基于改进3D-ESPRIT算法的三维GTD模型参数估计

Parameter Estimation of the 3D-GTD Model Based on a Modified 3D-ESPRIT Algorithm

三维旋转不变子空间(3D-ESPRIT)算法估计三维几何绕射理论(GTD)的散射中心模型时,参数精度不高,噪声鲁棒性较差,为此,提出一种改进的3D-ESPRIT算法.通过构建原始回波数据的共轭矩阵、对协方差矩阵叠加、取平均、平方处理,可提高对目标原始回波数据的利用率,并增大信号特征值与噪声特征值之间的差距,增大了信噪比,从而提高参数的估计精度.基于不同算法估计得到的三维GTD模型参数,比较了不同算法估计的参数均方差.仿真结果表明,改进算法的参数估计性能及噪声鲁棒性均优于经典3D-ESPRIT算法和改进的免配对3D-ESPRIT算法.

The noise robustness and parameter estimation performance of the classical three-dimensional estimating signal parameter via rotational invariance techniques( 3 D-ESPRIT) algorithm are poor when estimating parameters of the three dimensional geometric theory of diffraction( 3 D-GTD) model at low signal-to-noise ratio( SNR). To solve this problem,a modified algorithm is proposed. The modified algorithm improves the parameter estimation accuracy by constructing conjugated matrix of the original backscattered data,averaging the covariance matrices and performing quadratic power on the total covariance matrix to get another novel covariance matrix. The modified algorithm can broaden the differences between the eigenvalues of noises and signals,which is equivalent to increase SNR. Based on the parameters estimated by different algorithms,root-mean-square-errors of different parameters can be compared.Simulations verify that the parameter estimation performance and noise robustness of the modified algorithm are better than the classical 3 D-ESPRIT algorithm and the improved algorithm without pair.