Matched Filtering Performance Analysis for Massive MIMO Radar with One-Bit Quantization

Minglong Deng, Haoqi Wu, Ziyang Cheng, Jiaheng Wang, Zishu He
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Abstract

In this paper, we investigate the performance of matched filtering (MF) for massive MIMO radar with one-bit ADCs. Firstly, we show that in the context of white Gaussian noise, the MF output of one-bit quantized received signals of mas-sive MIMO radar is asymptotically Gaussian. Then, statistical characteristics, including mean and covariance matrix, of the MF output are derived, respectively. More importantly, using the fact that massive MIMO radar has a large number of measurements (i.e., the number of samples in space/frequency/time domains), we provide approximate probabilistic distribution of the MF output, which is capable of making the signal processing algorithms of one-bit MIMO radar low in complexity. Moreover, based on the above approximations, the performance gap between one-bit and traditional infinite-bit MIMO radars is mathematically derived. Finally, from the perspective of target detection and beamforming, representative simulations are conducted to demonstrate the performance of massive MIMO radar with one-bit ADCs.
一比特量化大规模MIMO雷达匹配滤波性能分析
本文研究了具有1位adc的大规模MIMO雷达的匹配滤波(MF)性能。首先,我们证明了在高斯白噪声背景下,大规模MIMO雷达的1位量化接收信号的中频输出是渐近高斯的。然后,分别导出了MF输出的统计特征,包括均值和协方差矩阵。更重要的是,利用大规模MIMO雷达具有大量测量(即空间/频率/时间域的样本数量)的事实,我们提供了MF输出的近似概率分布,这能够使1位MIMO雷达的信号处理算法具有较低的复杂性。此外,基于上述近似,数学推导了1位和传统无限位MIMO雷达之间的性能差距。最后,从目标检测和波束形成的角度,进行了有代表性的仿真,验证了采用1位adc的大规模MIMO雷达的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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