文章摘要
王星,陈相,周一鹏,陈游,肖冰松,王洪迅.一种基于改进DBSCAN的雷达信号分选算法[J].空军工程大学学报:自然科学版,2021,22(3):47-54
一种基于改进DBSCAN的雷达信号分选算法
A Radar Signal Sorting Algorithm Based on Improved DBSCAN Algorithm
  
DOI:
中文关键词: DBSCAN  聚类  云模型  雷达信号分选
英文关键词: DBSCAN  clustering  cloud model  radar signal sorting
基金项目:航空科学基金项目(20175596020)
作者单位
王星,陈相,周一鹏,陈游,肖冰松,王洪迅 空军工程大学航空工程学院 西安 710038 
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中文摘要:
      针对传统DBSCAN算法参数设置依靠人工经验的不可靠性,并且对非均匀数据聚类效果差的问题,基于云模型(Cloud Model)提出了一种CMDBSCAN算法,算法首先结合距离曲线倾角突变的特点自适应获得邻域半径,并根据雷达信号分布密度设置聚类密度点数阈值,可实现DBSCAN算法自适应运行;同时结合多维云模型理论,对DBSCAN 算法分选结果进行有效性评估,利用判定结果进一步优化参数设置。根据仿真模拟的复杂对抗过程中帧收的雷达信号进行实验,证明该算法可实现非均匀雷达信号的自适应分选,同时可有效避免在多功能雷达信号分选中的“增批”问题。
英文摘要:
      Aimed at the problems that the parameter setting of traditional DBSCAN algorithm relies on the unreliability of manual experience, and the heterogeneous data clustering effect is poor, A CMDBSCAN model is proposed based on Cloud model. Firstly, according to the characteristics of the distance curve angle mutation, the adaptive neighborhood radius is obtained. And cluster density threshold is set according to the distribution density of radar signal, realizing DBSCAN algorithm run adaptively. And then, in combination with the theory of multidimensional cloud model, the validity of DBSCAN algorithm sorting results is evaluated, and the decision results are used to further optimize parameter setting. The experiment is carried out according to the radar signal received during the complex countermeasure process. The result shows that the algorithm can realize the adaptive sorting of non uniform radar signals and effectively deal with the “batch” problem in multi mode radar signal sorting.
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