ARMA.hpp

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// This file is part of INSTINCT, the INS Toolkit for Integrated
// Navigation Concepts and Training by the Institute of Navigation of
// the University of Stuttgart, Germany.
//
// This Source Code Form is subject to the terms of the Mozilla Public
// License, v. 2.0. If a copy of the MPL was not distributed with this
// file, You can obtain one at https://mozilla.org/MPL/2.0/.
 
 
#pragma once
 
#include "internal/Node/Node.hpp"
 
#include "util/Eigen.hpp"
 
#include "NodeData/IMU/ImuObs.hpp"
 
#include <deque>
 
namespace NAV::experimental
{
class ARMA : public Node
{
  public:
    ARMA();
    ~ARMA() override;
    ARMA(const ARMA&) = delete;
    ARMA(ARMA&&) = delete;
    ARMA& operator=(const ARMA&) = delete;
    ARMA& operator=(ARMA&&) = delete;
 
    [[nodiscard]] static std::string typeStatic();
 
    [[nodiscard]] std::string type() const override;
 
    [[nodiscard]] static std::string category();
 
    void guiConfig() override;
 
    [[nodiscard]] json save() const override;
 
    void restore(const json& j) override;
 
  private:
    constexpr static size_t INPUT_PORT_INDEX_IMU_OBS = 0;  
    constexpr static size_t OUTPUT_PORT_INDEX_IMU_OBS = 0; 
 
    bool initialize() override;
 
    void deinitialize() override;
 
    void receiveImuObs(InputPin::NodeDataQueue& queue, size_t pinIdx);
 
    static void acf_function(Eigen::VectorXd& y, int p, Eigen::VectorXd& acf);
 
    static void pacf_function(Eigen::VectorXd& y, Eigen::VectorXd& acf, int p, Eigen::VectorXd& pacf, Eigen::VectorXd& e_hat_initial);
 
    static void hannan_rissanen(Eigen::VectorXd& y, int p, int q, int m, int deque_size, Eigen::VectorXd& x, Eigen::VectorXd& emp_sig, Eigen::VectorXd& y_hat);
 
    static void matrix_function(Eigen::VectorXd& y, Eigen::VectorXd& e_hat, int p, int q, int m, Eigen::MatrixXd& A);
 
    std::deque<std::shared_ptr<const ImuObs>> _buffer;
 
    int _k = 0;
 
    bool INITIALIZE = false; 
    // ARMA order
    int _p = 2; 
    int _q = 2; 
 
    int _deque_size = 1000; 
    int _num_obs = 6;       
 
    Eigen::MatrixXd _y;       
    Eigen::VectorXd _y_rbm;   
    Eigen::VectorXd _y_hat;   
    Eigen::VectorXd _emp_sig; 
    Eigen::VectorXd _x;       
    Eigen::VectorXd _y_hat_t; 
 
    int _p_mem = 0; 
    int _q_mem = 0; 
 
    int _m = 0;         
    double _y_mean = 0; 
};
 
} // namespace NAV::experimental