Hidden Markov models for radar pulse train analysis in electronic warfare

TitleHidden Markov models for radar pulse train analysis in electronic warfare
Publication TypeConference Paper
Year of Publication2005
AuthorsVisnevski, N., S. Haykin, V. Krishnamurthy, F. A. Dilkes, and P. Lavoie
Conference NameAcoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
Paginationv/597 - v/600 Vol. 5
Date Publishedmar.
Keywordscomplex pulse pattern extraction, corrupted pulse sequences, electronic warfare, feature extraction, hidden Markov model, hidden Markov models, military radar, noisy pulse sequences, Pattern Recognition, radar pulse train analysis, radar signal processing, radar word extraction, radar word templates, Viterbi algorithm

We present a new approach to radar pulse train analysis in electronic warfare. We consider an alternative to the classical time-of-arrival (TOA) histogram technique commonly used for extraction of complex pulse patterns. We derive a hidden Markov model for the radar word templates, and develop a modified version of the Viterbi algorithm to extract radar words from noisy and corrupted pulse sequences. We argue the advantages of this approach compared to the standard TOA histogram technique, and illustrate operation of the algorithm with computer simulation results.


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