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Support vector regression model for complex target RCS predicting

Support vector regression model for complex target RCS predicting
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摘要 The electromagnetic scattering computation has developed rapidly for many years; some computing problems for complex and coated targets cannot be solved by using the existing theory and computing models. A computing model based on data is established for making up the insufficiency of theoretic models. Based on the "support vector regression method", which is formulated on the principle of minimizing a structural risk, a data model to predicate the unknown radar cross section of some appointed targets is given. Comparison between the actual data and the results of this predicting model based on support vector regression method proved that the support vector regression method is workable and with a comparative precision. The electromagnetic scattering computation has developed rapidly for many years; some computing problems for complex and coated targets cannot be solved by using the existing theory and computing models. A computing model based on data is established for making up the insufficiency of theoretic models. Based on the "support vector regression method", which is formulated on the principle of minimizing a structural risk, a data model to predicate the unknown radar cross section of some appointed targets is given. Comparison between the actual data and the results of this predicting model based on support vector regression method proved that the support vector regression method is workable and with a comparative precision.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2009年第1期65-68,共4页 系统工程与电子技术(英文版)
关键词 radar cross section complex target coated target support vector regression. radar cross section, complex target, coated target, support vector regression.
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参考文献5

  • 1Chau Pham, Paul L Harton, Sunil K Simhal. Radar cross section measurements in space. Instrumentation and Measurement Technology Conference, IMTC/94. Conference Proceedings. l Oth Anniversary. Advanced Technologies in I & M, 1994: 44-47.
  • 2Steve R Gunn. Support vector machines for classification and regression. Technical Report, 1998: 29-42.
  • 3Alex J Smola, Bernhard Scholkopf. A tutorial on support vector regression. NeuroCOLT2 Technical Report Series, NC2-TR-1998-030.
  • 4Ruck G T, Barrick D E, Stuart W D,et al. Radar cross section handbook. New York: Plenum, 1970: 160-195.
  • 5Taylor D J, Jordan A K, Moser P J, et al. Complex resonances of conducting spheres with lossy coatings. IEEE Trans. on Antennas and Propagation, 1990, 28(2): 236- 240.

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