Radar Target Recognition Algorithm Based on RCS Observation Sequence -- Set-Valued Identification Method

This paper studies the problem of radar target recognition based on radar cross section （RCS） observation sequence. First, the authors compute the discrete wavelet transform of RCS ob- servation sequence and extract a valid statistical feature vector containing five components. These five components...

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Bibliographic Details
Published inJournal of systems science and complexity Vol. 29; no. 3; pp. 573 - 588
Main Authors Wang, Ting, Bi, Wenjian, Zhao, Yanlong, Xue, Wenchao
Format Journal Article
LanguageEnglish
Published Beijing Academy of Mathematics and Systems Science, Chinese Academy of Sciences 01.06.2016
Subjects
Complex Systems
Control
Mathematics
Mathematics and Statistics
Mathematics of Computing
Operations Research/Decision Theory
Statistics
Systems Theory
Feature extraction
RCS
set-valued identification
radar target recognition
wavelet transform
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Summary:This paper studies the problem of radar target recognition based on radar cross section （RCS） observation sequence. First, the authors compute the discrete wavelet transform of RCS ob- servation sequence and extract a valid statistical feature vector containing five components. These five components represent five different features of the radar target. Second, the authors establish a set-valued model to represent the relation between the feature vector and the authenticity of the radar target. By set-valued identification method, the authors can estimate the system parameter, based on which the recognition criteria is given. In order to illustrate the efficiency of the proposed recognition method, extensive simulations are given finally assuming that the true target is a cone frustum and the RCS of the false target is normally distributed. The results show that the set-valued identification method has a higher recognition rate than the traditional fuzzy classification method and evidential reasoning method.
Bibliography:Feature extraction, radar target recognition, RCS, set-valued identification, wavelet transform.
11-4543/O1
This paper studies the problem of radar target recognition based on radar cross section （RCS） observation sequence. First, the authors compute the discrete wavelet transform of RCS ob- servation sequence and extract a valid statistical feature vector containing five components. These five components represent five different features of the radar target. Second, the authors establish a set-valued model to represent the relation between the feature vector and the authenticity of the radar target. By set-valued identification method, the authors can estimate the system parameter, based on which the recognition criteria is given. In order to illustrate the efficiency of the proposed recognition method, extensive simulations are given finally assuming that the true target is a cone frustum and the RCS of the false target is normally distributed. The results show that the set-valued identification method has a higher recognition rate than the traditional fuzzy classification method and evidential reasoning method.
ISSN:1009-6124
1559-7067
DOI:10.1007/s11424-015-4151-8