Sequential Bearings-Only-Tracking Initiation with Particle Filtering Method
Joint Authors
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-25
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
The tracking initiation problem is examined in the context of autonomous bearings-only-tracking (BOT) of a single appearing/disappearing target in the presence of clutter measurements.
In general, this problem suffers from a combinatorial explosion in the number of potential tracks resulted from the uncertainty in the linkage between the target and the measurement (a.k.a the data association problem).
In addition, the nonlinear measurements lead to a non-Gaussian posterior probability density function (pdf) in the optimal Bayesian sequential estimation framework.
The consequence of this nonlinear/non-Gaussian context is the absence of a closed-form solution.
This paper models the linkage uncertainty and the nonlinear/non-Gaussian estimation problem jointly with solid Bayesian formalism.
A particle filtering (PF) algorithm is derived for estimating the model’s parameters in a sequential manner.
Numerical results show that the proposed solution provides a significant benefit over the most commonly used methods, IPDA and IMMPDA.
The posterior Cramér-Rao bounds are also involved for performance evaluation.
American Psychological Association (APA)
Liu, Bin& Hao, Chengpeng. 2013. Sequential Bearings-Only-Tracking Initiation with Particle Filtering Method. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1012404
Modern Language Association (MLA)
Liu, Bin& Hao, Chengpeng. Sequential Bearings-Only-Tracking Initiation with Particle Filtering Method. The Scientific World Journal No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1012404
American Medical Association (AMA)
Liu, Bin& Hao, Chengpeng. Sequential Bearings-Only-Tracking Initiation with Particle Filtering Method. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1012404
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1012404