| Citation: | ZHENG Shuyu, ZHANG Xiaokuan, GUO Yiduo, et al. Parameter estimation of 1D GTD scattering center model based on an improved MUSIC algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(11): 2149-2155. doi: 10.13700/j.bh.1001-5965.2019.0576(in Chinese)
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The noise robustness and parameter accuracy are poor when the classical Multiple Signal Classification (MUSIC) algorithm is used to estimate parameters of the one-dimensional Geometric Theory of Diffraction (GTD) scattering center model. To solve this problem, a series of improved MUSIC algorithms are proposed in this paper. Firstly, the improved algorithms construct the conjugate matrixof the original back-scattered data, which utilizes the information of the original data more effectively. Secondly, by averaging the covariance matrix of the original scattering data and its conjugated data, a novel total covariance matrix can be obtained. Finally, quadratic, quartic and other even power are performed on the matrix to obtain another matrix, and thus it can broaden the differences between the eigenvalues of noises and signals, which is equivalent to increasing the signal-to-noise ratio. Simulation results show that the parameter estimation performance and noise robustness are better than those of the classical MUSIC algorithm.
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