| 引用本文: | 刘鲁涛,王璐璐,李品,等.DSets-DBSCAN无参数聚类的雷达信号分选算法.[J].国防科技大学学报,2022,44(4):158-163.[点击复制] |
| LIU Lutao,WANG Lulu,LI Pin,et al.Radar signal sorting algorithm for DSets-DBSCAN without parameter clustering[J].Journal of National University of Defense Technology,2022,44(4):158-163[点击复制] |
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| DSets-DBSCAN无参数聚类的雷达信号分选算法 |
| 刘鲁涛1,王璐璐1,李品2,陈涛1 |
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(1. 哈尔滨工程大学 信息与通信工程学院, 黑龙江 哈尔滨 150001;2. 南京电子技术研究所, 江苏 南京 210000)
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| 摘要: |
| 针对现有的很多高效分选算法的性能严重依赖于外界输入的参数问题,例如聚类数目、聚类容差等,将无参数聚类算法DSets-DBSCAN应用于雷达信号分选,提出了一种无参数的雷达信号脉冲聚类算法。该算法无须依赖于任何参数的设置,就能自适应地完成聚类。算法输入直方图均衡化处理过的成对相似性矩阵,使得Dsets(dominant sets)算法不依赖于任何参数；根据得到的超小簇自适应给出DBSCAN的输入参数；利用DBSCAN扩展集群。仿真实验证明,该算法对雷达脉冲描述字特征进行无参数分选的有效性。同时,在虚假脉冲比例(虚假脉冲数/雷达脉冲数)不高于80%的情况下,对雷达信号的聚类准确率在97.56%以上。 |
| 关键词: 信号预分选 无参数聚类 DSets 直方图均衡化 |
| DOI：10.11887/j.cn.202204017 |
| 投稿日期：2020-11-12 |
| 基金项目:国家自然科学基金资助项目(61801143)；中央高校基本科研业务费专项资金资助项目(3072020CF0815) |
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| Radar signal sorting algorithm for DSets-DBSCAN without parameter clustering |
| LIU Lutao1, WANG Lulu1, LI Pin2, CHEN Tao1 |
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(1. College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China;2. Nanjing Research Institute of Electronic Technology, Nanjing 210000, China)
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| Abstract: |
| For the problem of the performance of many existing efficient sorting algorithms depends heavily on the parameters from external input, such as clustering number and clustering tolerance, the parameterless clustering algorithm DSets-DBSCAN was applied to the radar signal sorting, and a parameterless radar signal pulse clustering algorithm was presented. The proposed algorithm could automatically cluster without relying on any parameter settings. Firstly, the algorithm input was the pairwise similarity matrix processed by histogram equalization, which made the Dsets(dominant sets) algorithm independent of any parameters. Then, the input parameters of DBSCAN were given adaptively according to the obtained ultra-small cluster. Finally, the cluster was extended by DBSCAN. Simulation results show that the proposed method is effective in sorting radar pulse descriptors without parameters. And the clustering accuracy of radar signals is higher than 97.56% in the case of the false pulse ratio (false pulse/radar pulse) is lower than 80%. |
| Keywords: signal presorting parameterless clustering dominant sets histogram equalization |
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