Abstract
Forward-looking imaging systems are mainly divided into phased-array (PA) radar and multiple-input-multiple-output (MIMO) radar according to whether the transmitted signals are coherent or not. Since PA radar can improve the signal-to-noise ratio (SNR) through beamforming, while MIMO radar can achieve higher spatial resolution through channel separation at the receiver. In this paper, the noise-robustness and super-resolution performance of the two systems are analyzed. A fair comparison is conducted under the equal conditions, including algorithm, hardware, etc. We use a half-wavelength uniform array to transmit linear frequency modulation (LFM) signals for PA radar and orthogonal signals for MIMO radar. We first establishes signal models of PA system and MIMO system respectively, where the sparse Bayesian learning algorithm is used for the scene imaging. The simulation results show that the imaging quality of phased array radar is better than that of MIMO radar under low SNR, but worse than MIMO radar under high SNR, which shows that the PA radar is more suitable for imaging under low SNR, while MIMO radar is better under high SNR.
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