DFA在海杂波标度特性分析及目标检测中的应用

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

采用消除趋势波动分析(DFA)方法,研究了非平稳海杂波的标度特性及其参数表征问题,并提出了一种基于标度特性差异的目标检测算法。首先,在海杂波建模为分数布朗运动模型的基础上,对比分析了DFA和波动分析(FA)得出的标度特性,并初步解释了交叉标度现象出现的机理。然后,在假定相邻尺度范围内海杂波与理想分形模型相吻合的前提下,引入分段标度指数来表征海杂波标度特性随尺度的变化关系,分析结果表明,在特定的尺度范围内该参数可以有效区分目标单元与海杂波单元。为此,以该尺度范围内的分段标度指数均值为检验统计量设计了一种新的目标检测算法,并对尺度区间范围的选取、检测性能等问题进行了分析。实测数据中的检测性能证实了检测算法的有效性。

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.