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arXiv · 2411.03206

Indoor Statistical and Deterministic RCS Characterization for ISAC Channel Modeling

Ali Waqar Azim·Ahmad Bazzi·Roberto Bomfin·Nikolaos Giakoumidis·Theodore S. Rappaport·Marwa Chafii
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Abstract

In this study, we perform statistical radar cross section (RCS) analysis for various test targets in an indoor factory at \SI{25}{}-\SI{28}{\GHz}, with the goal of determining the best-fit parametric distributions that characterize the target scattering properties to be used in integrated sensing and communication channel modeling standardization. The analysis is conducted based on measurements in quasi-monostatic and bistatic configurations with bistatic angles of \(20^\circ\), \(40^\circ\), and \(60^\circ\). The test targets include unmanned aerial vehicles, an autonomous mobile robot, and a robotic arm. Goodness-of-fit tests validate that the RCS of these targets is best modeled by \textit{lognormal} and \textit{gamma} distributions with high statistical confidence. Additionally, we provide a framework for evaluating the \ac{NF}, specular-dominant effective bistatic RCS of a rectangular sheet under controlled bistatic geometries. Novel deterministic RCS models are evaluated, incorporating dependencies on the bistatic angle, transmitter-target separation (\SIrange{2}{10}{\meter}). The results demonstrate that some proposed deterministic RCS models accurately fit the measured data, highlighting their applicability in deterministic RCS characterization in NF bistatic configurations.

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Ali Waqar Azim, Ahmad Bazzi, Roberto Bomfin, Nikolaos Giakoumidis, Theodore S. Rappaport, Marwa Chafii. 2024-11-05. Indoor Statistical and Deterministic RCS Characterization for ISAC Channel Modeling. https://arxiv.org/abs/2411.03206

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