An adaptive filtering method based on EMD for X-ray pulsar navigation with uncertain measurement noise

¹ College of Information Science and Engineering, Hunan University, Changsha 410082, China
² College of Information Science and Engineering,Wuhan University of Science and Technology, Wuhan 430081, China

^a Corresponding author: Z. W. Kang <hn_zwkang@126.com>

Abstract

Affected by the unstable pulse radiation and the pulsar directional errors, the statistical characteristics of the pulsar measurement noise may vary with time slowly and cannot be accurately determined, which cause the filtering accuracy of the extended Kalman filter(EKF) in pulsar navigation positioning system decline sharply or even diverge. To solve this problem, an adaptive extended Kalman filtering algorithm based on the empirical mode decomposition(EMD) is proposed. In this method, the high frequency noise is separated from measurement information of pulsar by the method of EMD, and the noise variance can be estimated to update the parameters of EKF. The simulation results demonstrate that compared with conventional EKF, the proposed method can adaptively track the change of the measurement noise, and still keeps high estimation accuracy with unknown measurement noise, the positioning accuracy of the pulsar navigation is improved simultaneously.