Hidden markov modeling for radar electronic warfare

摘要

The present invention relates to a method for identifying modern radar systems. A finite state automaton comprising a finite set of states and a set of transitions from state to state that occur in dependence upon an input signal is provided for modeling the radar system. The finite state automaton produces a sequence of output symbols from an output alphabet in dependence upon the state transitions such that the sequence of output symbols corresponds to a received electromagnetic signal emitted from the radar system. The finite state automaton is then transformed into a hidden Markov model such that a sequence of observation symbols produced from an observation alphabet by the hidden Markov model is equal to the sequence of output symbols. The method provides powerful tools for solving electronic warfare problems such the classification problem, the decoding problem, the prediction problem and the training problem. Describing the radar system as a finite state automaton and transforming it into a hidden Markov model provides flexibility and preserves a maximum of information provided by the observed signals. The new method is compatible with conventional receiver front-ends and allows integration into a wide range of legacy ES, EA and ELINT systems. The only hardware requirement is a fast processor with sufficient memory.