In INS/GPS integration, the data fusion algorithm involves properly handling of nonlinear models. Therefore the nonlinear filtering methods have been commonly applied in the INS/GPS integration to estimate the state vector. The most popular and commonly used method is the Extended Kalman Filter (EKF) which approximates the nonlinear state and measurement equations using the first order Taylor s...

Conventional particle filtering-based visual ego-motion estimation often suffers from large local linearization errors in the case of abrupt camera motion. The main contribution of this paper is to present a novel particle filteringbased visual ego-motion estimation algorithm that is especially robust to the abrupt camera motion. The robustness to the abrupt camera motion is achieved by multi-l...

A new algorithm called maximum correntropy unscented Kalman filter (MCUKF) is proposed and applied to relative state estimation in space communication networks. As is well known, the unscented Kalman filter (UKF) provides an efficient tool to solve the non-linear state estimate problem. However, the UKF usually plays well in Gaussian noises. Its performance may deteriorate substantially in the ...