基于聚类算法的高分辨率雷达数据融合

Zhongzhi Li, Xue-gang Wang
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引用次数: 8

摘要

高分辨率雷达系统通常具有海量的原始数据,因此必须尽快进行数据融合。本文提出了一种基于一维距离计算的快速聚类算法。该算法将原始数据按单维距离划分为子集,然后根据单维距离和集密度对子集进行合并。最后将该算法应用于机场场景监控雷达系统的数据融合。实验结果表明,该算法执行效率高,对噪声数据不敏感;它对高分辨率雷达数据融合具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High Resolution Radar Data Fusion Based on Clustering Algorithm
High resolution radar system usually has a massive amount of raw data, so we have to carry out data fusion as quickly as possible. In this paper, we propose a fast clustering algorithm based on single dimensional distance calculation. The proposed algorithm divides raw data into subsets by single dimensional distance, and then merges subsets according to single dimensional distance and set-density. At last we apply the proposed algorithm to carry out data fusion for airport scene surveillance radar system. Experimental result shows the proposed algorithm has high execution efficiency and is not sensitive to noise data; it is useful for high resolution radar data fusion.
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