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

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.

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