A Comparison of Direction of Arrival Estimation Performance for Phased-MIMO Systems

This work combines the Phased-Multiple-Input-Multiple-Output (PH-MIMO) array and Compressive Sensing (CS) concepts from the literature, for the first time, and investigates direction of arrival (DoA) estimation problem of multiple targets in a such radar system. Transmitter model incorporates a phased-MIMO array with the number of subarrays taken as a parameter, and considers classical beamforming and random phase weight design approaches while placing an average power restriction on each antenna element. Receiver model evaluates three different reconstruction methods, namely beamforming, individual CS and group CS, for DoA performance assessment of multiple targets. Parametric Monte Carlo simulations are conducted to quantify angle error variance per target for each system configuration at different signal-to-noise (SNR) ratios. Simulation results demonstrate that a joint use of PH-MIMO and CS techniques can boost DoA performance at low SNRs, and that group sparsity solution can outperform individual solutions in terms of angle estimation error by a factor of three.