Hierarchical classification of dynamically varying radar pulse repetition interval modulation patterns

The central purpose of passive signal intercept receivers is to perform automatic categorization of unknown radar signals Currently there is an urgent need to develop intelligent classification algorithms for these devices due to emerging complexity of radar waveforms Especially multifunction radars (MFRs) capable of performing several simultaneous tasks by utilizing complex dynamically varying scheduled waveforms are a major challenge for automatic pattern classification systems To assist recognition of complex radar emissions in modern intercept receivers we have developed a novel method to recognize dynamically varying pulse repetition interval (PRI) modulation patterns emitted by MFRs We use robust feature extraction and classifier design techniques to assist recognition in unpredictable real-world signal environments We classify received pulse trains hierarchically which allows unambiguous detection of the subpatterns using a sliding window Accuracy robustness and reliability of the technique are demonstrated with extensive simulations using both static and dynamically varying PRI modulation patterns (C) 2010 Elsevier Ltd All rights reserved