
Bayesian Multiple Target Tracking
Artech House Publishers
Published in July 1999
Book
Hardback
324 pages
978-1-58053-024-8 (ISBN)
Shipment within 10-20 days
Description
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.
More details
Series
Language
English
Place of publication
Norwood
United States
Target group
College/higher education
Professional and scholarly
Product notice
Laminated cover
Illustrations
black & white illustrations
Dimensions
Height: 236 mm
Width: 165 mm
Thickness: 29 mm
Weight
621 gr
ISBN-13
978-1-58053-024-8 (9781580530248)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Lawrence D. Stone | Roy L. Streit | Thomas L. Corwin
Bayesian Multiple Target Tracking
Book
01/2014
2nd Edition
Artech House Publishers
€174.50
Shipment within 10-20 days
Persons
Lawrence D. Stone is Chief Operating Officer at Metron, Inc. He received his Ph.D. and MS in mathematics from Purdue University. Carl A. Barlow is an independent scientific consultant. He holds S.B. and S.M. degrees in theoretical physics from MIT. Thomas L. Corwin is Chief Executive Officer of Metron, Inc. He received his Ph.D and MS in statistics from Princeton University.
Content
The Multiple Target Detection and Tracking Problem -- The Case for the Bayesian Inference. Single Target Tracking -- Bayesian Filtering. Kalman Filtering. Discrete Bayesian Filtering. Classical Multiple Target Tracking -- General Multiple Hypothesis Tracking. Classical Multiple Hypothesis Tracking. Multiple Target Tracking Without Contacts or Association -- General Multiple Target Model. Relationship to Multiple Hypothesis Tracking. Likelihood Ratio Detection and Tracking: Theoretical Foundations. Likelihood Ratio Detection and Tracking: Implementation Issues. Appendices.