Cognitive EW
Advanced cross-platform machine learning software designed to pace modern, complex radar threats
Expand the Envelope
Vadum is a leader in the development and deployment of machine learning in electronic warfare. Augmenting existing intelligence-driven countermeasure systems, Vadum machine learning software enables deployed systems to pace modern, complex radar threats. Expertise in joint EW operations, machine learning, real-time software development, and radar operation and characterization allow Vadum to present the warfighter with robust solutions to rapidly changing operational environments across a range of tactical platforms.
Self-protection and Jamming Systems
Provide real-time unknown, adaptive, and complex radar threat characterization for jamming countermeasure selection and threat separation and identification with online threat model construction and radar capability analysis.
Adaptive Intelligence Analysis Support
Featuring real-time jammer characterization to support radar EP techniques selection for SAR and ISAR operations, and human interpretable machine learning to assess jammer capabilities and decision logic.
Countermeasure System Reprogramming
Enable real-time receiver tuning and jamming resource decision making to improve threat detection and application of jamming to priority threats with limited EW resource availability.
Pace the threat with ROCS – Radar Online Characterization System
Capabilities
Vadum has developed and matured a machine-learning software capability to characterize complex, adaptive, agile emitters to improve EW decisions, situation awareness, and force survivability
- Deep characterization of surface and airborne radars
- Radar behavioral and intent inference to support identification, countermeasure decisions, and effectiveness analysis
- Builds radar system models capturing capabilities and operations from observed emissions
- Adaptive analysis identifies agile and complex behavior from multi-function radars
Attributes
The capability (ROCS – Radar Online Characterization System) has been integrated, tested, and is ready to integrate and run real-time today
- Real-time, machine learning operation on existing avionics systems in tactical aircraft
- Scalable software for dense emitter environments
- Robust, streaming analytics accommodate noisy and missing emitter data
- Analytics from basic emitter data readily accepts new sensor or intelligence data to improve characterization accuracy and increase emitter model detail