双参数加权的低信噪比面目标检测方法

Low Signal Noise Ratio Surface Target Inspection Method of Weighted Two-parameter

针对传统恒虚警检测低信噪比情况下面目标性能下降问题,提出了基于均值和方差双参数检测的新方案。首先采用了目标与背景统计特性差异最大化准则,估计出待检测单元的均值和方差,并通过互乘待检测单元的均值和方差获得最终的检测图像,得到了最优均值和最优方差统计特性,再利用全局CFAR检测检测出目标,从而在保证一定检测概率的同时降低虚警概率。仿真结果表明,该方法对低信噪比面目标的检测性能优于传统的恒虚警检测。

According to the problem of surface targets performances debasing under the condition of tradition- al constant false alarm rate （CFAR） inspection and low signal noise ratio, a new inspection method based on mean value and variance two-parameter is proposed. Firstly, target and background statistical characteristic difference maximum rule is used to estimate the mean value and variance of the inspected unit. And the final inspection image is obtained through multiplication on the mean value and variance of the inspected unit to obtain the statistical char- acteristics of the best mean value and variance statistical characteristic. And then, global CFAR inspection is used to inspect targets to guarantee a certain inspection probability and reduce false alarm probability. Simulation results show that the inspection characteristics of the method for low signal noise ratio surface target is better than that of traditional CFAR inspection.