| 摘要: |
| 辐射源定位是战场军事行动的重要基础。而复杂战场电磁环境下，难以建立有效的传播模型，同时在多辐射源的条件下传统的定位方法难以快速准确定位。针对上述问题，基于分布式电磁态势感知网络，提出了一种智能优化感知节点位置的辐射源定位方法，采用改进的布谷鸟搜索（Cuckoo Search）算法进行网络中感知节点位置寻优，再利用克里金插值（Kriging Interpolation）来实现电磁态势的感知，以及对电磁态势数据进行结合峰值密度聚类（Density Peaks Clustering,DPC）思想的K-means聚类从而实现辐射源定位。该方法能够在初始部署不理想的条件下调整感知位置，实现无先验信息的目标辐射定位。实验表明，所提方法在多目标复杂环境下，插值精度优于随机部署和普通布谷鸟优化感知位置的克里金插值，在感知区域为4 km×4 km，节点总数为40 000个，且感知节点占比1%的条件下，平均定位误差为47.28 m，具有一定的应用前景。 |
| 关键词: 电磁态势感知 辐射源定位 无线传感器网络 布谷鸟搜索 聚类算法 |
| DOI：10.20079/j.issn.1001-893x.230601002 |
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| 基金项目:国家自然科学基金面上项目(61971473) |
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| A Radiation Source Localization Algorithm Based on Electromagnetic Situation Data Clustering |
| LIU Jinfan,SHEN Zhexian,CHANG Chao |
| ((College of Electronic Countermeasure,National University of Defense Technology,Hefei 230037,China)) |
| Abstract: |
| Radiation source location is an important basis for military operations on the battlefield.However,in the complex battlefield electromagnetic environment,it is difficult to establish an effective propagation model,and under the condition of multiple radiation sources,it is difficult for traditional positioning methods to realize locating quickly and accurately.In order to solve above problems,based on the distributed electromagnetic situation awareness network of ground movable unmanned platform,a radiation source localization method is proposed to intelligently optimize the node sensing position,and the improved Cuckoo Search Algorithm is used to optimize the node sensing position in the network,and then the Kriging Interpolation is used to realize the perception of electromagnetic situation,and K-means clustering of situation data combined with Density Peaks Clustering(DPC) ideas to achieve radiation source localization.This method can adjust the sensing position under the condition of unsatisfactory initial deployment to achieve target radiation localization without prior information.Experiments show that the interpolation accuracy of the proposed method is better than that of Kriging Interpolation of random deployment and ordinary Cuckoo Optimized Sensing position in a multi-target complex environment,and the average positioning error is 47.28 m while the perception area is 4 km×4 km,the total number of nodes is 40 000,and the perception node accounts for 1%,so it has certain application prospects. |
| Key words: electromagnetic situation awareness radiation source location wireless sensor network Cuckoo search clustering algorithm |
