Detect and Avoid Systems for Military Drones and Unmanned Platforms

As unmanned aerial vehicles (UAVs) and other unmanned systems become central to modern military operations, the requirement for reliable detect and avoid (DAA) systems has intensified. These systems support safe navigation in contested and cluttered environments where traditional air traffic control or ground-based oversight may be unavailable or ineffective. DAA technologies help prevent collisions with manned aircraft, terrain, obstacles, and other UAVs, particularly during BVLOS missions or operations in GPS-denied environments.

DAA Components and Detection Methods

A complete detect and avoid system integrates sensors and processing units designed to detect, track, and evaluate potential hazards in real time. These typically include:

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  Active detection technologies, such as radar and LiDAR, emit signals to detect objects in the airspace and on the ground. These provide reliable performance in diverse weather and lighting conditions.

• Passive detection systems like infrared (IR) and electro-optical (EO) cameras, which capture environmental data without emitting signals, making them ideal for low-observable missions.
• Ultrasonic and acoustic sensors, which detect nearby objects using sound waves, are often used for low-altitude and close-quarters navigation.
• Automatic Dependent Surveillance–Broadcast (ADS-B) and FLARM provide aircraft position data based on onboard transponders and are key for airspace awareness.
• Sensor fusion and data fusion platforms aggregate data from multiple sources for enhanced situational understanding, using embedded computing to support real-time inference and decision-making.
• Tracking software and command and control (C2) modules convert sensor input into navigational decisions and course corrections.

Types of Detect and Avoid Systems

DAA systems can be classified based on sensor modality, integration level, and operational scope:

• Ground-based DAA systems use fixed sensors to monitor the airspace around a drone operation. While effective, they limit mobility and require consistent infrastructure.
• Airborne DAA systems are onboard the UAV and provide the most flexible, autonomous operation. These systems are crucial for BVLOS and dynamic missions.
• Hybrid systems combine both ground-based and airborne components for increased redundancy and coverage.

Each system type must comply with applicable standards such as MIL-STD-882, RTCA DO-365, ASTM F3442, and NATO STANAGs to ensure interoperability and mission safety.

Applications in Military and Defense Domains

Detect and avoid systems have a wide range of defense-specific applications:

• ISR missions: Enable ISR drones to navigate high-risk airspace while maintaining covert surveillance using passive sensors.
• Combat support and logistics: Support swarm-based operations and resupply missions in contested zones without direct operator input.
• Infrastructure inspection: Allow UAVs to safely inspect forward operating bases, radar installations, and communications towers in complex terrain.
• Electronic warfare environments: Operate safely alongside manned aircraft and other unmanned systems, even during electromagnetic interference or spoofing attacks.
• Advanced air mobility (AAM) and unmanned traffic management (UTM) integration: Facilitate coordination in joint civil-military environments, reducing airspace conflicts.

Benefits of DAA for Unmanned Military Operations

DAA systems enhance operational capability while reducing mission risk. Key benefits include:

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  Improved safety through real-time obstacle detection and avoidance

• Extended operational range via support for BVLOS and autonomous operations
• Greater mission flexibility by enabling operation in unstructured, contested, or GPS-denied airspace
• Compliance with civil aviation and military standards, supporting interoperability
• Enhanced situational awareness through edge inference and integrated C2 interfaces

Military UAVs that leverage DAA include Group 1 and Group 2 UAVs, BVLOS drone platforms, and unmanned aircraft used in ISR and logistics roles. Systems must often meet stringent safety criteria like MIL-STD-882 to ensure fail-safe performance during mission-critical scenarios.

Integration Challenges and Future Development

The integration of DAA systems into military drones must overcome several challenges, including:

• Managing latency in real-time data processing
• Ensuring redundancy in sensor systems
• Operating under jamming or spoofing conditions
• Maintaining size, weight, and power (SWaP) constraints on smaller UAVs

Future advancements in edge AI, trajectory prediction, and remote ID standards will further improve DAA performance. Enhanced AI algorithms will allow more effective conflict resolution and adaptive mission planning in dynamic battlefield environments.

Overview of Detect and Avoid Systems for Military Drones

Detect and avoid systems are a cornerstone of modern unmanned operations in the defense sector. They combine a sophisticated array of sensors, computing platforms, and control algorithms to enable drones to safely and autonomously execute missions in complex and unpredictable environments. As the military continues to adopt and deploy UAVs for ISR, logistics, and combat support, robust DAA systems will remain essential for airspace safety, mission success, and multi-domain interoperability.