ROME, N.Y. \u2014 ANDRO Computational Solutions, LLC of Rome has been awarded a multimillion U.S. Army CPE IEW&S contract to advance Artificial Intelligence and Machine Learning (AI\/ML) readiness through the generation of high-fidelity synthetic radio frequency (RF-Gen) datasets to enhance the operational capabilities in electronic warfare (EW) and signal intelligence (SIGINT) domains.<\/p>\n\n\n\n
RF-Gen leverages state-of-the-art generative AI models to produce high-quality synthetic RF datasets that replicate realistic radio frequency environments, including complex interference and contested spectrum conditions. The datasets are crucial for training and evaluating AI\/ML models designed for modern EW and SIGINT systems. By creating data-rich, controlled, and secure simulation environments, RF-Gen ensures that mission-critical algorithms can be trained and tested without depending on expensive real-world RF data collection systems that may be limited or restricted in the manner or type of data acquired.<\/p>\n\n\n\n
The project, titled, \u201cRF-Gen: AI\/ML-Ready Synthetic RF Data,\u201d is being led by ANDRO\u2019s Marconi-Rosenblatt AI Innovation Lab under the direction of Co-Principal Investigators Dr. Jithin Jagannath, Chief Scientist \u2013 Chief Technology Officer and Dr. Anu Jagannath, Chief Scientist \u2013 Chief Research Officer. The work directly supports the Army\u2019s Project Linchpin initiative that is focused on delivering trusted AI\/ML capabilities enabling rapid development, integration, and deployment of advanced analytics to the Army\u2019s Integrated EW and sensor modernization efforts.<\/p>\n\n\n\n
According to ANDRO president Dr. Andrew Drozd, the RF-Gen project perfectly spotlights ANDRO\u2019s Marconi-Rosenblatt Lab strengths and deep expertise in AI\/ML-driven RF systems paving the way for emergent RF Machine Learning operational (RFMLOps) solutions for the military. The project team also includes Deepwave Digital\u2014a commercial software-defined radio (SDR) hardware supplier.<\/p>\n\n\n\n
Built upon an advanced AI\/ML hybrid framework, RF-Gen ensures adaptability across diverse operational and commercial contexts\u2014from tactical defense applications to next-generation telecommunications. Its model-agnostic architecture allows seamless integration with a wide range of AI frameworks, supporting both defense and commercial partners seeking to enhance system resilience and situational awareness.<\/p>\n\n\n\n
\u201cRF-Gen represents a transformative step in how synthetic RF data can empower AI-driven decision-making in both military and civilian domains,\u201d stated Jithin Jagannath. \u201cBy generating highly realistic datasets, we are enabling the development of smarter, more resilient systems capable of thriving in the most challenging of RF environments.\u201d<\/p>\n\n\n\n
Drozd added, \u201cRF-Gen represents ANDRO continual efforts at driving innovation at the intersection of AI, RF engineering, and national security. This work reflects the company\u2019s ongoing commitment to delivering mission-ready AI\/ML technologies that bolster defense readiness while advancing the frontier of intelligent spectrum operations.\u201d<\/p>\n\n\n\n
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