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

TL;DR

This paper analyzes the detection performance of one-bit ADC/DAC MIMO radar systems at low SNR/INR, derives theoretical detection probabilities, and proposes a joint waveform and filter design algorithm to optimize radar performance.

Contribution

It provides the first theoretical analysis of detection probabilities for one-bit MIMO radar and introduces GREET, a novel joint design algorithm for waveform and filter optimization.

Findings

Derived detection probability expressions for one-bit MIMO radar.

Quantified performance gap compared to infinite-bit systems.

Proposed GREET algorithm improves QSINR and detection performance.

Abstract

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 ($\mathcal{P}_d$) and probability of false alarm ($\mathcal{P}_f$) 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 $\mathcal{P}_f$, $\mathcal{P}_d$ 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\emph{g} wavefo\emph{r}m and filt\emph{e}r d\emph{e}sign for QSINR maximiza\emph{t}ion (GREET). At each iteration of GREET, the receive filter is upadted via the minimum variance distortionless response (MVDR) method, and the one-bit waveform is optimized based on the alternating direction method of multipliers (ADMM) algorithm where the closed-form solutions are obtained for both the primary and slack variables. Numerical simulations are consistent to the theoretical performance analysis and demonstrate the effectiveness of the proposed design algorithm.