Unscented Particle Smoother and Its Application to Transfer Alignment of Airborne Distributed POS

Abstract

This paper deals with the problem of state estimation for the transfer alignment of airborne distributed position and orientation system (distributed POS). For a nonlinear system, especially with large initial attitude errors, the performance of linear estimation methods will degrade. In this paper, a nonlinear smoothing algorithm called the unscented particle smoother (UPS) is proposed and utilized in the off-line transfer alignment of airborne distributed POS. In this algorithm, the measurements are first processed by the forward unscented particle filter (UPF) and then a backward smoother is used to achieve the improved solution. The performance of this algorithm is compared with that of a similar smoother known as the unscented Rauch-Tung-Striebel smoother. The simulation results show that the UPS effectively improves the estimation accuracy and this work offers a new off-line transfer alignment approach of distributed POS for multiantenna synthetic aperture radar and other airborne earth observation tasks.