基于小生境遗传算法的分布式OS-CFAR检测系统优化与性能分析

 利用小生境遗传算法,对不同检测窗长度和检测信噪比的三传感器分布式 OS-CFAR检测系统进行了优化设计,给出了一组针对不同检测环境与融合方式的搜索结果。分析表明,对于非一致环境下分布式 OS-CFAR检测系统,小生境遗传算法是一种良好的优化算法。利用搜索结果,研究了不同融合方式下环境变化对分布式 OS-CFAR检测系统的性能影响,结果表明,“或”融合对检测环境的非一致变化具有较强的鲁棒性,而“3选2”融合和“与”融合对检测环境的变化比较敏感。

OPTIMIZATION AND PERFORMANCE ANALYSIS OF DISTRIBUTED OS-CFAR DETECTION BASED ON NICHE GENETIC ALGORITHMS

In this paper, niche genetic algorithms are used to optimize the performance of a distributed 3 sensor OS CFAR detection system with different reference lengths and signal to noise ratios. A set of quasi optimum results is given and analyzed, which proves that niche genetic algorithms are efficient for this optimization. The influences of the nonidentity in environment on the performance of the distributed OS CFAR detector for different fusion rules are discussed subsequently. The results indicate that when OR fusion is employed, the system is robust to the nonidentical variety of detection environment, while 2 of 3 and AND fusion are sensitive in the same situation.