mirror of
https://github.com/gnss-sdr/gnss-sdr
synced 2024-09-30 16:00:51 +00:00
87 lines
2.8 KiB
C
87 lines
2.8 KiB
C
|
/*!
|
||
|
* \file bayesian_estimation.h
|
||
|
* \brief Interface of a library with Bayesian noise statistic estimation
|
||
|
*
|
||
|
* Bayesian_estimator is a Bayesian estimator which attempts to estimate
|
||
|
* the properties of a stochastic process based on a sequence of
|
||
|
* discrete samples of the sequence.
|
||
|
*
|
||
|
* [1] TODO: Refs
|
||
|
*
|
||
|
* \authors <ul>
|
||
|
* <li> Gerald LaMountain, 2018. gerald(at)ece.neu.edu
|
||
|
* <li> Jordi Vila-Valls 2018. jvila(at)cttc.es
|
||
|
* </ul>
|
||
|
* -------------------------------------------------------------------------
|
||
|
*
|
||
|
* Copyright (C) 2010-2018 (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.
|
||
|
*
|
||
|
* GNSS-SDR is free software: you can redistribute it and/or modify
|
||
|
* it under the terms of the GNU General Public License as published by
|
||
|
* the Free Software Foundation, either version 3 of the License, or
|
||
|
* (at your option) any later version.
|
||
|
*
|
||
|
* GNSS-SDR is distributed in the hope that it will be useful,
|
||
|
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||
|
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||
|
* GNU General Public License for more details.
|
||
|
*
|
||
|
* You should have received a copy of the GNU General Public License
|
||
|
* along with GNSS-SDR. If not, see <https://www.gnu.org/licenses/>.
|
||
|
*
|
||
|
* -------------------------------------------------------------------------
|
||
|
*/
|
||
|
|
||
|
#ifndef GNSS_SDR_BAYESIAN_ESTIMATION_H_
|
||
|
#define GNSS_SDR_BAYESIAN_ESTIMATION_H_
|
||
|
|
||
|
#include <gnuradio/gr_complex.h>
|
||
|
#include <armadillo>
|
||
|
|
||
|
/*! \brief Bayesian_estimator is an estimator of noise characteristics (i.e. mean, covariance)
|
||
|
*
|
||
|
* Bayesian_estimator is an estimator which performs estimation of noise characteristics from
|
||
|
* a sequence of identically and independently distributed (IID) samples of a stationary
|
||
|
* stochastic process by way of Bayesian inference using conjugate priors. The posterior
|
||
|
* distribution is assumed to be Gaussian with mean \mathbf{\mu} and covariance \hat{\mathbf{C}},
|
||
|
* which has a conjugate prior given by a normal-inverse-Wishart distribution with paramemters
|
||
|
* \mathbf{\mu}_{0}, \kappa_{0}, \nu_{0}, and \mathbf{\Psi}.
|
||
|
*
|
||
|
* [1] TODO: Ref1
|
||
|
*
|
||
|
*/
|
||
|
|
||
|
class Bayesian_estimator
|
||
|
{
|
||
|
|
||
|
public:
|
||
|
Bayesian_estimator();
|
||
|
Bayesian_estimator(int ny);
|
||
|
Bayesian_estimator(arma::vec mu_prior_0, int kappa_prior_0, int nu_prior_0, arma::mat Psi_prior_0);
|
||
|
~Bayesian_estimator();
|
||
|
|
||
|
void update_sequential(arma::vec data);
|
||
|
void update_sequential(arma::vec data, arma::vec mu_prior_0, int kappa_prior_0, int nu_prior_0, arma::mat Psi_prior_0);
|
||
|
|
||
|
arma::vec get_mu_est();
|
||
|
arma::mat get_Psi_est();
|
||
|
|
||
|
private:
|
||
|
|
||
|
arma::vec mu_est;
|
||
|
arma::mat Psi_est;
|
||
|
|
||
|
arma::vec mu_prior;
|
||
|
int kappa_prior;
|
||
|
int nu_prior;
|
||
|
arma::mat Psi_prior;
|
||
|
|
||
|
};
|
||
|
|
||
|
#endif
|