One-Bit ADCs/DACs Based MIMO Radar: Performance Analysis and Joint Design

• Published in: IEEE transactions on signal processing Vol. 70; pp. 2609 - 2624
• Main Authors: Deng, Minglong, Cheng, Ziyang, Wu, Linlong, Shankar, Bhavani, He, Zishu
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Analog to digital converters; Antenna arrays; Design analysis; Digital to analog converters; False alarms; Interference; Iterative methods; joint design of transmit waveform and receive filter; MIMO communication; MIMO radar; Noise; one-bit ADCs/DACs; Optimization; Power consumption; QSINR; Radar; Radar antennas; Receiving antennas; Signal to noise ratio; target detection; Waveforms
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2022.3176953

Extremely low-resolution (e.g. one-bit) analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) can substantially reduce hardware cost and power consumption for MIMO radar especially with large scale antennas. In this paper, we focus on the detection performance analysis and joint design for the MIMO radar with one-bit ADCs and DACs. Specifically, under the assumption of low signal-to-noise ratio (SNR) and interference-to-noise ratio (INR), we derive the expressions of probability of detection (<inline-formula><tex-math notation="LaTeX">\mathcal {P}_{d}</tex-math></inline-formula>) and probability of false alarm (<inline-formula><tex-math notation="LaTeX">\mathcal {P}_{f}</tex-math></inline-formula>) for one-bit MIMO radar and also the theoretical performance gap to infinite-bit MIMO radars for the noise-only case. We further find that for a fixed <inline-formula><tex-math notation="LaTeX">\mathcal {P}_{f}</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">\mathcal {P}_{d}</tex-math></inline-formula> depends on the defined quantized signal-to-interference-plus-noise ratio (QSINR), which is a function of the transmit waveform and receive filter. Thus, an optimization problem arises naturally to maximize the QSINR by joint designing the waveform and filter. For the formulated problem, we propose an alternatin g wavefo r m and filt e r d e sign for QSINR maximiza t ion (GREET). At each iteration of GREET, the optimal receive filter is updated via the minimum variance distortionless response (MVDR) method, and due to the difficulty in global optimality, an alternating direction method of multipliers (ADMM) based algorithm is devised to efficiently find a high-quality suboptimal one-bit waveform. Numerical simulations are consistent to the theoretical performance analysis and demonstrate the effectiveness of the proposed design algorithm.