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为提高单元平均类恒虚警 (CA- CFAR)检测的性能 ,提出一种新的与噪声初始分布无关的恒虚警处理方法 ,即 Gauss双参数恒虚警检测 (GB- CFAR)方法。其特点是根据独立同分布噪声的非相参积累结果近似 Gauss分布的特性 ,用不同的参考单元估计积累后噪声的均值和标准差 ,然后将待检测单元减去均值估计值 ,再与标准差估计值和固定门限的乘积相比较 ,从而实现恒虚警检测。结果表明 ,由于剔除积累后的噪声均值等价于剔除了部分噪声能量 ,因此提高了信噪比 ,使得检测性能明显优于传统的 CA - CFAR检测器
In order to improve the performance of CA-CFAR detection, a new CFAR method that is independent of initial noise distribution is proposed, that is, the Gauss two-parameter CFAR method. The method is characterized by estimating the mean and standard deviation of accumulated noise with different reference units according to the characteristics of approximating Gauss distribution of non-coherent accumulation results of independent and identically distributed noise, subtracting the mean estimation value from the unit to be detected, Estimated value and the fixed threshold of the product compared to achieve CFAR detection. The results show that since the accumulated noise mean is equivalent to removing part of the noise energy, the signal - noise ratio is improved and the detection performance is obviously better than the traditional CA - CFAR detector