Application of RELAX Algorithm to ISAR Superresolution Imaging

Abstract

Superresolution array processing methods have been applied to inverse synthetic aperture radar (ISAR) imaging in order to enhance the resolution for many years. Nevertheless, because the excellent performances of the methods are based on the accurate knowledge of the data model, the performance of superresolution methods is degraded extremely, when the signal-to-noise-ratio is not very high, and the number of snapshots is not very large or the system errors exist in the array. This drawback prevents greatly their applications in practical systems. So, the study of robust processing methods is main subject at present. The relaxation (RELAX) algorithm can relax the hypothesis of the additive noise and the system errors. The application of the RELAX algorithm in ISAR imaging is presented in this paper. The RELAX algorithm can yield more accurate spectral estimates than the fast Fourier transform (FFT) or estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. Therefore, the higher resolution can be obtained by using the RELAX algorithm instead of the FFT or ESPRIT algorithm when the target flies smoothly. The simulation results show the effectiveness of RELAX algorithm.