一种基于自适应密度阈值的未知雷达信号分选算法

摘要

Unknown radar signal sorting is always a problem of radar countermeasure.The density-based clustering algorithm does not work well when data distribution is not even,a new clustering algorithm based on adaptive density threshold is provided,which can process data without any prior knowledge.While data disribution is not even,with this proposed method,the radar signals are sorted,through finding the local density threshold,by takeing advantage of the distribution of signals from the same radar.Meanwhile,the efficiency can be improved,with a lemma is given.In the end,computer simulation results show that the proposed approach can not only discover clusters with arbitrary shapes and densities at different levels,but also be unsensitive to noise.%针对基于密度的聚类算法不能发现密度分布不均匀数据样本的问题,提出了一种基于自适应密度阈值的未知雷达信号分选算法。该方法利用同一部雷达数据的分布特性进行聚类,通过寻找局部密度阈值,以达到分选不同密度分布的雷达信号的目的,并且在此基础上提出一个引理,提升了算法的时间效率。算法测试表明,该方法对噪声不敏感,能够发现任意形状、大小和密度的聚类。