Bayesian Multiple Target Tracking

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Artech House, 1999 - Mathematics - 299 pages
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Get the solutions to your most challenging tracking problems with this up-to-date resource. Using the Bayesian inference framework, the book helps you design and develop mathematically sound algorithms for dealing with tracking problems involving multiple targets, multiple sensors, and multiple platforms. The book shows you how non-linear Multiple Hypothesis Tracking and the Theory of Unified Tracking are successful methods when multiple target tracking must be performed without contacts or association.

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Contents

Bayesian Inference and Likelihood Functions
29
References
53
Single Target Tracking
55
Copyright

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About the author (1999)

Lawrence D. Stone received his Ph.D. and MS in mathematics from Purdue University, Stone is Chief Operating Officer at Metron, Inc.

Carl A. Barlow holds S.B. and S.M. degrees in theoretical physics from MIT. Barlow is an independent scientific consultant.

Thomas L. Corwin received his Ph.D and MS in statistics from Princeton University. Corwin is Chief Executive Officer of Metron, Inc.

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