海杂波条件异方差特性分析与波动信息提取

由于低擦地角、高海况等易引起雷达海杂波序列的局部剧烈波动,传统的统计分布模型难以描述突然出现的具有冲激特性的强回波,因此,针对这一问题,将广义自回归条件异方差(Generalized Auto Regressive Conditional Heteroskedasticity,GARCH)模型引入海杂波建模中,通过 GARCH模型阶数步进搜索结合残差序列方差齐性检验,实现了海杂波数据的波动信息提取。经 X波段雷达实测数据验证,所提出的波动信息提取方法,可以很好地提取实测海杂波数据在局部区域或时间段内的波动信息,为特征检测方法设计提供有效的特征支撑。

Analysis of Conditional Heteroscedasticity Characteristics of Sea Clutter and Extraction of Fluctuation Information

Conditions such as low grazing angle and high sea state can easily cause severe local fluctuations of sea clutter se.quences in radar, and traditional statistical distribution models can hardly describe the strong echoes with impulsive charac.teristics appearing suddenly. To solve this problem, the generalized autoregressive conditional heteroscedasticity model is in.troduced into the sea clutter modeling, and the fluctuation information extraction of sea clutter data is realized by combiningthe multi-step search of the generalized autoregressive conditional heteroscedasticity model with the variance homogeneitytest of the residual sequence. Verified by the measured data of X-band radar, the proposed fluctuation information extrac.tion method can well extract the fluctuation information of measured sea clutter data in the local area or period, and provideeffective feature support for the design of feature detection methods.