Variations of Unscented Kalman filter with their applications in target tracking on re-entry

The most usually used method in nonlinear filtering and tracking community is extended Kalman filter. To make filtering results more accurate while keeping comparable complexity with those of real-time filters, the idea of iteration can be considered in the process of updating. In this paper new iterative methods using unscented transform are presented. An application in target tracking on re-entry shows their performance advantages. In addition, square root UKF is included in the simulation as another variation of UKF to improve statistical performance.