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Particle filter using acceptance-rejection method with emphasis on the target tracking problem.

Tsang Yuk Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 59-62). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Sequential Monte Carlo --- p.5 / Chapter 2.1 --- Recursive Bayesian estimation --- p.7 / Chapter 2.2 --- Bayesian sequential importance sampling --- p.8 / Chapter 2.3 --- Sclcction of iiiipoitance function --- p.10 / Chapter 2.4 --- Particle filter --- p.12 / Chapter 3 --- Target tracking and data association --- p.15 / Chapter 3.1 --- Target tracking and its applications --- p.16 / Chapter 3.2 --- Data association and JPDA method --- p.16 / Chapter 4 --- Particle filter using the acceptance-rejection method --- p.21 / Chapter 4.1 --- Particle Filter using the acceptance-rejection method --- p.22 / Chapter 4.2 --- Modified accoptance-rcjoction algorithm --- p.24 / Chapter 4.3 --- Examples --- p.26 / Chapter 4.3.1 --- Example 1: One dimensional non-linear case --- p.26 / Chapter 4.3.2 --- Example 2: Bearings-only tracking example --- p.27 / Chapter 4.3.3 --- Example 3: Single-target tracking --- p.31 / Chapter 4.3.4 --- Example 4: Multi-target tracking --- p.33 / Chapter 4.4 --- A new importance weight for bearings-only tracking problem --- p.34 / Chapter 5 --- Conclusion --- p.41

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_325578
Date January 2006
ContributorsTsang, Yuk Fung., Chinese University of Hong Kong Graduate School. Division of Statistics.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, xi, 62 leaves : ill. ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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