kalman-cpp
Implementation of Kalman Filter in C++
|
Header file for the Unscented Kalman filter (UKF). More...
#include <math.h>
#include <assert.h>
#include <armadillo>
Go to the source code of this file.
Classes | |
class | UKF |
Implemetation of the Unscented Kalman filter. This class needs to be derived. More... | |
Macros | |
#define | _USE_MATH_DEFINES |
Header file for the Unscented Kalman filter (UKF).
The implementation is based on the paper: Wan, E. A., & Van Der Merwe, R. (2006). The unscented Kalman filter for nonlinear estimation. Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373), 31(2), 153–158. https://doi.org/10.1109/ASSPCC.2000.882463
Define a non-linear discrete-time process:
\[x_k = f(x_{k-1}, u_{k-1}) + v_{k-1}\]
\[z_k = h(x_k) + w_k\]
where:
\(f\) is the dynamic model of the system
\(h\) is the measurement model of the system
\(v\) is the process noise (Gaussian with covariance Q)
\(w\) is the measurement noise (Gaussian with covariance R)
\(x\) is the state vector
\(z\) is the output vector
\(u\) is the input vector
#define _USE_MATH_DEFINES |