Systems Engineering and Electronics ›› 2020, Vol. 42 ›› Issue (1): 76-82.doi: 10.3969/j.issn.1001-506X.2020.01.11

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Extraction of scattering center parameters and reconstruction of RCS based on improved MUSIC algorithm

Shuyu ZHENG1(), Xiaokuan ZHANG2(), Binfeng ZONG2()   

  1. 1. The Graduate School, Air Force Engineering University, Xi'an 710051, China
    2. Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China
  • Received:2019-07-11 Online:2020-01-01 Published:2019-12-23
  • Supported by:
    国家自然科学基金(61372033);目标与环境电磁散射重点实验室创新基金(STES2014-2)

Abstract:

With the development of stealth technology, radar target edge diffraction gradually replaces mirror diffraction as the main scattering source. Therefore, the description of stealth targets based on the geometric theory of diffraction (GTD) scattering center model is more accurate than the damped exponential model. It is very important to accurately estimate the GTD scattering center parameters to characterize the scattering characteristics of the target. Aiming at the problem that the classical multiple signal classification (MUSIC) algorithm only uses the original echo data of the target and the accuracy of parameter estimation is not very high, an improved MUSIC algorithm is proposed to extract the scattering center parameters. By taking conjugate of original echo data, the improved MUSIC algorithm constructs a new total conjugate matrix, and makes effective use of conjugate information of target original echo data. Simulation results show that compared with the classical MUSIC algorithm, the improved MUSIC algorithm has a higher parameter estimation accuracy, better radar cross section (RCS) reconstruction fitting degree and little computational increase, which can effectively extract the scattering centers of stealth targets.

Key words: scattering center, geometric theory of diffraction (GTD), improved multiple signal classification (MUSIC) algorithm, conjugate matrix, radar cross section (RCS) reconstruction

CLC Number: 

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