The noise robustness and parameter estimation performance of the classical three-dimensional estimating signal parameter via rotational invariance techniques (3D-ESPRIT) algorithm are poor when the parameters of the geometric theory of the diffraction (GTD) model are estimated at low signal-to-noise ratio (SNR). To solve this problem, a modified 3D-ESPRIT algorithm is proposed. The modified algorithm improves the parameter estimation accuracy by proposing a novel spatial smoothing technique. Firstly, we make cross-correlation of the auto-correlation matrices; then by averaging the cross-correlation matrices of the forward and backward spatial smoothing, we can obtain a novel equivalent spatial smoothing matrix. The formula of the modified algorithm is derived and the performance of this improved method is also analyzed. Then we compare root-mean-square-errors (RMSEs) of different parameters and the locating accuracy obtained by different algorithms. Furthermore, radar cross section (RCS) of radar targets is extrapolated. Simulation results verify the effectiveness and superiority of the modified 3D-ESPRIT algorithm.

中文翻译：

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基于改进的3D-ESPRIT算法的GTD模型参数估计和RCS外推

当在低信噪比下估计衍射（GTD）模型的几何理论参数时，通过旋转不变技术（3D-ESPRIT）算法的经典三维估计信号参数的噪声鲁棒性和参数估计性能较差。噪声比（SNR）。为了解决这个问题，提出了一种改进的3D-ESPRIT算法。通过提出一种新颖的空间平滑技术，改进的算法提高了参数估计的准确性。首先，我们对自相关矩阵进行互相关；然后，通过对前向和后向空间平滑的互相关矩阵求平均，可以得到一个新颖的等效空间平滑矩阵。推导了改进算法的公式，并分析了该改进方法的性能。然后，我们比较了不同参数的均方根误差（RMSE）和通过不同算法获得的定位精度。此外，外推雷达目标的雷达截面（RCS）。仿真结果验证了改进后的3D-ESPRIT算法的有效性和优越性。