| 基于改进FCM的多传感器多目标数据互联算法 |
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| 引用本文： | 程知敬,汪圣利. 基于改进FCM的多传感器多目标数据互联算法[J]. 现代雷达, 2011, 0(11): 45-48 |
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| 作者姓名： | 程知敬 汪圣利 |
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| 作者单位： | 南京电子技术研究所; |
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| 摘 要： | 将模糊聚类分析的方法运用到数据互联中是现今多传感器多目标跟踪的发展方向之一。文中在模糊c-均值聚类(FCM)算法的基础上提出了一种适用于多传感器多目标数据互联的改进算法,该算法通过对隶属度函数进行加权,同时考虑了样本对聚类中心和样本与样本之间的隶属关系。仿真结果表明该改进算法使得分类效果更加清晰,能够更好地将测量结果划分给各个目标,且所需的迭代次数更少,收敛速度更快。仿真结果验证了算法的正确性和有效性。
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| 关 键 词： | 模糊c-均值聚类 加权因子 数据互联 |
An Improved Fuzzy C-means Clustering Algorithm in Multi-sensor Multi-target Data Association |
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| CHENG Zhi-jing,WANG Sheng-li. An Improved Fuzzy C-means Clustering Algorithm in Multi-sensor Multi-target Data Association[J]. Modern Radar, 2011, 0(11): 45-48 |
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| Authors: | CHENG Zhi-jing WANG Sheng-li |
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| Affiliation: | CHENG Zhi-jing,WANG Sheng-li(Nanjing Research Institute of Electronics Technology,Nanjing 210039,China) |
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| Abstract: | One of the directions of the future development for multi-sensor multi-target data association is the fuzzy clustering analysis method.This paper presents an improvement based on fuzzy c-means clustering(FCM) algorithm.This new algorithm,by weighted the membership functions,can considerate the subordinate relationship between samples and clustering centers.The simulation results show that the improved algorithm can provide clearer classification results to better the measured results of the division to each... |
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| Keywords: | fuzzy c-means clustering weight coefficient data association |
| 本文献已被 CNKI 等数据库收录！ |
