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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