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/*
* SimpleKalmanFilter - a Kalman Filter implementation for single variable models.
* Created by Denys Sene, January, 1, 2017.
* Released under MIT License - see LICENSE file for details.
*/
#include "SimpleKalmanFilter.h"
#include <math.h>
SimpleKalmanFilter::SimpleKalmanFilter(float mea_e, float est_e, float q)
{
_err_measure=mea_e;
_err_estimate=est_e;
_q = q;
}
float SimpleKalmanFilter::updateEstimate(float mea)
{
_kalman_gain = _err_estimate/(_err_estimate + _err_measure);
_current_estimate = _last_estimate + _kalman_gain * (mea - _last_estimate);
_err_estimate = (1.0f - _kalman_gain)*_err_estimate + fabsf(_last_estimate-_current_estimate)*_q;
_last_estimate=_current_estimate;
return _current_estimate;
}
void SimpleKalmanFilter::setMeasurementError(float mea_e)
{
_err_measure=mea_e;
}
void SimpleKalmanFilter::setEstimateError(float est_e)
{
_err_estimate=est_e;
}
void SimpleKalmanFilter::setProcessNoise(float q)
{
_q=q;
}
float SimpleKalmanFilter::getKalmanGain() {
return _kalman_gain;
}
float SimpleKalmanFilter::getEstimateError() {
return _err_estimate;
}
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