Bayesian multiple target tracking
著者
書誌事項
Bayesian multiple target tracking
（The Artech House radar library）
Artech House, c1999
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
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.
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