High-resolution ISAR imaging of maneuvering targets based on sparse reconstruction

Abstract

Traditional range-instantaneous Doppler (RID) imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. In this paper, a novel ISAR imaging method of maneuvering targets based on sparse reconstruction is proposed, which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. The proposed method exploits the sparse spatial feature of target scene to characterize the sparsity of the echo signal in its time–frequency domain, constructs the instantaneous Fourier-transform-based dictionary that can reflect the time-varying Doppler frequency and then transforms RID imaging into the problem of sparse reconstruction. After discriminating noise range cells from the range cells containing signal components, noise range cells are used for noise level estimation and signal range cells are used for signal reconstruction. Furthermore, the iteration weighted strategy for ISAR image generation is applied to enhance the signal components and suppress noise. Both simulated and real data experiments are performed to evaluate the proposed method, and the experimental results are presented to demonstrate the superiority of the proposed method over traditional imaging methods.