TooN Algorithm Library - tag
0.2
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#include <kalmanfilter.h>
Public Types | |
typedef State | state_type |
typedef Model | model_type |
Public Member Functions | |
KalmanFilter () | |
void | predict (double dt) |
template<class Measurement > | |
void | filter (Measurement &m) |
Public Attributes | |
TooN::Matrix < State::STATE_DIMENSION > | identity |
identity matrix of the right size, used in the measurement equations More... | |
State | state |
the current state of the filter More... | |
Model | model |
the process model used by the filter More... | |
the basic template class implementing the Kalman Filter, see Kalman Filter documentation for details.
typedef Model tag::KalmanFilter< State, Model >::model_type |
typedef State tag::KalmanFilter< State, Model >::state_type |
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inline |
References tag::KalmanFilter< State, Model >::identity.
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inline |
incorporates a measurement
[in] | m | the measurement to add to the filter state |
References tag::KalmanFilter< State, Model >::model, and tag::KalmanFilter< State, Model >::state.
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inline |
predicts the state by applying the process model over the time interval dt
[in] | dt | time interval |
References tag::KalmanFilter< State, Model >::model, and tag::KalmanFilter< State, Model >::state.
TooN::Matrix<State::STATE_DIMENSION> tag::KalmanFilter< State, Model >::identity |
identity matrix of the right size, used in the measurement equations
Referenced by tag::KalmanFilter< State, Model >::KalmanFilter().
Model tag::KalmanFilter< State, Model >::model |
the process model used by the filter
Referenced by tag::KalmanFilter< State, Model >::filter(), and tag::KalmanFilter< State, Model >::predict().
State tag::KalmanFilter< State, Model >::state |
the current state of the filter
Referenced by tag::KalmanFilter< State, Model >::filter(), and tag::KalmanFilter< State, Model >::predict().