| 摘要: |
| 针对复杂电磁环境下常规信号分析方法难以解决的多功能雷达信号分选“增批”和“漏批”问题，提出了一种改进的复杂网络社区检测信号分选方法。该方法首先通过有限穿透可视图将信号映射为复杂网络，引入基于密度的空间聚类去除杂散脉冲;然后根据节点的介数中心性改进标签传播算法，提高了社区划分的稳定性;最后利用密度峰值聚类合并子社区，完成分选过程。仿真结果表明，所提方法对多功能雷达信号分选正确率为98.13%；且增加杂散脉冲占比至35%时，分选批数未发生变化，能够有效处理“增批”和“漏批”问题。 |
| 关键词: 多功能雷达 信号分选 增批 漏批 有限穿透可视图 复杂网络社区检测 |
| DOI：10.20079/j.issn.1001-893x.240613003 |
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| 基金项目: |
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| Multi-functional Radar Signal Sorting Based on Improved Complex Network Community Detection |
| LI Shitong,HU Jin,YAN Bo |
| (The 724th Research Institute of China State Shipbuilding Corporation Limited,Nanjing 211153,China) |
| Abstract: |
| For the problem that conventional signal analysis methods are prone to cause the “increasing batch” and “missing batch” in multi-functional radar signal sorting in complex electromagnetic environments,a multi-functional radar signal sorting method based on improved complex network community detection is proposed.This method first transforms the signal sequence into the complex network using limited penetration visibility graph.Then,it introduces spatial clustering with density to eliminate spurious pulses.Subsequently,the label propagation algorithm is improved according to the between centrality of nodes,enhancing the stability of community division.Finally,the sub-communities are merged to complete the signal sorting task by density peak clustering.Simulation results show that the proposed method achieves a sorting accuracy of 98.13% for multi-functional radar signals.Moreover,even when the proportion of spurious pulses increases to 35%,the number of sorted batches remains unchanged,effectively alleviating the “increasing batch” and “missing batch” problems. |
| Key words: multi-functional radar signal sorting increasing batch missing batch limited penetrable visible graph complex network community detection |
