Under homogeneous and heterogeneous environments, the VI-CFAR detector is outstanding and robust on the detection performance and the control ability of false alarm. However, the detection performance of the VI-CFAR degrades extremely if the interfering targets are not confined to a single half of the reference windows. To overcome this problem, the paper presents an improved MVI-CFAR detector, which replaces the SO-CFAR by the OSCA-CFAR and the OSSOCFAR. It can solve both the interfering target occurring randomly in the reference windows and the number of interfering targets exceeding the maximum numbers of resisting interfering targets in a single half of the reference windows. In this paper, we also analyze the variation characteristics of the statistic VI under the different number of interfering targets and under the different signal-noise rate. The analysis is helpful to design and assess the maximum number of resisting interfering targets in Vl-type CFAR detectors. The simulation results show that the MVI-CFAR is more robust under multi-targets environments and its processing time is only half of the other improved VI-CFAR detectors.%VI-CFAR检测器在均匀环境和非均匀环境下均具有较强的自适应性,但若前后两个参考滑窗均存在干扰目标时,VI-CFAR检测性能急剧下降.为克服该问题,本文采用有序统计平均CFAR和有序统计选小CFAR来替代VI-CFAR中最小选择CFAR.所提出的算法不但解决了干扰目标位置随机分布的问题,还解决了当其中一个滑窗的干扰目标数超过最大容限时检测性能下降的问题.在参考滑窗中干扰目标个数与扰噪比均不相同的情况下,分析了统计量VI的变化,有助于评估和设计VI-CFAR类检测器在多目标环境下抗干扰目标的最大容限.仿真结果表明,该改进算法提高了VI-CFAR在多目标环境下的鲁棒性,与其他改进算法相比,其排序处理时间降低一倍.
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