The US Army and the Defense Innovation Unit (DIU) have selected defense technology firm Anduril Industries to develop a next-generation fire control system for counter-unmanned aircraft systems (C-UAS). The project aims to modernize the Forward Area Air Defense Command and Control (FAAD C2) system by integrating artificial intelligence (AI), sensor fusion, and automated threat engagement capabilities.
Strategic Need for Modernized C-UAS Fire Control
As small unmanned aerial systems (sUAS) proliferate across global battlefields—from commercial quadcopters used by insurgents to military-grade loitering munitions—traditional air defense systems face increasing challenges. The US Army’s existing FAAD C2 architecture was originally designed for short-range air defense (SHORAD) against rotary-wing threats and cruise missiles. However, it lacks the speed and automation needed to counter swarming drones or low-signature FPV threats in real time.
To address this capability gap, the Army is pursuing a new fire control capability that can ingest data from diverse sensors—including radar, electro-optical/infrared (EO/IR), acoustic arrays, and RF detectors—and rapidly assign targets to appropriate effectors such as jammers, directed energy weapons (DEWs), or kinetic interceptors. The goal is a modular, scalable system that can operate autonomously or with minimal operator input in complex environments.
Anduril’s Role and Technology Stack
Anduril Industries was selected through a competitive solicitation issued by DIU in partnership with the US Army’s Joint Counter-small Unmanned Aircraft Systems Office (JCO). The company will leverage its existing Lattice OS platform—an AI-powered command-and-control software suite already deployed with several US services—to form the core of the new fire control architecture.
Lattice OS enables real-time fusion of multi-domain sensor inputs with autonomous decision-making algorithms. It has been used in Anduril’s own Sentry Towers and Ghost UAS platforms for perimeter security and ISR missions. In this new application, Lattice will be adapted for tactical C-UAS operations with enhanced latency reduction and kill chain automation.
- Sensor Fusion: Integrates radar tracks with EO/IR imagery and RF signatures
- Threat Classification: Uses machine learning models trained on drone behavior profiles
- Effector Assignment: Automates tasking of soft-kill or hard-kill countermeasures
- C2 Interoperability: Designed to plug into existing FAAD C2 nodes via open standards like ATAK/MIL-STD-6017
A Modular Approach Aligned with JCO Architecture
The Joint C-sUAS Office has emphasized modularity and interoperability as key tenets of its acquisition strategy. Rather than fielding monolithic systems from single vendors, JCO advocates a “system-of-systems” approach where best-of-breed sensors and effectors are integrated via open architectures. This allows rapid insertion of emerging technologies while preserving backward compatibility with legacy assets.
Anduril’s solution aligns closely with this vision. By decoupling sensing, decision-making, and engagement layers—and using common data formats like STANAG 4586 or Link-16—the new fire control module can serve as a plug-and-play node within broader air defense networks. It also supports integration with NATO allies’ systems under coalition operations.
Testing Roadmap and Fielding Timeline
The development effort will proceed through phased prototyping under an Other Transaction Authority (OTA) agreement managed by DIU. Initial lab demonstrations are expected in early FY2025, followed by live-fire testing at Yuma Proving Ground later that year. If successful, limited fielding could begin in FY2026 under urgent operational needs statements from forward-deployed units.
This timeline reflects growing urgency within DoD circles about drone threats observed in Ukraine, Syria, Gaza Strip, and other conflict zones where low-cost UAS have inflicted disproportionate damage on armored vehicles and logistics nodes.
Implications for Future Air Defense Doctrine
The adoption of AI-enabled fire control represents a doctrinal shift toward machine-speed engagement cycles. Rather than relying solely on human operators for threat identification and response decisions—often too slow against drone swarms—the future battlefield will increasingly rely on autonomous or semi-autonomous kill chains governed by trusted algorithms.
This raises important questions about rules of engagement (ROE), human-in-the-loop requirements under international law, cyber resilience of AI models under adversarial conditions, and ethical use of lethal autonomy. The FAAD modernization effort may serve as a testbed not only for technology validation but also policy refinement across these domains.
