Fundamental Trade-offs in Quantized Hybrid Radar Fusion: A CRB-Rate Perspective
Akhileswar Chowdary, Ahmad Bazzi, Vaibhav Kumar, Roberto Bomfin, and Marwa Chafii

TL;DR
This paper analyzes the fundamental trade-offs in quantized hybrid radar fusion systems, deriving bounds on sensing accuracy and communication rate to guide ADC design and system configuration.
Contribution
It introduces a finite-resolution quantized framework for HRF, deriving CRB and rate bounds to characterize the sensing-communication trade-off.
Findings
ADC resolution significantly impacts HRF performance.
Coarse quantization can sharply degrade sensing accuracy.
Guidelines for ADC design in HRF systems are provided.
Abstract
Hybrid radar fusion (HRF), which combines monostatic and bistatic sensing in a common spectrum, offers enhanced spatial diversity, but is particularly vulnerable to quantization error effects due to the large power imbalance between the direct and reflected uplink signals. Although finite-resolution analog-to-digital converters (ADCs) have been considered in the existing literature on integrated sensing and communication (ISAC), their role in HRF architectures has not yet been characterized. This paper develops a finite-resolution quantized sensing-communication framework for HRF systems by deriving a Cramer-Rao bound (CRB) and achievable uplink rate. Tight lower bounds on the Fisher information matrix and the communication rate are obtained, enabling a tractable characterization of finite-resolution quantized HRF. The fundamental sensing-communication trade-off is then characterized…
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Taxonomy
TopicsRadar Systems and Signal Processing
