13 July 2000 Interactive banks of Bayesian matched filters
Author Affiliations +
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Boris L. Rozovskii, Boris L. Rozovskii, Anton Petrov, Anton Petrov, Rudolf B. Blazek, Rudolf B. Blazek, } "Interactive banks of Bayesian matched filters", Proc. SPIE 4048, Signal and Data Processing of Small Targets 2000, (13 July 2000); doi: 10.1117/12.391972; https://doi.org/10.1117/12.391972
PROCEEDINGS
12 PAGES


SHARE
RELATED CONTENT

IMM algorithm and aperiodic data
Proceedings of SPIE (November 25 1992)
Detection in clutter enhancement
Proceedings of SPIE (June 17 1996)

Back to Top