Insights

Advanced Heuristics for Identifying and Tracking Airborne Devices in Mobile Networks

As drones increasingly use 4G and 5G networks for beyond visual line-of-sight operations, distinguishing them from ordinary mobile devices presents a growing challenge. This paper outlines a two-stage detection model: an initial behavioural sieve that flags suspicious devices based on handover frequency, signalling patterns and data usage, followed by advanced confirmation techniques such as triangulation, signal strength analysis and trajectory modelling. Together, these methods provide a layered, scalable approach for identifying airborne devices and strengthening airspace security using existing mobile network infrastructure.

4G LTE (and 5G) in BVLOS Drone Control

As beyond visual line-of-sight drone operations expand, 4G LTE has become a key enabler, offering wide-area coverage, reliable connectivity and seamless integration with cloud-based command systems. Unlike traditional short-range RF links, LTE supports long-distance control at significant altitudes, making it well suited to commercial, humanitarian and defence applications. However, reliance on public mobile networks introduces security, regulatory and strategic challenges, including cyber risks and potential misuse. As adoption grows, securing LTE-based command-and-control links and strengthening oversight will be essential to ensure safe, resilient and accountable integration into shared airspace.

image of a traffic control center (for a mobility and transportation)

Non-Kinetic Options for Drone Countermeasures (CUAS): The MAVLink Exposure in Mobile Networks

MAVLink is widely used across the drone ecosystem, but many deployments lack mandatory encryption and strong authentication, exposing command-and-control traffic to interception or manipulation—particularly when carried over 4G or 5G networks. When unprotected MAVLink is transmitted across mobile operator infrastructure, authorised analysis of signalling and data flows can, in theory, enable detection, correlation and situational awareness of drone sessions. Under narrow technical conditions, weaknesses in unauthenticated links may even create a conceptual non-kinetic intervention option. The broader implication is clear: securing MAVLink with proper authentication and encrypted transport is essential as BVLOS drones increasingly rely on public cellular networks.

Modern Air Defence Must Include Mobile Network Intelligence

The growing use of drones in hybrid warfare has exposed a critical vulnerability: hostile systems exploiting civilian LTE and 5G networks for command, control and surveillance. By using ordinary SIM cards, drones can blend into national infrastructure while operating beyond visual line of sight, often deep inside sovereign airspace. Recent incidents across Ukraine and NATO states highlight the urgency of the threat. Governments must assess unintended airborne network coverage and treat telecom infrastructure as a defensive sensor layer. Through behavioural and signalling analysis, mobile networks can provide early warning, attribution and a new layer of air defence.

ISAC and S1/NG Signalling: Why Identity-Native Detection Must Lead in 5G and 6G

As networks progress toward 5G Advanced and 6G, Integrated Sensing and Communication (ISAC) introduces powerful new capabilities for detecting airborne objects. However, in the case of cellular-controlled drones, control plane signalling analysis remains the decisive detection method. Unlike sensing, signalling provides persistent network identity, observable mobility behaviour and continuity over time, enabling drones to be detected and tracked even without physical visibility. While ISAC strengthens situational awareness by confirming the presence of an object in the air, it does not reveal who is controlling it. A robust architecture therefore places signalling at the core of detection and attribution, with ISAC acting as a complementary corroboration layer.

Tracking Mobile Network-Connected Drone Swarms Following Border Incursion

The proliferation of unmanned aerial vehicles (UAVs) using commercial mobile networks for command-and-control (C2) and video transmission has created new detection and tracking challenges for states seeking to maintain airspace sovereignty. This paper presents a conceptual framework for identifying swarms of UAVs that initiate network attachment while airborne shortly after crossing national borders.