Parameter estimation of GTD model and RCS extrapolation based on a modified 3D-ESPRIT algorithm

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The noise robustness and parameter estimation per-formance of the classical three-dimensional estimating signal parameter via rotational invariance techniques (3D-ESPRIT) al-gorithm 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 al-gorithm is proposed.The modified algorithm improves the para-meter estimation accuracy by proposing a novel spatial smooth-ing technique.Firstly,we make cross-correlation of the auto-cor-relation 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.
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