PX4-Autopilot/src/modules/ekf2/EKF/bias_estimator.hpp

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/**
 * @file bias_estimator.hpp
 * @brief Implementation of a single-state bias estimator
 *
 * state: bias
 *
 * The state is noise driven: Transition matrix A = 1
 * x[k+1] = Ax[k] + v with v ~ N(0, Q)
 * y[k] = x[k] + w with w ~ N(0, R)
 *
 * During the measurment update step, the Normalized Innovation Squared (NIS) is checked
 * and the measurement is rejected if larger than the gate size.
 *
 * @author Mathieu Bresciani 	<mathieu@auterion.com>
 */

#pragma once

#include <matrix/math.hpp>
#include <mathlib/mathlib.h>
#include <mathlib/math/filter/AlphaFilter.hpp>

class BiasEstimator
{
public:
	struct status {
		float bias;
		float bias_var;
		float innov;
		float innov_var;
		float innov_test_ratio;
	};

	BiasEstimator(float state_init, float state_var_init): _state{state_init}, _state_var{state_var_init} {};
	virtual ~BiasEstimator() = default;

	void reset()
	{
		_state = 0.f;
		_state_var = 0.f;
		_signed_innov_test_ratio_lpf.reset(0.f);
		_time_since_last_negative_innov = 0.f;
		_time_since_last_positive_innov = 0.f;
	}

	virtual void predict(float dt);
	virtual void fuseBias(float measurement, float measurement_var);

	void setBias(float bias) { _state = bias; }
	void setProcessNoiseSpectralDensity(float nsd)
	{
		_process_psd = nsd * nsd;
	}
	void setBiasStdDev(float state_noise) { _state_var = state_noise * state_noise; }
	void setInnovGate(float gate_size) { _gate_size = gate_size; }

	void setMaxStateNoise(float max_noise) { _state_var_max = math::max(sq(0.01f), max_noise * max_noise); }

	float getBias() const { return _state; }
	float getBiasVar() const { return _state_var; }
	const status &getStatus() const { return _status; }

private:
	float _state{0.f};
	float _dt{0.01f};

	float _gate_size{3.f}; ///< Used for innovation filtering (innovation test ratio)
	float _state_var{0.1f}; ///< Initial state uncertainty variance (m^2)
	float _process_psd{1.25e-6f}; ///< State process power spectral density (m^2/s^2/Hz)
	float _state_var_max{2.f}; ///< Used to constrain the state variance (m^2)

	// Innovation sequence monitoring; used to detect a bias in the state
	AlphaFilter<float> _signed_innov_test_ratio_lpf;
	float _time_since_last_negative_innov{0.f};
	float _time_since_last_positive_innov{0.f};

	status _status;

	void constrainStateVar();
	float computeKalmanGain(float innov_var) const;

	/*
	 * Compute the ratio between the Normalized Innovation Squared (NIS)
	 * and its maximum gate size. Use isTestRatioPassing to know if the
	 * measurement should be fused or not.
	 */
	float computeInnovTestRatio(float innov, float innov_var) const;
	bool isTestRatioPassing(float innov_test_ratio) const;

	void updateState(float K, float innov);
	void updateStateCovariance(float K);

	void updateOffsetDetection(float innov, float innov_test_ratio);
	bool isOffsetDetected() const;

	status packStatus(float innov, float innov_var, float innov_test_ratio) const;

	static constexpr float _innov_sequence_monitnoring_time_constant{10.f}; ///< in seconds
	static constexpr float _process_var_boost_gain{1.0e3f};
};