Application of DFA to Scaling Property Analysis of Sea Clutter and Target Detection

The detrended fluctuation analysis (DFA) method is adopted to research the scaling property and parametric representation problem of non-stationary sea clutter, and a target detection algorithm is presented based on diversity of scaling property. First, the scaling property derived from DFA and fluctuation analysis (FA) is analyzed with comparison on the basis that sea clutter is modeled as Fractional Brownian Motion (FBM). A basic interpretation is given to the scaling crossover phenomenon in DFA. Then, the concept of segment generalized Hurst exponent is introduced to express the changing pattern of scaling property with scales, on the premise that sea clutter complies with ideal fractal model in adjacent scale range. Analysis results show that this parameter can effectively distinguish between target bins and sea clutter bins on a specified scale range. As a result, a new target detection algorithm is put forward with the mean of segment generalized Hurst exponent in such scale range as detection statistics. Such problems as the choice of this scale range, detection performance are also analyzed. The detection performance with real sea clutter justified the effectiveness of the algorithm.