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utility: Add lerp and 1D Kalman filter

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Michael Fabian 'Xaymar' Dirks 2020-03-20 23:10:11 +01:00
parent 6d3c540349
commit ba1780afa6
1 changed files with 41 additions and 0 deletions
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41
source/utility.hpp
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@ -270,6 +270,47 @@ namespace util {
return T(final); return T(final);
} }
template<typename T>
inline T lerp(T a, T b, double_t v)
{
return static_cast<T>((static_cast<double_t>(a) * (1.0 - v)) + (static_cast<double_t>(b) * v));
}
template<typename T>
class kalman1D {
T _q_process_noise_covariance;
T _r_measurement_noise_covariance;
T _x_value_of_interest;
T _p_estimation_error_covariance;
T _k_kalman_gain;
public:
kalman1D()
: _q_process_noise_covariance(0), _r_measurement_noise_covariance(0), _x_value_of_interest(0),
_p_estimation_error_covariance(0), _k_kalman_gain(0.0)
{}
kalman1D(T pnc, T mnc, T eec, T value)
: _q_process_noise_covariance(pnc), _r_measurement_noise_covariance(mnc), _x_value_of_interest(value),
_p_estimation_error_covariance(eec), _k_kalman_gain(0.0)
{}
~kalman1D() {}
T filter(T measurement)
{
_p_estimation_error_covariance += _q_process_noise_covariance;
_k_kalman_gain =
_p_estimation_error_covariance / (_p_estimation_error_covariance + _r_measurement_noise_covariance);
_x_value_of_interest += _k_kalman_gain * (measurement - _x_value_of_interest);
_p_estimation_error_covariance = (1 - _k_kalman_gain) * _p_estimation_error_covariance;
return _x_value_of_interest;
}
T get()
{
return _x_value_of_interest;
}
};
} // namespace math } // namespace math
inline size_t aligned_offset(size_t align, size_t pos) inline size_t aligned_offset(size_t align, size_t pos)