Gridless Parameter Estimation for One-Bit MIMO Radar With Time-Varying Thresholds

• Published in: IEEE transactions on signal processing Vol. 68; pp. 1048 - 1063
• Main Authors: Xi, Feng, Xiang, Yijian, Chen, Shengyao, Nehorai, Arye
• Format: Journal Article
• Language: English
• Published: New York IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 1-bit sampling; ADMM; atomic norm; Domains; Doppler effect; Doppler radar; Energy consumption; Iterative methods; low-rank matrix recovery; MIMO radar; off-grid; Parameter estimation; Quantization (signal); Radar; Receiving antennas; Sampling
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2020.2970343

We investigate the one-bit MIMO (1b-MIMO) radar that performs one-bit sampling with a time-varying threshold in the temporal domain and employs compressive sensing in the spatial and Doppler domains. The goals are to significantly reduce the hardware cost, energy consumption, and amount of stored data. The joint angle and Doppler frequency estimations from noisy onebit data are studied. By showing that the effect of noise on one-bit sampling is equivalent to that of sparse impulsive perturbations, we formulate the one-bit ℓ 1 -regularized atomic-norm minimization (1b-ANM-L1) problem to achieve gridless parameter estimation with high accuracy. We also develop an iterative method for solving the 1b-ANM-L1 problem via the alternating direction method of multipliers. The Cramér-Rao bound (CRB) of the 1b-MIMO radar is analyzed, and the analytical performance of one-bit sampling with two different threshold strategies is discussed. Numerical experiments are presented to show that the 1b-MIMO radar can achieve high-resolution parameter estimation with a largely reduced amount of data.