A skewed unscented Kalman filter

ABSTRACT

State estimation of nonlinear systems is a challenging task, especially when the Gaussian approximation fails. The unscented Kalman filter was proposed to deal with state estimation of nonlinear systems. We modify the traditional unscented Kalman filter to capture the third-order moment (skewness) of the state vector. Methods are also proposed to reduce the computation time of the suggested approach, and showing that the proposed algorithm is as fast as the unscented Kalman filter. Simulation results confirm that the method is better than, or at least as good as, the unscented Kalman filter.

KEYWORDS:

• State estimation
• unscented Kalman filter
• skewness
• nonlinear systems
• closed skew normal distribution

Disclosure statement

No potential conflict of interest was reported by the authors.