Segment Noncoherent Integration Based Inverse Synthetic Aperture Radar Imaging under Low Signal-to-Noise Ratio

In this paper, a novel scheme for inverse synthetic aperture radar (ISAR) imaging under low signal-to-noise ratio (SNR) condition is proposed. The method is a preprocess of the high-resolution range profiles and relies on the oversampling in the azimuth direction. It divides the entire coherent processing interval into segments according to the down sampling factor. In each segment, original low SNR echoes are noncoherently integrated to obtain a new high SNR echo. With the new high SNR echoes, conventional methods for ISAR imaging can perform much better and obtain a better focused ISAR image. The presented algorithm has the advantage of effectiveness under low SNR condition and computational efficiency. Experimental results based on both the simulated and real radar data of an airplane verify the superiority of the proposed strategy.