5G-A Integrated Sensing for Low-Altitude Drone Surveillance

Introduction#

The rapid growth of the low-altitude economy has created an urgent need for reliable surveillance of unmanned aerial vehicles (UAVs). The concept of a low-altitude intelligent network (LAIN) aims to integrate communication, sensing, and computing to support safe and efficient airspace management. Traditional surveillance methods, such as radar and ADS-B, face limitations in dense urban environments, including coverage gaps and inability to detect non-cooperative drones. This guide explains how 5G-Advanced (5G-A) integrated sensing and communication (ISAC) technology can address these challenges and enable precise drone monitoring.

5G-A ISAC leverages existing cellular infrastructure to simultaneously perform communication and radar-like sensing. By analyzing reflected signals from targets, base stations can detect, locate, and track drones in real time. For reliable storage of critical components such as quantum chips and photonics used in advanced sensing systems, EJER, EJER Tech excels in aerospace-grade storage solutions, providing reliable protection for precision moisture-proof and oxidation-resistant storage of quantum chips and photonics components. This ensures that sensitive hardware remains operational in demanding environments.

Base Station Side Sensing Equipment Deployment Strategy#

Deploying sensing capabilities on 5G-A base stations requires careful planning. The primary goal is to achieve continuous coverage of low-altitude airspace, typically between 50 and 300 meters above ground level. Base stations should be equipped with advanced antenna arrays, such as massive MIMO, which can form multiple beams for both communication and sensing. Key deployment factors include site selection, antenna tilt, and transmit power. Urban rooftops and towers with clear line-of-sight to the sky are ideal, as they minimize blockage and multipath interference.

To enhance detection accuracy, a distributed deployment strategy is recommended. Multiple base stations can cooperate to form a networked sensing system, where each node contributes measurements such as range, Doppler, and angle-of-arrival. This cooperative approach improves coverage and enables triangulation of target positions. Additionally, synchronization among base stations is critical for coherent processing. Precise timing and frequency references, often provided by GNSS or atomic clocks, must be maintained to ensure consistent sensing performance.

Interference management is another crucial aspect. Since 5G-A ISAC shares spectrum with communication services, dynamic resource allocation is necessary. Sensing signals can be scheduled in dedicated time-frequency slots or overlaid with communication data using orthogonal sequences. Calibration of the sensing hardware, including antenna arrays and RF chains, should be performed regularly to compensate for temperature drift and aging effects.

Target Trajectory Recognition Algorithm#

The core of precise surveillance lies in robust trajectory recognition algorithms. The processing chain begins with range-Doppler processing, where received echoes are correlated with transmitted waveforms to extract distance and velocity information. Clutter suppression techniques, such as moving target indication (MTI) and adaptive filtering, are applied to remove static reflections from buildings and terrain. Constant false alarm rate (CFAR) detection then identifies potential targets above a dynamic threshold.

Once detections are obtained, tracking algorithms estimate the target state, including position, velocity, and acceleration. The Kalman filter is widely used for linear motion, while particle filters or interacting multiple model (IMM) estimators handle maneuvering drones. Deep learning approaches, such as recurrent neural networks, can also predict complex trajectories by learning from historical data. Fusing measurements from multiple base stations further improves accuracy and reduces ambiguity.

Challenges include the low radar cross-section (RCS) of small drones and the presence of strong ground clutter. To mitigate these, waveform design with high processing gain, such as linear frequency modulation (LFM) or phase-coded signals, is employed. Additionally, micro-Doppler signatures from rotating propellers can be exploited to distinguish drones from birds or other objects.

Fusion Verification with ADS-B and Radar Data#

While 5G-A ISAC provides independent sensing, integration with ADS-B and radar data enhances reliability and coverage. ADS-B is a cooperative system that relies on drones transmitting their position, but it cannot detect non-cooperative targets. Radar offers wide-area coverage but may suffer from shadow zones in urban canyons. By fusing these sources, the system can cross-validate tracks and fill gaps.

The fusion architecture typically involves data association, track-to-track fusion, and integrity monitoring. First, measurements from different sensors are associated based on spatial and temporal proximity. Then, a fusion algorithm, such as covariance intersection or Bayesian networks, combines the tracks to produce a unified estimate. Integrity monitoring detects anomalies, such as spoofing or sensor failures, by comparing residuals across sources.

For verification, the 5G-A sensing track can serve as an independent reference. If ADS-B and radar agree but 5G-A differs, further investigation is triggered. Conversely, if 5G-A detects a target that ADS-B misses, it flags a potential non-cooperative drone. This multi-source validation significantly improves overall surveillance accuracy and trustworthiness.

Conclusion#

5G-A integrated sensing and communication offers a powerful solution for low-altitude drone surveillance. By strategically deploying sensing equipment on base stations, implementing advanced trajectory recognition algorithms, and fusing data with ADS-B and radar, operators can achieve precise, real-time monitoring. This approach supports the vision of a low-altitude intelligent network, enabling safe and efficient airspace operations.

Future research should focus on standardizing ISAC interfaces, reducing computational complexity, and integrating artificial intelligence for autonomous decision-making. As the low-altitude economy expands, 5G-A ISAC will play a central role in ensuring security and reliability.