基于改进3D-ESPRIT算法的GTD模型参数估计与目标识别

doi:10.12305/j.issn.1001-506X.2021.02.07

Abstract

Abstract:

Aiming at the problem that the traditional three-dimensional estimating signal parameter via rotational invariance techniques (3D-ESPRIT) algorithm and quadratic-forward-backward 3D-ESPRIT (Q-FB-3D-ESPRIT) algorithm significantly reduce the estimation accuracy of geometric theory of diffraction (GTD) model parameters under the condition of low signal to noise ratio (SNR), an improved polarized-Q-FB-3D-ESPRIT (PQ-FB-3D-ESPRIT) algorithm is proposed. Compared with the above two traditional algorithms, the improved algorithm increases the use of target polarization information and effectively extends the length of available electromagnetic scattering data. The simulation results show that the parameter estimation accuracy of the improved algorithm is higher than that of the other two algorithms, especially in the case of low SNR. In addition, the radar target recognition based on scattering center model is studied, and the simulation results further verify the feasibility of the proposed algorithm.

Key words: parameter estimation, scattering center, geometric theory of diffraction (GTD) scattering center model, three-dimensional estimating signal parameter via rotational invariance techniques (3D-ESPRIT) algorithm, target recognition

CLC Number:

TN957

Jiahua XU, Xiaokuan ZHANG, Shuyu ZHENG, Binfeng ZONG, Shuchang ZHENG. GTD model parameter estimation and target recognition based on improved 3D-ESPRIT algorithm[J]. Systems Engineering and Electronics, 2021, 43(2): 336-342.

Figures/Tables 13

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算法名称	计算协方差矩阵
3D-ESPRIT算法	P²Q²L²(M－P+1)(N－Q+1)(K－L+1)
Q-FB-3D-ESPRIT算法	(3P²Q²L²+PQL)(M－P+1)(N－Q+1)(K－L+1)+P³Q³L³
PQ-FB-3D-ESPRIT算法	4[(3P²Q²L²+PQL)(M－P+1)(N－Q+1)(K－L+1)+P³Q³L³]

x_i/m	y_i/m	z_i/m	散射类型α_i	散射强度A_i
0.81	1.10	1.13	1.000	4.000
1.24	1.28	1.27	0.500	3.000
1.63	1.80	1.62	0	2.000
1.82	2.50	1.87	-1.000	1.000

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GTD model parameter estimation and target recognition based on improved 3D-ESPRIT algorithm

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