Why modern, automated, non-library based counter unmanned aerial systems are vital

In December 2018, the closure of Gatwick Airport due to unauthorized drone activity cost airlines $64.5 million. In 2019, rebel groups used drones to attack Saudi Arabian oil fields, slashing the country's oil output by half. In 2023, we see how military and commercial off the shelf (COTS) drones are changing the face of modern conflict.

All three instances illustrate the asymmetric engagement between actors that drone technology can afford. Despite being restricted by limited resources, substantial damage can be inflicted in terms of financial consequences, public safety, and various levels of conflict scenarios.

CRFS is not a C-UAV system vendor. However, our leading-edge RF solutions are a highly regarded sensor system deployed by end-users and renowned system integrators as part of their C-UAS activity, with field-hardened hardware and workflows in operation 24/7/365.

Here is our perspective on why a modern, automated, non-library-based C-UAS is mission-critical for military and civilian applications.

NATO members’ counter UAS are inadequate

A recent LinkedIn post by a member of the senior leadership team at Anduril highlighted that many of the current counter UAS systems “consist of multiple pieces of cable networked hardware, operated by numerous sensor operators and relying on human beings to pass data ‘manually’ across operations rooms to coordinate their response. Often around 15 people (3 x shifts of 5 people for 24 hrs) are needed for a single C-UAS system; a significant logistical burden and force protection risk.”

Many C-UAS used by police and military in NATO member states are only capable of countering threats from the ‘first drone age’ (small numbers of commercial-off-the-shelf drones operating in non-threatening environments), let alone the ‘second drone age’ (when a vast array of State and non-State actors can deploy ever-more advanced drone technologies).

Arguably, we have entered the 'third drone age,’ when virtually every actor has access to advanced drone technologies—drones are software-defined, fast, and can operate in a swarm mode to overwhelm defenses. Current initiatives to counter the third drone age are not on target.

How drone swarms are overwhelming legacy C-UAS technologies

Drone swarms can present significant challenges to legacy C-UAS systems designed to address single threats.

First, as drone swarms involve many drones operating in coordination, the sheer volume makes it difficult for the C-UAS system to process and prioritize them, the kill chain is compromised as the available defenses are outnumbered, and the systems cannot detect and target individual drones quickly enough. And even if individual drones are neutralized, the swarm can reconfigure, adapt, and continue its mission—proving resilient against C-UAS measures.

Second, drone swarms can coordinate their attacks from multiple directions, making it harder for the C-UAS to track and engage them simultaneously. The swarm can exploit vulnerabilities or overwhelm the C-UAS sensors and response capabilities by approaching from various angles.

Third, drone swarms can employ electronic warfare techniques to disrupt C-UAS systems. They may use electronic jamming to interfere with radar, communication, or GNSS signals, hampering the C-UAS's ability to start the kill chain. Swarms can also employ decoys or deceptive tactics to confuse C-UAS systems and divert their attention.

A multi-layered approach to C-UAS defenses

As Bertie B. writes, “For C-UAS systems to be effective against these rapidly evolving dynamic threats, they need to have an open architecture software-first approach, be modular, able to processes data at machine speed and employ autonomous technology and AI to make or enable real-time decisions to provide the best possible opportunity to act at the speed of relevance.”

To counter drone swarms, military-grade drones, and repurposed commercial drones (COTS drones with their transponder removed), C-UAS defenses must employ a multi-layered approach that combines various technologies and strategies.

These may include a combination of radar systems, electro-optical and infrared sensors, and passive radio frequency receivers.

What are the critical elements of a modern C-UAV platform?

RF receivers are one essential component of any C-UAV platform, as they can detect the radio frequency signals emitted by drones. By monitoring the RF spectrum, passive receivers can detect the presence of UAVs. And as they do not emit any signals, they are ideal for operations requiring a minimized risk of detection.

However, not all RF receivers are made equal. Slow receivers requiring manual operation and short-range have no place in the 'third drone age.'

Effective RF receivers need to have the following functionalities:

Automation

Operators get distracted and tired, and many are needed for 24/7/365 defense. However, advanced systems avoid these issues by offering automated functionality that generates high-value data and low false positives.

Quick refresh speeds

Many commercial systems have refresh speeds of once per second, which is adequate if the threat is a single target. However, sending multiple targets overwhelms and confuses these basic sensor systems.

In this scenario, advanced systems need a rapid geolocation detection cycle of 50–60 cycles per second. Drone swarms can only be combatted by systems that operate at the highest possible speed and efficiency.

Increased detection and geolocation ranges

Many commercial systems are adept at geolocating and detecting drones when they are 1 km from the perimeter; however, this is inadequate as the threat has already penetrated your air space. To efficiently combat potential threats, operators must be able to detect UAVs as early as possible; the golden target is to detect some 10 km from their perimeter to provide early warning to the system and evaluate the threat.

At this distance, an advanced system can undertake direction finding and provide a line of bearing to the drone. An operator can then identify the drone using a camera and neutralize it (using kinetic or non-kinetic warfare) before it becomes a threat.

Why are library-based drone identification systems not the answer?

Library-based drone detection has recently been touted as a critical feature of a counter-unmanned aerial system. The method uses pre-existing software libraries to detect and identify drones. These libraries typically provide a set of algorithms and tools to analyze data captured by sensors to detect drones in a given area based on information, including their type, model, and manufacturer.  

While the approach sounds reasonable, it has one major flaw: if the drone is not in the library, it is invisible—making it a severe threat.

Moreover, library-based approaches are limited to detecting COTS drones. So any military-grade or commercial drone with the transponder taken out will not be identifiable.

A system fit for purpose for a modern C-UAS must be able to detect every type of drone, regardless of the frequency range within which it operates. Therefore, it is mission-critical for a counter UAS to obtain RF information quickly to detect and geolocate the threat in real-time.

However, the principle upon which library-based systems are based—the need to remove false positives—is crucial. Advanced software-defined ratio systems without the downsides of library systems can filter out spurious signals and false positives on the ISM band thanks to two innovative systems. 

1. Cluster filters analyze the geolocations of a signal for time continuity to determine if it is a false positive. For example, the filter recognizes one isolated spurious splash of energy as a noncontinuous signal, which can be ignored. 
   
   However, suppose the cluster filter identifies five continuous geolocations in one second within a few meters of each other. In that case, it recognizes the signal as coming from a drone as the software-defined radio's parameters are met. Consequently, an alarm can be raised and countermeasures taken.
   
   
2. Geofencing refers to creating a virtual boundary around a specific geographic area. The technique is used to identify false positives; for example, anything flying below 50 meters can be ignored, and an area containing many fixed wifi routers can be excluded.

Conclusion

Legacy systems designed to identify single targets cannot counter dynamic threats such as drone swarms. A multi-layered approach to C-UAS defenses is required, and advanced RF sensor technology is an essential part of the solution—the faster modern counter-unmanned aerial systems can identify drones, the faster they can neutralize the threat.

To protect people, borders, and assets, we need counter-unmanned aerial systems fit for the 'third drone age.'