Bayesian Multiple Target Tracking

Using the Bayesian inference framework, this book enables the reader to design and develop mathematically sound algorithms for dealing with tracking problems involving multiple targets, multiple sensors, and multiple platforms. It shows how non-linear Multiple Hypothesis Tracking and the Theory of United Tracking are successful methods when multiple target tracking must be performed without contacts or association. With detailed examples illustrating the developed concepts, algorithms, and approaches, the book helps the reader track when observations are non-linear functions of target site, when the target state distributions or measurements error distributions are not Gaussian, when notions of contact and association are merged or unresolved among more than one target, and in low data rate and low signal to noise ratio situations.

ISBN 1580530249   Pages 324 ISBN13 9781580530248 (What's this?)   Volumes 1 Publisher Artech House   Weight (grammes) 646 Imprint Artech House   Published in London Format Hardback   Series title Radar S. Publication date 01 Jul 1998   Height (mm) 229 Library of Congress 99-27662   Width (mm) 152 DEWEY 621.38480151   Spine width (mm) 22 DEWEY edition DC21   Academic level Postgraduate, Professional / Scholarly

		Preface
		Introduction
		Acknowledgments
Ch. 1		Tracking Problems		1
Ch. 2		Bayesian Inference and Likelihood Functions		29
Ch. 3		Single Target Tracking		55
Ch. 4		Classical Multiple Target Tracking: Multiple Hypothesis Tracking		103
Ch. 5		Multiple Target Tracking Without Contacts or Association		161
Ch. 6		Likelihood Ratio Detection and Tracking: Theoretical Foundations		209
Ch. 7		Likelihood Ratio Detection and Tracking: Implementation Issues		269
		Appendix		291
		About the Authors		293
		Index		295

 Be the first to write a customer review