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通常将复合随机变量Ｚ＝ＡＸ作为海杂波幅度的模型，其中Ａ为正值的随机变量，Ｘ具有瑞利分布。Ｋ和离散瑞利混合分布源自采用Ａ分别为伽马或离散分布的该模型。在某些应用中，能将Ａ的连续值进行相关。如果该相关被模拟成有限Ｍａｒｋｏｖ过程的话，那么用隐含Ｍａｒｋｏｖ模型（ＨＭＭ）来描述Ｚ。仅有幅度的和相位相干检测的统计结果是由ＨＭＭ模型用局部最优和似然比技术导出的。文中将这些算法的性能与使用雷达数据的ＣＦＡＲ和多普勒处理器作了比较。
The composite random variable Z = AX is usually used as a model of the sea clutter amplitude, where A is a positive random variable and X has a Rayleigh distribution. The mixed distribution of K and discrete Rayleigh originates from the model using A, respectively, gamma or discrete distribution. In some applications, continuous values of A can be correlated. If this correlation is modeled as a finite Markov process, then an implicit Markov model (HMM) is used to describe Z. The statistical results of only amplitude and phase coherent detection are derived from the HMM model using the local optimality and likelihood ratio technique. The performance of these algorithms is compared with CFAR and Doppler processors that use radar data.