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 geo...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-meansquare-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 3DESPRIT algorithm.展开更多
This resolution 5 (25−1 factorial) study aimed to ascertain an understanding of the interactions between different geometries on the resulting Radar Cross Section (RCS) of a target. The results of the study are in lin...This resolution 5 (25−1 factorial) study aimed to ascertain an understanding of the interactions between different geometries on the resulting Radar Cross Section (RCS) of a target. The results of the study are in line with the general understanding of the impact different geometries have on RCS but show that geometries can also influence the variance of measured RCS, and typical attributes that reduce RCS increase the variance of the measured RCS. Notably, an increased angle between the front face of a plate and the direction of the radar signal decreased RCS but increased the variance of the RCS measured.展开更多
Taking into account the influences of scatterer geometrical shapes on induced currents, an algorithm, termed the sparse-matrix method （SMM）, is proposed to calculate radar cross section （RCS） of aircraft configura...Taking into account the influences of scatterer geometrical shapes on induced currents, an algorithm, termed the sparse-matrix method （SMM）, is proposed to calculate radar cross section （RCS） of aircraft configuration. Based on the geometrical characteristics and the method of moment （MOM）, the SMM points out that the strong current coupling zone could be predefined according to the shape of scatterers. Two geometrical parameters, the surface curvature and the electrical space between the field position and source position, are deducted to distinguish the dominant current coupling. Then the strong current coupling is computed to construct an impedance matrix having sparse nature, which is solved to compute RCS. The efficiency and feasibility of the SMM are demonstrated by computing electromagnetic scattering of some kinds of shapes such as a cone-sphere with a gap, a bi-arc column and a stealth aircraft configuration. The numerical results show that： （1） the accuracy of SMM is satisfied, as compared with MOM, and the computational time it spends is only about 8% of the MOM; （2） with the electrical space considered, making another allowance for the surface curvature can reduce the computation time by 9.5%.展开更多
基金This work was supported by the National Natural Science Foundation of China(61372033).
文摘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-meansquare-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 3DESPRIT algorithm.
文摘This resolution 5 (25−1 factorial) study aimed to ascertain an understanding of the interactions between different geometries on the resulting Radar Cross Section (RCS) of a target. The results of the study are in line with the general understanding of the impact different geometries have on RCS but show that geometries can also influence the variance of measured RCS, and typical attributes that reduce RCS increase the variance of the measured RCS. Notably, an increased angle between the front face of a plate and the direction of the radar signal decreased RCS but increased the variance of the RCS measured.
基金National Natural Science Foundation of China (90205020)
文摘Taking into account the influences of scatterer geometrical shapes on induced currents, an algorithm, termed the sparse-matrix method （SMM）, is proposed to calculate radar cross section （RCS） of aircraft configuration. Based on the geometrical characteristics and the method of moment （MOM）, the SMM points out that the strong current coupling zone could be predefined according to the shape of scatterers. Two geometrical parameters, the surface curvature and the electrical space between the field position and source position, are deducted to distinguish the dominant current coupling. Then the strong current coupling is computed to construct an impedance matrix having sparse nature, which is solved to compute RCS. The efficiency and feasibility of the SMM are demonstrated by computing electromagnetic scattering of some kinds of shapes such as a cone-sphere with a gap, a bi-arc column and a stealth aircraft configuration. The numerical results show that： （1） the accuracy of SMM is satisfied, as compared with MOM, and the computational time it spends is only about 8% of the MOM; （2） with the electrical space considered, making another allowance for the surface curvature can reduce the computation time by 9.5%.
