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http://dx.doi.org/10.1109/JCN.2016.000102

Multi-mode Radar Signal Sorting by Means of Spatial Data Mining  

Wan, Jian (College of Information and Communication Engineering, Harbin Engineering University)
Nan, Pulong (College of Information and Communication Engineering, Harbin Engineering University)
Guo, Qiang (College of Information and Communication Engineering, Harbin Engineering University)
Wang, Qiangbo (College of Science, Harbin Engineering University)
Publication Information
Journal of Communications and Networks / v.18, no.5, 2016 , pp. 725-734 More about this Journal
Abstract
For multi-mode radar signals in complex electromagnetic environment, different modes of one emitter tend to be deinterleaved into several emitters, called as "extension", when processing received signals by use of existing sorting methods. The "extension" problem inevitably deteriorates the sorting performance of multi-mode radar signals. In this paper, a novel method based on spatial data mining is presented to address above challenge. Based on theories of data field, we describe the distribution information of feature parameters using potential field, and makes partition clustering of parameter samples according to revealed distribution features. Additionally, an evaluation criterion based on cloud model membership is established to measure the relevance between different cluster-classes, which provides important spatial knowledge for the solution of the "extension" problem. It is shown through numerical simulations that the proposed method is effective on solving the "extension" problem in multi-mode radar signal sorting, and can achieve higher correct sorting rate.
Keywords
Cloud model; data field; membership; multi-mode radar signal sorting; spatial data mining;
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