AI-Driven Mission Planning Platform for Model-Based Counter-UAS Operations

Omnisys is introducing a next-generation Counter-Unmanned Aerial System (C-UAS) mission planning platform within its Battle Resource Optimization (BRO™) suite, aimed at moving defense strategies from reactive interception to proactive, model-driven prevention.

The new BRO™ C-UAS platform leverages advanced technologies to enable operational users to understand their arena in depth and anticipate likely UAS attack paths. By utilizing a physics-accurate digital twin of the battlespace, the system reveals low-altitude approach corridors and coverage gaps caused by terrain, buildings, and vegetation.

This capability allows planners to calculate real-world detection, tracking, and engagement ranges for sensors and effectors, ensuring radars, RF sensors, jammers, and interceptors are placed where they have the greatest impact under real terrain and spectrum conditions. It also helps users identify vulnerabilities, close blind spots, and prioritize critical sites and routes.

An AI-driven optimization engine evaluates alternative deployment options and recommends courses of action to enhance interception probability while reducing mutual interference and redundant overlaps.

The platform functions as an independent planning tool, focusing on mission logic rather than controlling devices in real time, and complements existing command-and-control and sensor systems. By simulating operational behavior, enemy actions, and constraints, it provides deeper mission understanding, beyond mission awareness, helping commanders make faster, more informed decisions against small drones, FPV strike platforms, and loitering munitions using existing C-UAS assets.

Omnisys’ platform is fully vendor-agnostic, supporting the modeling of mixed fleets of radars, EO/IR sensors, RF detectors, and kinetic effectors from multiple suppliers. A secure local configurator allows users to input sensitive performance parameters, ensuring that classified or proprietary information about own forces and hostile systems remains under sovereign user control. This architecture enables accurate simulation and optimization without requiring dependence on external parties.

Beyond mission planning, the system supports training and long-term force development by providing a realistic environment for complex counter-drone scenarios and data-driven after-action reviews. Acquisition and force-development authorities can use the platform to evaluate alternative architectures and quantify operational trade-offs, identifying the most cost-effective combination of sensors and effectors for specific mission profiles and budgets.