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Proceedings Paper

Interactive banks of Bayesian matched filters
Author(s): Boris L. Rozovskii; Anton Petrov; Rudolf B. Blazek
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Paper Abstract

There exist a number of powerful methods for detecting small low observable targets with stationary dynamics in image sequences provided by IR and other imaging sensors (see e.g.12). However, these methods need to be extended to handle maneuvering targets. In this paper, we demonstrate that banks of interacting Bayesian filters (BIBF) can be utilized for this purpose. We are considering target dynamics modeled by jump-linear systems. In contrast to previous studies, we do not assume that the mode jump process is a Markov chain. In particular, we allow the probabilities of jumps to be conditioned on the state variable. Then, we present a computationally efficient (real time) algorithm for detection and tracking of low observable agile targets. A comparison of BIBY and IMM approaches is carried out in a simple example.

Paper Details

Date Published: 13 July 2000
PDF: 12 pages
Proc. SPIE 4048, Signal and Data Processing of Small Targets 2000, (13 July 2000); doi: 10.1117/12.391972
Show Author Affiliations
Boris L. Rozovskii, Univ. of Southern California (United States)
Anton Petrov, Univ. of Southern California (United States)
Rudolf B. Blazek, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 4048:
Signal and Data Processing of Small Targets 2000
Oliver E. Drummond, Editor(s)

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