nonlinearmeasurementpdf.cpp

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// $Id: nonlinearanalyticconditionalgaussianmobile.cpp 5823 2005-10-27 13:43:02Z TDeLaet $
// Copyright (C) 2006  Tinne De Laet <first dot last at mech dot kuleuven dot be>
//
// This program is free software; you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as published by
// the Free Software Foundation; either version 2.1 of the License, or
// (at your option) any later version.
//
// This program 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 Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//

#include "bayesian_filtering/nonlinearmeasurementpdf.h"
#include <wrappers/rng/rng.h> // Wrapper around several rng libraries

#define MEASMODEL_NUMCONDARGUMENTS_MOBILE 1
#define MEASMODEL_DIMENSION_MOBILE        3

namespace BFL
{
  using namespace MatrixWrapper;

  NonlinearMeasurementPdf::NonlinearMeasurementPdf(const Gaussian& measNoise)
    : ConditionalPdf<ColumnVector,ColumnVector>(MEASMODEL_DIMENSION_MOBILE,MEASMODEL_NUMCONDARGUMENTS_MOBILE)
  {
    _measNoise = measNoise;
  }


  NonlinearMeasurementPdf::~NonlinearMeasurementPdf(){}

  Probability
  NonlinearMeasurementPdf::ProbabilityGet(const ColumnVector& measurement) const
  {
    ColumnVector state = ConditionalArgumentGet(0);

    ColumnVector expected_measurement(1);
    expected_measurement(1) = 2 * state(2);

    return _measNoise.ProbabilityGet(expected_measurement-measurement);
  }

}//namespace BFL