Moving Target's HRRP Synthesis With Sparse Frequency-Stepped Chirp Signal via Atomic Norm Minimization

Abstract

Compressive sensing (CS) has been introduced into inverse synthetic aperture radar (ISAR) imaging with partial measurements. However, in the case of transmitting sparse frequency-stepped chirp signal (FSCS), the CS-based method will produce an irregular range cell migration (IRCM) problem in the recovered high-resolution range profiles (HRRPs). The IRCM is induced by the basis mismatch problem in CS, and it will degrade the ISAR image. To obviate the IRCM, an atomic norm minimization (ANM) method is proposed in this letter. By reformulating the ANM as a semidefinite program (SDP), the echo with full FSCS can be recovered using off-the-shelf SDP solvers. Thus, HRRPs without IRCM can be achieved via the conventional inverse fast Fourier transform. As a result, an improved ISAR image will be obtained. Real data results demonstrate the advantages of the proposed method over the CS-based and matrix completion-based methods.