A Super-Resolution Sparse Aperture ISAR Sensors Imaging Algorithm via the MUSIC Technique

The conventional range-Doppler (RD) technique uses fast Fourier transformation (FFT) to generate focused images. However, the spectrum of FFT has high sidelobes and wide main lobes and the resolution of RD is limited by the radar parameters so that the RD method cannot generate super-resolution images especially with sparse aperture (SA) data. A super-resolution SA inverse synthetic aperture radar (SA-ISAR) imaging algorithm via the multiple signal classification (MUSIC) technique is proposed in this paper. The proposal uses the MUSIC algorithm to estimate the location and employs the least-squares technique to calculate the intensity of each scatterer. Then, the scatterers can be precisely depicted in the images without the interference of sidelobes and wide main lobes. The resolution of the proposal depends less on the radar parameters, and it can be further improved by using a smaller search step. Experiments obtained by processing of simulated and raw data demonstrate that the proposal can efficiently generate super-resolution images with full aperture (FA) or SA data.