标题： 量化混合雷达融合中的基本权衡：CRB-速率视角 显示英文标题

标题： Fundamental Trade-offs in Quantized Hybrid Radar Fusion: A CRB-Rate Perspective

摘要： 尽管最近的进展强调了低分辨率模数转换器(ADC)在集成感知和通信(ISAC)系统中的作用，但ADC分辨率对混合雷达融合(HRF)的具体影响，其中我们融合单基地和双基地感知系统，仍然相对未被探索。HRF中的上行链路(UL)路径，包括同一频段内的直接信号和反射信号，带来了独特的挑战，特别是由于反射信号通常比直接路径弱得多，使得HRF系统容易受到ADC分辨率的影响。为了研究量化和ADC分辨率对HRF的影响，我们采用量化Cramér-Rao界(CRB)作为感知精度的度量。本工作专门推导了HRF系统的量化CRB和量化通信速率。我们将分析扩展到获得Fisher信息矩阵(FIM)和UL通信速率的下限，我们用这些来表征量化HRF系统。利用这些推导出的界限，我们通过CRB-速率边界的角度分析量化HRF系统。我们通过两个优化问题获得CRB-速率边界，其中每个解点代表感知精度和通信速率之间的权衡边界。大量仿真说明了ADC分辨率、动态范围(DR)和各种系统参数对HRF系统CRB-速率边界的影响。这些结果为高效和高性能HRF系统的设计提供了关键见解。 显示英文摘要

摘要： While recent advancements have highlighted the role of low-resolution analog-to-digital converters (ADCs) in integrated sensing and communication (ISAC) systems, the specific impact of ADC resolution on hybrid radar fusion (HRF), where we fuse monostatic and bistatic sensing systems remains relatively unexplored. The uplink (UL) paths in HRF, comprising both direct and reflected signals within the same frequency band, pose unique challenges, particularly given that the reflected signal is often significantly weaker than the direct path, making HRF systems susceptible to ADC resolution. To investigate the influence of quantization and ADC resolution on HRF, we employ the quantized Cram\'er-Rao bound (CRB) as a metric for sensing accuracy. This work derives the quantized CRB specifically for HRF systems and the quantized communication rate. We extend our analysis to obtain lower bounds on the Fisher Information Matrix (FIM) and UL communication rate, which we use to characterize quantized HRF systems. Using these derived bounds, we analyze the quantized HRF system through the lens of CRB-rate boundaries. We obtain the CRB-rate boundary through two optimization problems, where each solution point represents a trade-off boundary between the sensing accuracy and the communication rate. Extensive simulations illustrate the influence of ADC resolution, dynamic range (DR), and various system parameters on the CRB-rate boundary of HRF systems. These results offer critical insights into the design of efficient and high-performance HRF systems.