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Multiple-Parameter Radar Signal Sorting Using Support Vector Clustering and Similitude Entropy Index

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Abstract

The radar signal sorting method based on traditional support vector clustering (SVC) algorithm takes a high time complexity, and the traditional validity index cannot efficiently indicate the best sorting result. Aiming at solving the problem, we study a new sorting method based on cone cluster labeling (CCL) method. The CCL method relies on the theory of approximate coverings both in feature space and data space. Also a new cluster validity index, similitude entropy (SE), is proposed. It can be used to evaluate the compactness and separation of clusters with information entropy theory. Simulations including the performance comparison between the proposed method and the conventional methods are presented. Results show that while maintaining the sorting accuracy, the proposed method can reduce the computing complexity effectively in sorting the signals.

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Acknowledgements

This paper was supported in part by the National Natural Science Foundation of China under the Grant nos. 61203268 and 61202339, by the National Defense Technology Keystone Laboratory Foundation, China under the Grant nos. 9140C610301080C6106 and 9140C6001070801, by the Aviation Science Foundation, China under the Grant nos. 20095596014 and 20101996009, and supported by the Shaanxi Natural Science Foundation of China under the Grant no. 2012JQ8034.

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Authors and Affiliations

  1. School of Aeronautics and Astronautics, Air Force Engineering University, No. 1 Baling Road, Baqiao District, Xi’an City, 710038, P.R. China

    Zhanling Wang, Dengfu Zhang, Duyan Bi & Shiqiang Wang

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  1. Zhanling Wang
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  2. Dengfu Zhang
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  3. Duyan Bi
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  4. Shiqiang Wang
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Correspondence to Shiqiang Wang.

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Wang, Z., Zhang, D., Bi, D. et al. Multiple-Parameter Radar Signal Sorting Using Support Vector Clustering and Similitude Entropy Index. Circuits Syst Signal Process 33, 1985–1996 (2014). https://doi.org/10.1007/s00034-013-9721-1

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  • DOI: https://doi.org/10.1007/s00034-013-9721-1

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