FDA-MIMO radar for DOD, DOA, and range estimation: SA-MCFO framework and RDMD algorithm

Abstract The frequency diverse array-multi-input multi-output (FDA-MIMO) radar can locate target in angle and range dimensions by transmitting little frequency offset across the transmit sensors. In this paper, a joint space-time-frequency domain optimization scheme is designed to estimate the direction of departure (DOD), direction of arrival (DOA) and range of target. We propose synthetic aperture-multi coprime frequency offset (SA-MCFO) framework which synthesizes all subarrays generated by array motion to expand array aperture and signal bandwidth. We also propose reduce dimension multiple signal classification with decoupling (RDMD) algorithm to detect target by combining reduce dimension (RD) transformation and subarray based estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which results in decoupling of DOD and range as well as fine estimation accuracy. The proposed SA-MCFO framwork enjoys remarkable system flexibility but with lower system cost. The proposed RDMD algorithm significantly reduce computational complexity but with ignorable performance degradation compared with the conventional 3D multiple signal classification (3D-MUSIC) algorithm. We also provide the Cramer-Rao Bounds (CRBs) of DOD, DOA and range as performance benchmark, and numerical simulations are conducted to verify the superiorities and effectiveness of the proposed SA-MCFO framework and RDMD algorithm.