NDLI: Combined Cramer-Rao/Weiss-Weinstein Bound for Tracking Target Bearing

Content Provider	IEEE Xplore Digital Library
Author	Bell, K.L. Van Trees, H.L.
Copyright Year	2006
Description	Author affiliation: George Mason Univ., Fairfax, VA (Bell, K.L.; Van Trees, H.L.)
Abstract	A recursive Bayesian Cramer-Rao/Weiss-Weinstein bound for the discrete-time nonlinear filtering problem for the special case when the state-space model consists of a linear process model and a general (nonlinear) measurement model is developed. This type of model arises in many applications including target tracking. It is often the case that the recursive Bayesian Cramer-Rao bound (BCRB) developed by Tichavsky et al is a good predictor of mean-square error performance for some of the state vector parameters, but is a weak bound for other components. The recursive Weiss-Weinstein bound (WWB) developed by Rapoport & Oshman and Reece & Nicholson offers a potentially higher bound but is generally more difficult to derive and implement, and its evaluation involves choosing "test points" in the parameter space. It becomes equal to the BRCB in the limiting case when the test points equal zero. A bound which combines the BCRB with the WWB using non-zero test points only for a subset of the state-vector components can provide as tight a bound as the WWB while keeping the complexity manageable. We first derive the recursive bound for the linear process/nonlinear measurement model, then apply the bound to the problem of tracking the bearing and bearing rate of a narrowband source using observations from a sparse linear array. The bound is compared to the recursive BCRB and to simulated tracking performance. The BCRWWB provides a tighter bound than the BCRB for the bearing tracking error, which is subject to ambiguities
Starting Page	273
Ending Page	277
File Size	243339
Page Count	5
File Format	PDF
ISBN	1424403081
DOI	10.1109/SAM.2006.1706136
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Target tracking Bayesian methods Testing Filtering Vectors Nonlinear filters Narrowband AWGN Mean square error methods Performance analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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