Analysis of goodness-of-fit method based on local property of statistical model for airborne sea clutter data

Distribution models are of practical significance to clutter modelling, target detection method and performance evaluation in sea clutter background. The goodness of fit (GOF) between the real sea clutter data and the assumed distribution can be used to choose the proper distribution model. So the great importance of determining the suited statistical model and analysis of goodness-of-fit are highlighted. This paper concentrates on the statistical properties of real L-band airborne sea clutter datasets, which is collected at different grazing angles (30°∼60°). To overcome the shortage of traditional GOF methods, such as Mean Square Difference (MSD) and Modified Mean Square Difference (MMSD), the Variable-window local Mean Square Difference (VW-LMSD) is proposed. By this method, rectangle windows, whose number and position are flexibly selected according to the radar acquirement and sea state, are added to the sea clutter amplitude series to observe the partial GOF results of the statistical distribution models in detail, which provides a multi-angle GOF evaluation to judge the suitable statistical model and establishes a better foundation for clutter modelling, clutter classification and detection criterion selection further.