PX4-Autopilot/EKF/estimator_interface.cpp

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/**
 * @file estimator_interface.cpp
 * Definition of base class for attitude estimators
 *
 * @author Roman Bast <bapstroman@gmail.com>
 * @author Paul Riseborough <p_riseborough@live.com.au>
 * @author Siddharth B Purohit <siddharthbharatpurohit@gmail.com>
 */

#include "estimator_interface.h"

#include "../ecl.h"
#include <math.h>
#include "mathlib.h"

// Accumulate imu data and store to buffer at desired rate
void EstimatorInterface::setIMUData(uint64_t time_usec, uint64_t delta_ang_dt, uint64_t delta_vel_dt,
				    float (&delta_ang)[3], float (&delta_vel)[3])
{
	if (!_initialised) {
		init(time_usec);
		_initialised = true;
	}

	float dt = (float)(time_usec - _time_last_imu) / 1000 / 1000;
	dt = math::max(dt, 1.0e-4f);
	dt = math::min(dt, 0.02f);

	_time_last_imu = time_usec;

	if (_time_last_imu > 0) {
		_dt_imu_avg = 0.8f * _dt_imu_avg + 0.2f * dt;
	}

	// copy data
	imuSample imu_sample_new = {};
	imu_sample_new.delta_ang = Vector3f(delta_ang);
	imu_sample_new.delta_vel = Vector3f(delta_vel);

	// convert time from us to secs
	imu_sample_new.delta_ang_dt = delta_ang_dt / 1e6f;
	imu_sample_new.delta_vel_dt = delta_vel_dt / 1e6f;
	imu_sample_new.time_us = time_usec;
	_imu_ticks++;

	// calculate a metric which indicates the amount of coning vibration
	Vector3f temp = cross_product(imu_sample_new.delta_ang, _delta_ang_prev);
	_vibe_metrics[0] = 0.99f * _vibe_metrics[0] + 0.01f * temp.norm();

	// calculate a metric which indiates the amount of high frequency gyro vibration
	temp = imu_sample_new.delta_ang - _delta_ang_prev;
	_delta_ang_prev = imu_sample_new.delta_ang;
	_vibe_metrics[1] = 0.99f * _vibe_metrics[1] + 0.01f * temp.norm();

	// calculate a metric which indicates the amount of high fequency accelerometer vibration
	temp = imu_sample_new.delta_vel - _delta_vel_prev;
	_delta_vel_prev = imu_sample_new.delta_vel;
	_vibe_metrics[2] = 0.99f * _vibe_metrics[2] + 0.01f * temp.norm();

	// accumulate and down-sample imu data and push to the buffer when new downsampled data becomes available
	if (collect_imu(imu_sample_new)) {
		_imu_buffer.push(imu_sample_new);
		_imu_ticks = 0;
		_imu_updated = true;

		// down-sample the drag specific force data by accumulating and calculating the mean when
		// sufficient samples have been collected
		if (_params.fusion_mode & MASK_USE_DRAG) {
			_drag_sample_count ++;
			// note acceleration is accumulated as a delta velocity
			_drag_down_sampled.accelXY(0) += imu_sample_new.delta_vel(0);
			_drag_down_sampled.accelXY(1) += imu_sample_new.delta_vel(1);
			_drag_down_sampled.time_us += imu_sample_new.time_us;
			_drag_sample_time_dt += imu_sample_new.delta_vel_dt;

			// calculate the downsample ratio for drag specific force data
			uint8_t min_sample_ratio = (uint8_t) ceilf((float)_imu_buffer_length / _obs_buffer_length);

			if (min_sample_ratio < 5) {
				min_sample_ratio = 5;

			}

			// calculate and store means from accumulated values
			if (_drag_sample_count >= min_sample_ratio) {
				// note conversion from accumulated delta velocity to acceleration
				_drag_down_sampled.accelXY(0) /= _drag_sample_time_dt;
				_drag_down_sampled.accelXY(1) /= _drag_sample_time_dt;
				_drag_down_sampled.time_us /= _drag_sample_count;

				// write to buffer
				_drag_buffer.push(_drag_down_sampled);

				// reset accumulators
				_drag_sample_count = 0;
				_drag_down_sampled.accelXY.zero();
				_drag_down_sampled.time_us = 0;
				_drag_sample_time_dt = 0.0f;

			}
		}

		// get the oldest data from the buffer
		_imu_sample_delayed = _imu_buffer.get_oldest();

		// calculate the minimum interval between observations required to guarantee no loss of data
		// this will occur if data is overwritten before its time stamp falls behind the fusion time horizon
		_min_obs_interval_us = (_imu_sample_new.time_us - _imu_sample_delayed.time_us) / (_obs_buffer_length - 1);

	} else {
		_imu_updated = false;

	}
}

void EstimatorInterface::setMagData(uint64_t time_usec, float (&data)[3])
{
	// limit data rate to prevent data being lost
	if (time_usec - _time_last_mag > _min_obs_interval_us) {

		magSample mag_sample_new = {};
		mag_sample_new.time_us = time_usec - _params.mag_delay_ms * 1000;

		mag_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
		_time_last_mag = time_usec;

		mag_sample_new.mag = Vector3f(data);

		_mag_buffer.push(mag_sample_new);
	}
}

void EstimatorInterface::setGpsData(uint64_t time_usec, struct gps_message *gps)
{
	if (!_initialised) {
		return;
	}

	// limit data rate to prevent data being lost
	bool need_gps = (_params.fusion_mode & MASK_USE_GPS) || (_params.vdist_sensor_type == VDIST_SENSOR_GPS);

	if (((time_usec - _time_last_gps) > _min_obs_interval_us) && need_gps && gps->fix_type > 2) {
		gpsSample gps_sample_new = {};
		gps_sample_new.time_us = gps->time_usec - _params.gps_delay_ms * 1000;

		gps_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
		_time_last_gps = time_usec;

		gps_sample_new.time_us = math::max(gps_sample_new.time_us, _imu_sample_delayed.time_us);
		gps_sample_new.vel = Vector3f(gps->vel_ned);

		_gps_speed_valid = gps->vel_ned_valid;
		gps_sample_new.sacc = gps->sacc;
		gps_sample_new.hacc = gps->eph;
		gps_sample_new.vacc = gps->epv;

		gps_sample_new.hgt = (float)gps->alt * 1e-3f;

		// Only calculate the relative position if the WGS-84 location of the origin is set
		if (collect_gps(time_usec, gps)) {
			float lpos_x = 0.0f;
			float lpos_y = 0.0f;
			map_projection_project(&_pos_ref, (gps->lat / 1.0e7), (gps->lon / 1.0e7), &lpos_x, &lpos_y);
			gps_sample_new.pos(0) = lpos_x;
			gps_sample_new.pos(1) = lpos_y;

		} else {
			gps_sample_new.pos(0) = 0.0f;
			gps_sample_new.pos(1) = 0.0f;
		}

		_gps_buffer.push(gps_sample_new);
	}
}

void EstimatorInterface::setBaroData(uint64_t time_usec, float data)
{
	if (!_initialised) {
		return;
	}

	// limit data rate to prevent data being lost
	if (time_usec - _time_last_baro > _min_obs_interval_us) {

		baroSample baro_sample_new{};
		baro_sample_new.hgt = data;
		baro_sample_new.time_us = time_usec - _params.baro_delay_ms * 1000;

		baro_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
		_time_last_baro = time_usec;

		baro_sample_new.time_us = math::max(baro_sample_new.time_us, _imu_sample_delayed.time_us);

		_baro_buffer.push(baro_sample_new);
	}
}

void EstimatorInterface::setAirspeedData(uint64_t time_usec, float true_airspeed, float eas2tas)
{
	if (!_initialised) {
		return;
	}

	// limit data rate to prevent data being lost
	if (time_usec - _time_last_airspeed > _min_obs_interval_us) {
		airspeedSample airspeed_sample_new{};
		airspeed_sample_new.true_airspeed = true_airspeed;
		airspeed_sample_new.eas2tas = eas2tas;
		airspeed_sample_new.time_us = time_usec - _params.airspeed_delay_ms * 1000;
		airspeed_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2; //typo PeRRiod
		_time_last_airspeed = time_usec;

		_airspeed_buffer.push(airspeed_sample_new);
	}
}
static float rng;
// set range data
void EstimatorInterface::setRangeData(uint64_t time_usec, float data)
{
	if (!_initialised) {
		return;
	}

	// limit data rate to prevent data being lost
	if (time_usec - _time_last_range > _min_obs_interval_us) {
		rangeSample range_sample_new = {};
		range_sample_new.rng = data;
		rng = data;
		range_sample_new.time_us = time_usec - _params.range_delay_ms * 1000;
		_time_last_range = time_usec;

		_range_buffer.push(range_sample_new);
	}
}

// set optical flow data
void EstimatorInterface::setOpticalFlowData(uint64_t time_usec, flow_message *flow)
{
	if (!_initialised) {
		return;
	}

	// limit data rate to prevent data being lost
	if (time_usec - _time_last_optflow > _min_obs_interval_us) {
		// check if enough integration time and fail if integration time is less than 50%
		// of min arrival interval because too much data is being lost
		float delta_time = 1e-6f * (float)flow->dt;
		bool delta_time_good = (delta_time >= 5e-7f * (float)_min_obs_interval_us);

		// check magnitude is within sensor limits
		float flow_rate_magnitude;
		bool flow_magnitude_good = false;

		if (delta_time_good) {
			flow_rate_magnitude = flow->flowdata.norm() / delta_time;
			flow_magnitude_good = (flow_rate_magnitude <= _params.flow_rate_max);
		}

		// check quality metric
		bool flow_quality_good = (flow->quality >= _params.flow_qual_min);

		if (delta_time_good && flow_magnitude_good && (flow_quality_good || !_control_status.flags.in_air)) {
			flowSample optflow_sample_new;
			// calculate the system time-stamp for the mid point of the integration period
			optflow_sample_new.time_us = time_usec - _params.flow_delay_ms * 1000 - flow->dt / 2;
			// copy the quality metric returned by the PX4Flow sensor
			optflow_sample_new.quality = flow->quality;
			// NOTE: the EKF uses the reverse sign convention to the flow sensor. EKF assumes positive LOS rate is produced by a RH rotation of the image about the sensor axis.
			// copy the optical and gyro measured delta angles
			optflow_sample_new.gyroXYZ = - flow->gyrodata;

			if (flow_quality_good) {
				optflow_sample_new.flowRadXY = - flow->flowdata;

			} else {
				// when on the ground with poor flow quality, assume zero ground relative velocity
				optflow_sample_new.flowRadXY(0) = + flow->gyrodata(0);
				optflow_sample_new.flowRadXY(1) = + flow->gyrodata(1);

			}

			// compensate for body motion to give a LOS rate
			optflow_sample_new.flowRadXYcomp(0) = optflow_sample_new.flowRadXY(0) - optflow_sample_new.gyroXYZ(0);
			optflow_sample_new.flowRadXYcomp(1) = optflow_sample_new.flowRadXY(1) - optflow_sample_new.gyroXYZ(1);
			// convert integration interval to seconds
			optflow_sample_new.dt = 1e-6f * (float)flow->dt;
			_time_last_optflow = time_usec;
			// push to buffer
			_flow_buffer.push(optflow_sample_new);
		}
	}
}

// set attitude and position data derived from an external vision system
void EstimatorInterface::setExtVisionData(uint64_t time_usec, ext_vision_message *evdata)
{
	if (!_initialised) {
		return;
	}

	// limit data rate to prevent data being lost
	if (time_usec - _time_last_ext_vision > _min_obs_interval_us) {
		extVisionSample ev_sample_new;
		// calculate the system time-stamp for the mid point of the integration period
		ev_sample_new.time_us = time_usec - _params.ev_delay_ms * 1000;
		// copy required data
		ev_sample_new.angErr = evdata->angErr;
		ev_sample_new.posErr = evdata->posErr;
		ev_sample_new.quat = evdata->quat;
		ev_sample_new.posNED = evdata->posNED;
		// record time for comparison next measurement
		_time_last_ext_vision = time_usec;
		// push to buffer
		_ext_vision_buffer.push(ev_sample_new);
	}
}

bool EstimatorInterface::initialise_interface(uint64_t timestamp)
{
	// find the maximum time delay required to compensate for
	uint16_t max_time_delay_ms = math::max(_params.mag_delay_ms,
					 math::max(_params.range_delay_ms,
					     math::max(_params.gps_delay_ms,
						 math::max(_params.flow_delay_ms,
						     math::max(_params.ev_delay_ms,
							 math::max(_params.airspeed_delay_ms, _params.baro_delay_ms))))));

	// calculate the IMU buffer length required to accomodate the maximum delay with some allowance for jitter
	_imu_buffer_length = (max_time_delay_ms / FILTER_UPDATE_PERIOD_MS) + 1;

	// set the observaton buffer length to handle the minimum time of arrival between observations in combination
	// with the worst case delay from current time to ekf fusion time
	// allow for worst case 50% extension of the ekf fusion time horizon delay due to timing jitter
	uint16_t ekf_delay_ms = max_time_delay_ms + (int)(ceilf((float)max_time_delay_ms * 0.5f));
	_obs_buffer_length = (ekf_delay_ms / _params.sensor_interval_min_ms) + 1;

	// limit to be no longer than the IMU buffer (we can't process data faster than the EKF prediction rate)
	_obs_buffer_length = math::min(_obs_buffer_length, _imu_buffer_length);

	if (!(_imu_buffer.allocate(_imu_buffer_length) &&
	      _gps_buffer.allocate(_obs_buffer_length) &&
	      _mag_buffer.allocate(_obs_buffer_length) &&
	      _baro_buffer.allocate(_obs_buffer_length) &&
	      _range_buffer.allocate(_obs_buffer_length) &&
	      _airspeed_buffer.allocate(_obs_buffer_length) &&
	      _flow_buffer.allocate(_obs_buffer_length) &&
	      _ext_vision_buffer.allocate(_obs_buffer_length) &&
	      _drag_buffer.allocate(_obs_buffer_length) &&
	      _output_buffer.allocate(_imu_buffer_length) &&
	      _output_vert_buffer.allocate(_imu_buffer_length))) {
		ECL_ERR("EKF buffer allocation failed!");
		unallocate_buffers();
		return false;
	}

	// zero the data in the observation buffers
	for (int index = 0; index < _obs_buffer_length; index++) {
		gpsSample gps_sample_init = {};
		_gps_buffer.push(gps_sample_init);
		magSample mag_sample_init = {};
		_mag_buffer.push(mag_sample_init);
		baroSample baro_sample_init = {};
		_baro_buffer.push(baro_sample_init);
		rangeSample range_sample_init = {};
		_range_buffer.push(range_sample_init);
		airspeedSample airspeed_sample_init = {};
		_airspeed_buffer.push(airspeed_sample_init);
		flowSample flow_sample_init = {};
		_flow_buffer.push(flow_sample_init);
		extVisionSample ext_vision_sample_init = {};
		_ext_vision_buffer.push(ext_vision_sample_init);
		dragSample drag_sample_init = {};
		_drag_buffer.push(drag_sample_init);
	}

	// zero the data in the imu data and output observer state buffers
	for (int index = 0; index < _imu_buffer_length; index++) {
		imuSample imu_sample_init = {};
		_imu_buffer.push(imu_sample_init);
		outputSample output_sample_init = {};
		_output_buffer.push(output_sample_init);
	}

	_dt_imu_avg = 0.0f;

	_imu_sample_delayed.delta_ang.setZero();
	_imu_sample_delayed.delta_vel.setZero();
	_imu_sample_delayed.delta_ang_dt = 0.0f;
	_imu_sample_delayed.delta_vel_dt = 0.0f;
	_imu_sample_delayed.time_us = timestamp;

	_imu_ticks = 0;

	_initialised = false;

	_time_last_imu = 0;
	_time_last_gps = 0;
	_time_last_mag = 0;
	_time_last_baro = 0;
	_time_last_range = 0;
	_time_last_airspeed = 0;
	_time_last_optflow = 0;
	_fault_status.value = 0;
	_time_last_ext_vision = 0;
	return true;
}

void EstimatorInterface::unallocate_buffers()
{
	_imu_buffer.unallocate();
	_gps_buffer.unallocate();
	_mag_buffer.unallocate();
	_baro_buffer.unallocate();
	_range_buffer.unallocate();
	_airspeed_buffer.unallocate();
	_flow_buffer.unallocate();
	_ext_vision_buffer.unallocate();
	_output_buffer.unallocate();
	_output_vert_buffer.unallocate();

}

bool EstimatorInterface::local_position_is_valid()
{
	// return true if the position estimate is valid
	return (((_time_last_imu - _time_last_optflow) < 5e6) && _control_status.flags.opt_flow) ||
	       (((_time_last_imu - _time_last_ext_vision) < 5e6) && _control_status.flags.ev_pos) ||
	       global_position_is_valid();
}