Threat Estimation by Electronic Surveillance of Multifunction Radars: A Stochastic Context Free Grammar Approach

TitleThreat Estimation by Electronic Surveillance of Multifunction Radars: A Stochastic Context Free Grammar Approach
Publication TypeConference Paper
Year of Publication2006
AuthorsWang, A., V. Krishnamurthy, F. A. Dilkes, and N. A. Visnevski
Conference NameDecision and Control, 2006 45th IEEE Conference on
Pagination2153 -2158
Date Publisheddec.
Keywordscontext-free grammars, electronic surveillance, electronic warfare surveillance, maximum likelihood estimation, maximum likelihood threat estimation, military computing, military radar, military system, multifunction radars, stochastic context free grammar, stochastic processes
Abstract

Multi-function radars (MFRs) are sophisticated sensors that are widely used in military systems. It is shown that the stochastic context free grammar (SCFG) efficiently captures the essential features of the MFR dynamics compared to more traditional finite Markov models (regular grammars). The dynamics of the MFR are formulated as a mixture of two SCFGs - the mixture parameter determining the threat level. We then present a maximum likelihood threat estimation algorithm by capturing the noisy radar signals represented as strings from the MFR language. The relative simplicity of the SCFG model facilitates development of a systematic design procedure for electronic warfare (EW) surveillance algorithms

URLhttp://dx.doi.org/10.1109/CDC.2006.377254
DOI10.1109/CDC.2006.377254

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