Abstract
Monitoring lower airspace over critical infrastructure using cellular signals of opportunity is highly practical because transmitters are pre-deployed, licensed, and continuously active. Digital twins can evaluate the feasibility of such integrated sensing and communication (ISAC) architectures, but their predictive accuracy must be validated against real-world data. This paper reports validation results for TiamiTwin, a digital twin developed for bistatic ISAC drone sensing, using empirical measurements from an operational 5G deployment featuring a commercial band n41 gNB and a receiver separated by 572.8 m over a non-line-of-sight (NLOS) channel. TiamiTwin incorporates three parallel channel representations evaluated on a 240-subcarrier grid: the 3GPP TR 38.901 (Release 19) bistatic ISAC model, a ray-traced site model, and the captured field measurements. Empirical results demonstrate that both statistical and ray-tracing models under-predict the measured root-mean-square (RMS) delay spread by approximately a factor of three. Furthermore, target reflections sit 68 dB below static clutter in power, making target detection entirely dependent on Doppler separation to isolate the drone from zero-Doppler background returns. Despite this severe clutter environment, the target remains separable along 88% of the flight path in the delay, Doppler, or joint delay-Doppler domains.
BibTeX
@misc{zafari2026tiamitwin,
author = {Zafari, Mehdi and Enayati, Saeede and Swindlehurst, A. Lee and Mukherjee, Amitav},
title = {{TiamiTwin}: A Digital Twin for Bistatic {ISAC} Drone Sensing, Validated Against Measurements},
year = {2026},
eprint = {2609.22709},
archivePrefix = {arXiv},
primaryClass = {eess.SP},
url = {https://arxiv.org/abs/2609.22709}
}