基于分数低阶本征滤波的雷达目标检测方法

在非高斯相关杂波背景下,通常杂波分布的概率密度函数结构复杂甚至无闭式表达,难以建立统计检测模型。针对此问题,以α稳定分布为背景,基于分数低阶统计量和最佳滤波器理论,以滤波器输出分数低阶信杂比最大为准则,给出了一种分数低阶本征滤波(FLOEF)模型。该模型利用杂波的分数低阶协方差矩阵对非高斯相关杂波进行白化,可显著改善信杂比,实现非高斯相关杂波背景下雷达目标的有效检测。通过仿真和实测数据给出了FLOEF在不同条件下的检测性能,并同传统基于二阶统计量的本征滤波进行了比较,结果验证了FLOEF的优越性。

Radar target detection method based on fractional lower order eigenfilter

It is difficult to establish statistical detection model in non-Gaussian correlated clutter backgrounds when the clutter has a complicated probability density function(PDF) or even no closed expression.Therefore,a fractional lower order eigenfilter(FLOEF) model under the conditions of α-stable clutter distribution is proposed.The proposed model mainly bases on the fractional lower order statistics and the optimum filtering theory,and the optimum filter is obtained with the rule of maximizing the output fractional lower order signal-to-clutter power ratio.The proposed method can whiten the non-Gaussian correlated clutter by using the clutter fractional lower order covariance matrix,so as to greatly improve the signal-to-clutter ratio and detect the radar target in non-Gaussian correlated clutter effectively.Simulations and real data results show that the detection performance of FLOEF obviously outperforms the traditional eigenfilter(EF) in non-Gaussian correlated clutter environments.