刘鲁涛, 王璐璐, 陈涛. 基于改进DSets的无参数雷达信号分选算法[J]. 中国舰船研究, 2021, 16(4): 232–238. doi: 10.19693/j.issn.1673-3185.02012
引用本文: 刘鲁涛, 王璐璐, 陈涛. 基于改进DSets的无参数雷达信号分选算法[J]. 中国舰船研究, 2021, 16(4): 232–238. doi: 10.19693/j.issn.1673-3185.02012
LIU L T, WANG L L, CHEN T. Non-parametric radar signal sorting algorithm based on improved DSets[J]. Chinese Journal of Ship Research, 2021, 16(4): 232–238. doi: 10.19693/j.issn.1673-3185.02012
Citation: LIU L T, WANG L L, CHEN T. Non-parametric radar signal sorting algorithm based on improved DSets[J]. Chinese Journal of Ship Research, 2021, 16(4): 232–238. doi: 10.19693/j.issn.1673-3185.02012

基于改进DSets的无参数雷达信号分选算法

Non-parametric radar signal sorting algorithm based on improved DSets

  • 摘要:
      目的  随着电磁环境日益复杂,信号分选越来越困难。为了解决现有高效分选算法性能严重依赖于外界输入参数的不足,提出了基于DSets-DS的无参数雷达信号聚类算法。
      方法  将直方图均衡化后的主导集(dominant sets,DSets)算法应用于雷达信号分选,提出一种无参数的雷达信号脉冲聚类算法,然后结合D-S (Dempster-Shafer)证据理论,以解决DSets算法过度分割问题。
      结果  在无任何先验信息条件下,能够完成对雷达信号混合脉冲精准聚类;此外,在虚假脉冲比例低于50%的情况下,分选正确率大于93.13%。
      结论  将DSets算法与D-S证据理论结合,可有效完成对无先验信息的雷达信号脉冲聚类,且有很好的聚类性能。

     

    Abstract:
      Objective  With the increasingly complex electromagnetic environment, it is more and more difficult to separate signals. In order to solve the problem that the performance of the existing efficient sorting algorithm depends heavily on external input parameters, a non-parametric radar signal clustering algorithm based on Dominant Sets (DSets) and Dempster-Shafer(D-S) evidence theory is proposed.
      Method  The algorithm is applied to radar signal sorting; a non-parametric radar signal pulse clustering algorithm is then given and combined with D-S evidence theory to solve the problem of excessive DSets algorithm segmentation.
      Results  In the absence of any prior information, this algorithm can complete the precise clustering of mixed pulse radar signals. In addition, its sorting accuracy rate is more than 93.13% when the false pulse ratio is less than 50%.
      Conclusion  The combination of the DSets algorithm and D-S evidence theory can effectively complete the clustering of radar signal pulses without prior information, and achieves good clustering performance.

     

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