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Volume 42 Issue 1
Jan.  2020
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Cheng HU, Linlin FANG, Rui WANG, Chao ZHOU, Weidong LI, Fan ZHANG, Tianjiao LANG, Teng LONG. Analysis of Insect RCS Characteristics[J]. Journal of Electronics & Information Technology, 2020, 42(1): 140-153. doi: 10.11999/JEIT190611
Citation: Cheng HU, Linlin FANG, Rui WANG, Chao ZHOU, Weidong LI, Fan ZHANG, Tianjiao LANG, Teng LONG. Analysis of Insect RCS Characteristics[J]. Journal of Electronics & Information Technology, 2020, 42(1): 140-153. doi: 10.11999/JEIT190611

Analysis of Insect RCS Characteristics

doi: 10.11999/JEIT190611
Funds:  The Special Fund for Research on National Major Research Instruments (31727901)
  • Received Date: 2019-08-12
  • Rev Recd Date: 2019-11-22
  • Available Online: 2019-11-30
  • Publish Date: 2020-01-21
  • Insect radar is the most effective tool for insect migration observation. In order to realize target recognition of insect radar, it is important to study the RCS characteristics of insects. This paper will analyze the static and dynamic Radar Cross Section (RCS) characteristics of insects. Firstly, based on the measured X-band fully-polarimetric RCS data, the static RCS characteristics of insects are analyzed, including the variations of horizontal and vertical polarization RCS with body weight respectively, and the variation of insect polarization pattern with body weight. Secondly, the dielectrics and geometric models currently used to study the RCS characteristics of insects are summarized by electromagnetic simulation. Twelve dielectric models consisting of four dielectrics (including water, spinal cord, dry skin, and chitin and hemolymph mixture) and three geometric models (including equivalent size prolate spheroid, equivalent mass prolate spheroid and triaxial prolate spheroid) are compared, and it be found that the RCS characteristics of equivalent mass prolate spheroid are closest to that of the real insects. Then, the fluctuation characteristics of insect dynamic RCS are analyzed based on the insect echo data measured in field by a Ku-band high-resolution insect radar. The measured insect dynamic RCS fluctuation data are fitted with four classical RCS fluctuation distribution  models (χ2, Log-normal, Weibull and Gamma distribution), respectively. It can be seen from the least square error of fitting and goodness of fit test that Gamma distribution gives the best description of the statistical characteristics of insect RCS fluctuations. Finally, the application of insect RCS characteristics to insect orientation, mass and body length measurements for insect radars is summarized.

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