Bayesian multiple target tracking von stone lawrence (12 Ergebnisse)

Zustand: Very Good. *Price HAS BEEN REDUCED by 10% until Monday, Nov. 9 (weekend SALE item)* 317 pp., hardcover, highlighting to a few early pages, else very good. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Photos available upon request. …

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hardcover. Zustand: New. In shrink wrap. Looks like an interesting title.

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Zustand: As New. Unread book in perfect condition.

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Zustand: As New. Unread book in perfect condition.

Zustand: New. 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.&Uumlber den Autor.

Zustand: New. &Uumlber den AutorLawrence D. Stone is chief scientist at Metron, Inc. He received his Ph.D. and MS in mathematics from Purdue University. Roy Streit is a senior scientist at Metron, Inc. He earned his Ph.D. in mathematics from the Univ.

Hardback. Zustand: New. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements the Bayesian single target recursion, this resource provides numerous examples that involve the use of particle filters. With these examples illustrating the developed concepts, algorithms, and approaches -- the book helps radar engineers track when observations are nonlinear functions of target site, when the target state distributions or measurement error distributions are not Gaussian, in low data rate and low signal to noise ratio situations, and when notions of contact and association are merged or unresolved among more than one target.…

Hardback. Zustand: New. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements the Bayesian single target recursion, this resource provides numerous examples that involve the use of particle filters. With these examples illustrating the developed concepts, algorithms, and approaches -- the book helps radar engineers track when observations are nonlinear functions of target site, when the target state distributions or measurement error distributions are not Gaussian, in low data rate and low signal to noise ratio situations, and when notions of contact and association are merged or unresolved among more than one target.…