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Indoor Statistical and Deterministic RCS Characterization for ISAC Channel Modeling
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DOI：10.1109/twc.2026.3718356.png)
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Abstract
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In this study, we perform statistical radar cross section (RCS) analysis for various test targets in an indoor factory at 25-28 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°, 40°, and 60°. 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 lognormal and gamma distributions with high statistical confidence. Additionally, we provide a framework for evaluating the near-field (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 (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathrm {2~\text {m}}~\text {to}~\mathrm {10~\text {m}}$ </tex-math></inline-formula>). 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.
Keywords:
Radar cross section
bistatic
integrated sensing and communications
indoor factory
indoor hotspot
Journal
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10.7
Papers:
1.3W
Citations:
5.3W
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