Autonomous counter-UAS has become one of the most urgent topics in modern defense, as rapidly evolving drone tactics outpace traditional protection systems. In this guest post, Nolan Bowlus of AimLock examines why autonomy and multi-sensor integration are now essential to staying ahead of emerging battlefield threats. DRONELIFE does not pay or accept payment for guest posts.
Autonomous C-UAS: Why Autonomy is Key to Eradicating the Most Sophisticated Drone Threats
by Nolan Bowlus, Vice President of Business Development at AimLock
The war in Ukraine has become a testing ground showcasing the evolving capability of drones, as well as the increasing role of technologies such as artificial intelligence (AI) and machine learning (ML). Drones are becoming faster, more sophisticated and able to carry larger payloads, with AI playing an increasing role.
The Ukraine conflict offers a vision of what the battlefield of the future might look like in a conflict against a near-peer or near-peer-supported adversary. Drones are not only an increasing threat, but are evolving rapidly with the adoption of new technologies. It’s vital that leaders begin to plan now to deal with not just the drone threat that we see today, but the evolving threat of tomorrow.
In Ukraine, drones are being used for multiple roles, in everything from surveillance to kamikaze attacks, and it has never been more urgent to detect and deal with such threats as efficiently as possible. With drone technology evolving so rapidly, a single-sensor approach is no longer adequate. To deal with new and ever-changing drone threats, a multiple sensor approach including sensors such as acoustic, radar and RF sensors will be vital to build truly comprehensive defense networks, along with thermal detection and optical targeting. Simple one-way drone attacks are growing and are increasing in volume: to ensure warfighters can deal with such attacks, it’s vital that they are equipped with systems with autonomy, armed with optical precision targeting with AI and ML target recognition and autonomous slew-to-cue.
Keeping Warfighters Safe
In light of this continuing evolution of drone technology and how drones are used on the battlefield, technologies that can work autonomously to identify, engage and destroy targets are growing in importance. In previous decades, autonomy had become something of a taboo in discussions around military technology, but when it comes to the threat of drones which are cheaply produced, packed with explosives, and launched from locations hundreds of miles away, systems need to be able to detect at long range, and automatically target when within weapon range. In this context, autonomy is vital to the safety of the warfighter. Early detection is vital for human countermeasures. The less early detection available, the more the war fighter needs autonomous sensors, so the only reaction needed is to arm and engage. Leave the processing to the computers, so humans can focus on the authorization to execute.
AI and ML algorithms will also come into their own here, helping to rapidly identify and categorize drones. C-UAS systems need to be able to rapidly detect drones, track them, calculate firing solutions and engage, independent of human intervention. In the current evolving threat landscape, C-UAS is growing rapidly in importance, and it’s clear that networked equipment, autonomous systems and AI will be vital when it comes to keeping warfighters safe.
The Strategic Advantage
Fully integrated C-UAS systems will enable operators to disrupt, degrade and delay enemy attacks. This offers a vital advantage, with computer vision and AI helping to increase situational awareness and offering early warnings of approaching drones. This is why a multi-sensor approach is so key in delivering for warfighters. By taking a multi-sensor approach to C-UAS, targets can first be detected by radar, then at closer range by optical, then dealt with as they move into weapons range. By handling this autonomously, C-UAS systems can be faster than human response at the tactical level with the appropriate sensors.
It’s clear that not only is the use of one-way unmanned aerial system attacks growing in conflicts such as Ukraine, but that this trend will continue. Cheaply produced one-way drone attacks, packed with explosives, are a challenge to existing mission command systems. Lacking capability and interoperability, traditional mission command systems are ill-equipped to deal with the evolving smaller threats we see on the battlefields of Ukraine.
Autonomous C-UAS, with a multi-sensor approach and built on AI algorithms, can deliver a cost-effective way to extend awareness, stay ahead of evolving threats and keep warfighters safe.
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Nolan Bowlus is the Vice President of Business Development at AimLock, a company that develops autonomous systems for Defense applications. He is a seasoned Special Operations Forces veteran, with a military career spanning three decades and dozens of deployments in response to the Global War on Terror. In his 30-year career with the United States Army, Nolan served 24 years in the Special Operations Forces community, 20 of which were spent on a national mission force specially tasked with navigating and adapting to the ever-changing landscape of modern warfare.
His extensive military background has enabled him to bring a critical, on-the-ground operational understanding of the battlefield to the Defense technology sector. Before joining AimLock, he managed SOF-focused programs at Draper, solving complex technical problems for Special Operations Forces and warfighters.
Nolan is continuing his mission of service to the Nation through his dedication in advancing cutting-edge autonomous and aided target recognition systems that enhance operational effectiveness and safeguard national security.
