Enhancing Situational Awareness in ISAC Networks via Drone Swarms: A Real-World Channel Sounding Data Set

TL;DR

This paper introduces a real-world dataset from drone swarm-based sensing in ISAC networks, enabling improved situational awareness through multi-static radar measurements in diverse environments.

Contribution

It provides a publicly available channel sounding data set from synchronized drone and ground sensors for real-world ISAC applications, which is novel for multi-static radar research.

Findings

Demonstrated drone swarm capabilities for air-to-air and air-to-ground radar tracking.

Collected data supports development of real-world ISAC algorithms.

Showcased potential for enhanced situational awareness in 6G networks.

Abstract

With the upcoming capabilities of integrated sensing and communication (ISAC) and the incorporation of user equipment (UE) like unmanned aerial vehicles (UAVs) in 6G mobile networks, there is a significant opportunity to enhance situational awareness through multi-static radar sensing in meshed ISAC networks. This paper presents a real-world channel sounding data set acquired using a testbed with synchronized, distributed ground-based sensor nodes and flying sensor nodes within a swarm of up to four drones. The conducted measurement campaign is designed to sense the bi-static reflectivity of objects such as parking cars, vertical take-off and landing (VTOL) aircraft, and small drones in multi-path environments. We detail the rationale behind the selection of the included scenarios and the configuration of the participating nodesand present exemplary results to demonstrate the potential of using collaborating drone swarms for multi-static radar tracking and localization in air-to-air (A2A) and air-to-ground (A2G) scenarios. The data sets are publicly available to support the development and validation of future ISAC algorithms in real-world environments rather than relying solely on simulation.