nonlinear_tracking.h

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/*!
 * \file nonlinear_tracking.h
 * \brief Interface of a library for nonlinear tracking algorithms
 *
 * CubatureFilter implements the functionality of the Cubature Kalman
 * Filter, which uses multidimensional cubature rules to estimate the
 * time evolution of a nonlinear system. UnscentedFilter implements
 * an Unscented Kalman Filter which uses Unscented Transform rules to
 * perform a similar estimation.
 *
 * [1] I Arasaratnam and S Haykin. Cubature kalman filters. IEEE
 * Transactions on Automatic Control, 54(6):1254–1269,2009.
 *
 * \authors <ul>
 *          <li> Gerald LaMountain, 2019. gerald(at)ece.neu.edu
 *          <li> Jordi Vila-Valls 2019. jvila(at)cttc.es
 *          </ul>
 * -----------------------------------------------------------------------------
 *
 * Copyright (C) 2010-2020  (see AUTHORS file for a list of contributors)
 *
 * GNSS-SDR is a software defined Global Navigation
 *          Satellite Systems receiver
 *
 * This file is part of GNSS-SDR.
 *
 * SPDX-License-Identifier: GPL-3.0-or-later
 *
 * -----------------------------------------------------------------------------
 */

#ifndef GNSS_SDR_NONLINEAR_TRACKING_H
#define GNSS_SDR_NONLINEAR_TRACKING_H

#if ARMA_NO_BOUND_CHECKING
#define ARMA_NO_DEBUG 1
#endif

#include <armadillo>
#include <gnuradio/gr_complex.h>

// Abstract model function
class ModelFunction
{
public:
    ModelFunction(){};
    virtual arma::vec operator()(const arma::vec& input) = 0;
    virtual ~ModelFunction() = default;
};

class CubatureFilter
{
public:
    // Constructors and destructors
    CubatureFilter();
    explicit CubatureFilter(int nx);
    CubatureFilter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0);
    ~CubatureFilter() = default;

    // Reinitialization function
    void initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0);

    // Prediction and estimation
    void predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, ModelFunction* transition_fcn, const arma::mat& noise_covariance);
    void update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, ModelFunction* measurement_fcn, const arma::mat& noise_covariance);

    // Getters
    arma::mat get_x_pred() const;
    arma::mat get_P_x_pred() const;
    arma::mat get_x_est() const;
    arma::mat get_P_x_est() const;

private:
    arma::vec x_pred_out;
    arma::mat P_x_pred_out;
    arma::vec x_est;
    arma::mat P_x_est;
};

class UnscentedFilter
{
public:
    // Constructors and destructors
    UnscentedFilter();
    explicit UnscentedFilter(int nx);
    UnscentedFilter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0);
    ~UnscentedFilter() = default;

    // Reinitialization function
    void initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0);

    // Prediction and estimation
    void predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, ModelFunction* transition_fcn, const arma::mat& noise_covariance);
    void update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, ModelFunction* measurement_fcn, const arma::mat& noise_covariance);

    // Getters
    arma::mat get_x_pred() const;
    arma::mat get_P_x_pred() const;
    arma::mat get_x_est() const;
    arma::mat get_P_x_est() const;

private:
    arma::vec x_pred_out;
    arma::mat P_x_pred_out;
    arma::vec x_est;
    arma::mat P_x_est;
};

#endif