Paper
19 May 2006 Weiss-Weinstein lower bound for maneuvering target tracking
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Abstract
Typically, the posterior Cramer-Rao lower bound (PCRLB) is the performance bound of choice in tracking applications. This is primarily due to the availability of a computationally efficient recursive formulation of the bound. It has been shown, however, that this bound is weak in certain applications. Weiss-Weinstein lower bound (WWLB) is another second-order error bound that is free from the regularity conditions and it is applicable in a wide range of problems. In addition, it has free variables that can be tuned to get tighter bounds. In this paper, we develop the WWLB for maneuvering target tracking. In particular, we utilize the ability of the WWLB to handle continuous and discrete random variables: target motion model is represented by a separate discrete variable and the bound is calculated over the continuous state and discrete motion model variables. The bound is tightened by optimizing with respect to the free variables.
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T. Sathyan, M. Hernandez, A. Sinha, and T. Kirubarajan "Weiss-Weinstein lower bound for maneuvering target tracking", Proc. SPIE 6236, Signal and Data Processing of Small Targets 2006, 62360G (19 May 2006); https://doi.org/10.1117/12.667792
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Cited by 2 scholarly publications.
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KEYWORDS
Motion models

Matrices

Process modeling

Astatine

Sensors

Switches

Switching

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