ANRA Technologies, a provider of digital airspace and mission management solutions, has announced continued advancement of its counter-uncrewed aircraft systems (C-UAS) capabilities following participation in NATO Counter-UAS Technical Interoperability Exercises and the U.S. Army’s Driving Innovation in Realistic Training (DIRT) Days, the Washington-based company said on 27 October 2026. As U.S. defense, homeland security and public safety agencies expand investment in drone detection and airspace security, ANRA is advancing its Single Integrated Operating Picture (SIOP) software and Tactical Airspace and C-UAS Operations (TACO) system to help organisations combine drone detection with information about authorised airspace activity. Both systems have progressed from Technology Readiness Level 5 to Level 7 through development and testing in defense and security environments, including multinational interoperability exercises.

“The next challenge in drone security is not simply seeing an aircraft; it is understanding who is operating, where they are flying and whether that activity is permitted,” said Amit Ganjoo, Founder and CEO of ANRA Technologies. “Our operational UTM experience, combined with the interoperability demonstrated by SIOP and TACO, provides a foundation for partners to build a more complete airspace picture without being locked into one sensor or one vendor.”

Unlike traditional counter-drone systems that focus primarily on detecting and tracking aircraft, ANRA’s approach combines sensor-based detection data with available UTM information about authorised drone activity, helping security operators assess whether detected aircraft may be associated with legitimate commercial, public safety or government operations.

FROM SENSOR DATA TO A COMMON OPERATING PICTURE

SIOP is ANRA’s sensor-agnostic airspace awareness and command-and-control software. It correlates data from multiple sources, including radar, passive radio frequency sensors, optical sensors, Remote ID and automatic dependent surveillance-broadcast systems, alongside UTM information such as geozones and flight activity, to help operators identify potential conflicts and flag detections warranting further investigation. TACO packages SIOP’s capabilities into a rugged, modular, portable system that can be deployed in under 15 minutes and has been tested with up to ten simultaneously connected sensors and 100 tracked targets.

INTEROPERABILITY DEMONSTRATED IN DEFENSE ENVIRONMENTS

ANRA has participated in NATO C-UAS Technical Interoperability Exercises since 2023, as well as U.S. Army DIRT Days, testing integration with diverse sensor and command-and-control systems using SAPIENT, an open architecture and interface standard. SIOP and TACO also support ASTERIX and other industry-standard interfaces. The company notes that these exercises provide evidence of technical interoperability in test environments and do not constitute NATO certification or endorsement of its products.

UTM EXPERIENCE AND U.S. PARTNERSHIP OPPORTUNITIES

ANRA’s counter-drone capabilities draw on its experience supporting operational UAS Traffic Management services, including work with customers such as Amazon Prime Air and the New York Power Authority; the company says approximately one beyond-visual-line-of-sight flight launches every ten seconds on ANRA-powered systems, and that its technology supports operations at more than two dozen police departments. Following the Federal Emergency Management Agency’s announcement on 16 October of $250 million in funding through its fiscal 2027 Counter-Unmanned Aircraft Systems Grant Program, ANRA is inviting U.S. sensor manufacturers, defence and homeland security integrators, public safety technology companies and government agencies to explore joint demonstrations and teaming opportunities.

Note: ANRA notes that detection and identification alone do not establish legal authority to mitigate an aircraft, and that any response must remain within the legal authorities and operational requirements applicable to the responding organisation.