[i].have_vertical_velocity) {
state[GPS_BLENDED_INSTANCE].have_vertical_velocity = true;
}
if (state[i].have_speed_accuracy && state[i].speed_accuracy > 0.0f && state[i].speed_accuracy < state[GPS_BLENDED_INSTANCE].speed_accuracy) {
state[GPS_BLENDED_INSTANCE].have_speed_accuracy = true;
state[GPS_BLENDED_INSTANCE].speed_accuracy = state[i].speed_accuracy;
}
if (state[i].hdop > 0 && state[i].hdop < state[GPS_BLENDED_INSTANCE].hdop) {
state[GPS_BLENDED_INSTANCE].hdop = state[i].hdop;
}
if (state[i].vdop > 0 && state[i].vdop < state[GPS_BLENDED_INSTANCE].vdop) {
state[GPS_BLENDED_INSTANCE].vdop = state[i].vdop;
}
if (state[i].num_sats > 0 && state[i].num_sats > state[GPS_BLENDED_INSTANCE].num_sats) {
state[GPS_BLENDED_INSTANCE].num_sats = state[i].num_sats;
}
// report a blended average GPS antenna position
Vector3f temp_antenna_offset = params[i].antenna_offset;
temp_antenna_offset *= _blend_weights[i];
_blended_antenna_offset += temp_antenna_offset;
// blend the timing data
if (timing[i].last_fix_time_ms > timing[GPS_BLENDED_INSTANCE].last_fix_time_ms) {
timing[GPS_BLENDED_INSTANCE].last_fix_time_ms = timing[i].last_fix_time_ms;
}
if (timing[i].last_message_time_ms > timing[GPS_BLENDED_INSTANCE].last_message_time_ms) {
timing[GPS_BLENDED_INSTANCE].last_message_time_ms = timing[i].last_message_time_ms;
}
}
/*
* Calculate an instantaneous weighted/blended average location from the available GPS instances and store in the _output_state.
* This will be statistically the most likely location, but will be not stable enough for direct use by the autopilot.
*/
// Use the GPS with the highest weighting as the reference position
float best_weight = 0.0f;
uint8_t best_index = 0;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (_blend_weights[i] > best_weight) {
best_weight = _blend_weights[i];
best_index = i;
state[GPS_BLENDED_INSTANCE].location = state[i].location;
}
}
// Calculate the weighted sum of horizontal and vertical position offsets relative to the reference position
Vector2f blended_NE_offset_m;
float blended_alt_offset_cm = 0.0f;
blended_NE_offset_m.zero();
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (_blend_weights[i] > 0.0f && i != best_index) {
blended_NE_offset_m += state[GPS_BLENDED_INSTANCE].location.get_distance_NE(state[i].location) * _blend_weights[i];
blended_alt_offset_cm += (float)(state[i].location.alt - state[GPS_BLENDED_INSTANCE].location.alt) * _blend_weights[i];
}
}
// Add the sum of weighted offsets to the reference location to obtain the blended location
state[GPS_BLENDED_INSTANCE].location.offset(blended_NE_offset_m.x, blended_NE_offset_m.y);
state[GPS_BLENDED_INSTANCE].location.alt += (int)blended_alt_offset_cm;
// Calculate ground speed and course from blended velocity vector
state[GPS_BLENDED_INSTANCE].ground_speed = state[GPS_BLENDED_INSTANCE].velocity.xy().length();
state[GPS_BLENDED_INSTANCE].ground_course = wrap_360(degrees(atan2f(state[GPS_BLENDED_INSTANCE].velocity.y, state[GPS_BLENDED_INSTANCE].velocity.x)));
// If the GPS week is the same then use a blended time_week_ms
// If week is different, then use time stamp from GPS with largest weighting
// detect inconsistent week data
uint8_t last_week_instance = 0;
bool weeks_consistent = true;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (last_week_instance == 0 && _blend_weights[i] > 0) {
// this is our first valid sensor week data
last_week_instance = state[i].time_week;
} else if (last_week_instance != 0 && _blend_weights[i] > 0 && last_week_instance != state[i].time_week) {
// there is valid sensor week data that is inconsistent
weeks_consistent = false;
}
}
// calculate output
if (!weeks_consistent) {
// use data from highest weighted sensor
state[GPS_BLENDED_INSTANCE].time_week = state[best_index].time_week;
state[GPS_BLENDED_INSTANCE].time_week_ms = state[best_index].time_week_ms;
} else {
// use week number from highest weighting GPS (they should all have the same week number)
state[GPS_BLENDED_INSTANCE].time_week = state[best_index].time_week;
// calculate a blended value for the number of ms lapsed in the week
double temp_time_0 = 0.0;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (_blend_weights[i] > 0.0f) {
temp_time_0 += (double)state[i].time_week_ms * (double)_blend_weights[i];
}
}
state[GPS_BLENDED_INSTANCE].time_week_ms = (uint32_t)temp_time_0;
}
// calculate a blended value for the timing data and lag
double temp_time_1 = 0.0;
double temp_time_2 = 0.0;
for (uint8_t i=0; i<GPS_MAX_RECEIVERS; i++) {
if (_blend_weights[i] > 0.0f) {
temp_time_1 += (double)timing[i].last_fix_time_ms * (double) _blend_weights[i];
temp_time_2 += (double)timing[i].last_message_time_ms * (double)_blend_weights[i];
float gps_lag_sec = 0;
get_lag(i, gps_lag_sec);
_blended_lag_sec += gps_lag_sec * _blend_weights[i];
}
}
timing[GPS_BLENDED_INSTANCE].last_fix_time_ms = (uint32_t)temp_time_1;
timing[GPS_BLENDED_INSTANCE].last_message_time_ms = (uint32_t)temp_time_2;
#if HAL_LOGGING_ENABLED
if (timing[GPS_BLENDED_INSTANCE].last_message_time_ms > last_blended_message_time_ms &&
should_log()) {
Write_GPS(GPS_BLENDED_INSTANCE);
}
#endif
}
#endif // GPS_BLENDED_INSTANCE