Applying hidden Markov models to radar detection in clutter

Sea clutter amplitude is often modeled as a compound random variable Z=AX, where A is a positive valued random variable and X has a Rayleigh distribution. The K and discrete Rayleigh mixture distributions arise from this model using a gamma or discrete distribution, respectively, for A. In certain applications, successive values of A may be correlated. If this correlation is modeled as a finite Markov process, Z is described by a hidden Markov model (HMM). Amplitude only and phase coherent detection statistics are derived from the HMM models using locally optimal and likelihood ratio techniques, respectively. The performance of these algorithms are compared with CFAR and Doppler processors using radar data.