#include <kalman_filter.h>
|
| KalmanFilter (const T *state_transition_data, const T *observation_data, const T *process_covariance_data, const T *default_measurement_covariance_data) |
|
| KalmanFilter (const Eigen::Matrix< T, N, N > &state_transition_matrix, const Eigen::Matrix< T, K, N > &observation_matrix, const Eigen::Matrix< T, N, N > &process_covariance, const Eigen::Matrix< T, K, K > &default_measurement_covariance) |
|
void | Step (State *state) const |
|
void | Update (const Eigen::Matrix< T, K, 1 > &measurement_mean, const Eigen::Matrix< T, K, K > &measurement_covariance, State *state) const |
|
void | Update (State *state, const Eigen::Matrix< T, K, 1 > &measurement_mean) const |
|
template<typename T, int N, int K>
class mv::KalmanFilter< T, N, K >
Definition at line 30 of file kalman_filter.h.
◆ KalmanFilter() [1/2]
template<typename T , int N, int K>
mv::KalmanFilter< T, N, K >::KalmanFilter |
( |
const T * |
state_transition_data, |
|
|
const T * |
observation_data, |
|
|
const T * |
process_covariance_data, |
|
|
const T * |
default_measurement_covariance_data |
|
) |
| |
|
inline |
◆ KalmanFilter() [2/2]
template<typename T , int N, int K>
mv::KalmanFilter< T, N, K >::KalmanFilter |
( |
const Eigen::Matrix< T, N, N > & |
state_transition_matrix, |
|
|
const Eigen::Matrix< T, K, N > & |
observation_matrix, |
|
|
const Eigen::Matrix< T, N, N > & |
process_covariance, |
|
|
const Eigen::Matrix< T, K, K > & |
default_measurement_covariance |
|
) |
| |
|
inline |
◆ Step()
template<typename T , int N, int K>
◆ Update() [1/2]
template<typename T , int N, int K>
void mv::KalmanFilter< T, N, K >::Update |
( |
const Eigen::Matrix< T, K, 1 > & |
measurement_mean, |
|
|
const Eigen::Matrix< T, K, K > & |
measurement_covariance, |
|
|
State * |
state |
|
) |
| const |
|
inline |
◆ Update() [2/2]
template<typename T , int N, int K>
The documentation for this class was generated from the following file: