A Bayesian Classifier for X-Ray Pulsars Recognition. (24th November 2016)

• Record Type: Journal Article
• Authors: Liang, Hao; Zhan, Yafeng; Duan, Chaowei
• Other Names: Williams Paul Academic Editor.
• Is Part Of: International journal of aerospace engineering. Volume 2016(2016)
• Publication Date: 2016-11-24
• Subjects: Aerospace engineering -- Periodicals; 629.105
• DOI: 10.1155/2016/1746925
• Languages: English
• ISSNs: 1687-5966

Abstract

Abstract : Recognition for X-ray pulsars is important for the problem of spacecraft's attitude determination by X-ray Pulsar Navigation (XPNAV). By using the nonhomogeneous Poisson model of the received photons and the minimum recognition error criterion, a classifier based on the Bayesian theorem is proposed. For X-ray pulsars recognition with unknown Doppler frequency and initial phase, the features of every X-ray pulsar are extracted and the unknown parameters are estimated using the Maximum Likelihood (ML) method. Besides that, a method to recognize unknown X-ray pulsars or X-ray disturbances is proposed. Simulation results certificate the validity of the proposed Bayesian classifier.