Radar working‐state identification using the hidden Markov model

Using the statistical signal processing principle in the field of natural language processing, a radar state identification approach based on the hidden Markov model (HMM) is proposed. Since each radar state is modelled by three model parameters of a HMM, the radar state identification can be solved from the solution of the evaluation problem of a HMM. Simulation results show that the HMM‐based statistical identification method has tolerance to parameter error, which is suitable for the intelligent identification of the radar state in a complex environment.