High-resolution Sparse Self-calibration Imaging for Vortex Radar with Phase Error - Haiyou QU; Di CHENG; Chang CHEN; Weidong CHEN (Leida xuebao, 2021)
The Orbital Angular Momentum (OAM)-based vortex radar has drawn increasing attention because of its potential for high-resolution imaging. The vortex radar high resolution imaging with limited OAM modes is commonly solved by sparse recovery, in which the prior knowledge of the imaging model needs to be known precisely. However, the inevitable phase error in the system results in imaging model mismatch and deteriorates the imaging performance considerably. To address this problem, the vortex radar imaging model with phase error is established for the first time in this work. Meanwhile, a two-step self-calibration imaging method for vortex radar is proposed to directly estimate the phase error. In the first step, a sparsity-driven algorithm is developed to promote sparsity and improve imaging performance. In the second step, a self-calibration operation is performed to directly compensate for the phase error. By alternately reconstructing the targets and estimating the phase error, the proposed method can reconstruct the target with high imaging quality and effectively compensate for the phase error. Simulation results demonstrate the advantages of the proposed method in enhancing the imaging quality and improving the phase error estimation performance.