Unmanned aircraft systems are becoming smaller and increasingly autonomous, expanding their potential use against military, government, and critical-infrastructure targets. At the same time, the global counter-UAS market is growing rapidly as defense and security organizations look for new ways to detect, track, and respond to these evolving threats. 

As more drones gain the ability to fly without a live radio link, counter-UAS systems face a fundamental detection challenge: What happens when there is no radio signal to detect? 

The Challenge of Detecting Autonomous Drones 

Radio-frequency detection has an important role in counter-UAS systems. By identifying communications between a drone and its operator, RF-based systems can help detect potential threats. 

Traditionally, many drones relied on frequent communication with a human operator to receive instructions or updates to their flight path. Today, more sophisticated drones can use onboard computing and AI to make decisions based on their mission objectives, reducing the need for continuous communication with a human controller. 

As a result, some drones can operate for extended periods without transmitting a radio signal. That creates a challenge for counter-UAS systems that depend on detecting those transmissions: if a drone isn’t communicating, there may be no command-and-control signal to intercept. 

GPS adds another layer of complexity. While drones may use GPS signals to determine their location, receiving a GPS signal is different from transmitting one. A drone’s use of GPS does not, by itself, provide a readily detectable signal that identifies the aircraft’s location to a counter-UAS system. 

Instead of relying on a drone to announce its presence through a radio transmission, counter-UAS systems increasingly need sensing technologies capable of detecting the physical aircraft itself which is where lidar can provide another layer of perception.  

From Detecting a Signal to Detecting the Object 

Lidar approaches the detection problem differently. It doesn’t depend on intercepting communications between a drone and an operator. Instead, lidar directly measures the physical environment in three dimensions. 

Put simply, the question shifts from “Can I detect its signal?” to “Can I see and track the physical object?”.  

For counter-UAS applications, that distinction becomes increasingly important as potential targets become smaller and less dependent on radio communications. A useful counter-UAS sensing layer also needs to provide information that can help the broader system understand what it is seeing. 

Why Range and Resolution Matter Together 

Detecting a small aerial target at long distance presents a demanding perception problem. 

Range is important because detecting an object farther away can provide earlier awareness, but range alone tells only part of the story. The sensor also needs sufficient resolution to provide meaningful information about a small object at that distance. 

AEye’s STRATOS™ ultra-long-range lidar is designed for this combination of range and resolution. The third-generation sensor is designed to detect objects at distances of up to 1.5 kilometers while providing more than twice the resolution of AEye’s Apollo™ sensor. 

For counter-UAS applications, that combination is intended to help move detection beyond simply indicating that an object is present. High-resolution 3D perception can provide a precise three-dimensional track, including information such as distance, height, and speed, helping an operator assess a potential threat and determine how to respond. 

This is an important distinction: seeing farther is most valuable when you can also extract useful information from what you see. 

Counter-UAS Is a Multi-Sensor Problem 

Lidar isn’t intended to make every other sensing technology obsolete. Counter-UAS presents a complex perception challenge, and different sensors can provide different kinds of information. That’s why multi-sensor architectures can be particularly valuable. 

AEye’s work with Swiftstrike AI illustrates this approach. Swiftstrike is developing an autonomous, modular counter-UAS platform that uses multiple sensing modalities and kinetic effectors to detect, track, and neutralize small and medium-sized drones. 

Under the companies’ announced collaboration, AEye’s STRATOS™ lidar is being integrated as an ultra-long-range detection layer within Swiftstrike’s counter-UAS system. The goal is to pair STRATOS’™ long-range 3D perception with Swiftstrike’s counter-UAS platform and autonomy software to provide defense and security customers with earlier, more reliable detection of small drone threats. 

Rather than asking one sensor to solve every part of the problem, the architecture can bring together complementary technologies to create a more complete understanding of what is  happening in the environment. 

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