NDLI: An efficient Bayesian algorithm for joint target tracking and classification

Content Provider	IEEE Xplore Digital Library
Author	Wei Mei Gan-lin Shan Li, X.R.
Copyright Year	2004
Description	Author affiliation: Dept. of Electron. Eng., Shijiazhuang Mech. Eng. Coll., Shijazhuang, China (Wei Mei; Gan-lin Shan)
Abstract	It is pointed our in this paper that a more appropriate description of the joint target tracking and classification (JTC) problem would be the simultaneous probability density function (pdfs) of target state and target class instead of the joint target state-class pdf. In this paper, models of different classes are combined info a unified set. The Bayesian optimal JTC algorithm based on pdfs of target state and target class is derived, which integrates a Bayesian multiple-model filter and a Bayesian classifier. Also given is a suboptimal JTC algorithm with much lesser computational complexity, which is suitable for real-time application. Simulation results reveal that the proposed JTC algorithm provides a theoretically attractive solution to a class of joint target, tracking and classification problems.
Starting Page	2090
Ending Page	2098
File Size	1291793
Page Count	9
File Format	PDF
ISBN	0780384067
DOI	10.1109/ICOSP.2004.1442188
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-08-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian methods Target tracking Radar tracking Equations Sensor phenomena and characterization Sensor systems Aerodynamics Target recognition Radar cross section Passive radar
Content Type	Text
Resource Type	Article

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