Hidden Markov models in radar target classification
Guy Kouemou, Felix Opitz · 2007
A classification technology is presented that uses hidden Markov models (HMMs) to classify simulated and real radar signals from five classes of targets: personnel, tracked vehicles, wheeled vehicles, helicopters and propeller aircrafts. Similar to techniques that have been well proven in speech recognition, the time-varying nature of radar doppler data is exploited. The method classifies the different targets by their different doppler characteristics. The purpose of this paper is to make a comparison between three kinds of HMM methods: 1. HMM with continuous outputs (CHMM) 2. HMM with discrete outputs (DHMM) 3. Semi-continuous hidden Markov models (SCHMM). (5 pages)