Sparse self-calibration via iterative minimization against phase synchronization mismatch for MIMO radar imaging

We address the problem of three-dimensional (3-D) imaging for multiple-input multiple-output (MIMO) radar in the presence of phase synchronization mismatch between each transmitter-receiver pair. Although usually set to the default values (zero) in the popular practice, such inevitable errors often occur owing to imperfect knowledge of the local oscillators and could seriously deteriorate the imaging result. Hence in this paper, taking the sparse priori of target into account and motivated by the maximum likelihood estimation (MLE), we propose the sparse self-calibration method via iterative minimization (SSCIM) algorithm to provide better inversion performance against the phase synchronization mismatch at low signal-to-noise ratio (SNR), and finally we demonstrate the effectiveness of the proposed method through numerical simulations.