A Bayesian Classifier for X-Ray Pulsars Recognition
Joint Authors
Zhan, Yafeng
Liang, Hao
Duan, Chaowei
Source
International Journal of Aerospace Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-11-24
Country of Publication
Egypt
No. of Pages
10
Abstract EN
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.
American Psychological Association (APA)
Liang, Hao& Zhan, Yafeng& Duan, Chaowei. 2016. A Bayesian Classifier for X-Ray Pulsars Recognition. International Journal of Aerospace Engineering،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1104976
Modern Language Association (MLA)
Liang, Hao…[et al.]. A Bayesian Classifier for X-Ray Pulsars Recognition. International Journal of Aerospace Engineering No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1104976
American Medical Association (AMA)
Liang, Hao& Zhan, Yafeng& Duan, Chaowei. A Bayesian Classifier for X-Ray Pulsars Recognition. International Journal of Aerospace Engineering. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1104976
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1104976
