Adaptation of Los Alamos National Laboratory's SmartTensors AI Suite for Advanced RF Signal Detection and Analysis in Complex Electromagnetic Environments

This proposal outlines a groundbreaking approach to RF signal detection and analysis in complex electromagnetic environments, leveraging the SmartTensors AI suite. Our goal is to adapt and extend these powerful algorithms to meet the U.S. Army's critical needs in electronic warfare and signals intelligence.SmartTensors, a collection of advanced nonnegative matrix and tensor factorization algorithms, has demonstrated unprecedented capabilities in processing massive datasets. Recently, it achieved a world record by factorizing a 340-terabyte dense matrix and an 11-exabyte sparse matrix. We propose to harness this computational power to revolutionize RF signal processing, enabling the analysis of wide-band, long-duration RF recordings at scales previously thought impossible.Our approach centers on three key innovations:Adaptation of SmartTensors for RF-specific challenges: We will extend our algorithms to handle the unique characteristics of RF signals, including time-frequency representations, phase information, and multi-path effects. This will build upon our successful ShiftNMFk method, enhancing it to identify and separate overlapping signals in noisy environments.Development of edge-optimized models: We will create compressed versions of our algorithms suitable for deployment on resource-constrained devices, bringing advanced signal processing capabilities to the tactical edge. Our goal is to reduce the computational footprint by 80% while maintaining accuracy.Implementation of automated model selection: We will incorporate our proven techniques for automatically determining the optimal number of signal sources, reducing the need for manual tuning and expert intervention.The proposed system will be capable of processing RF data in near-real-time, identifying and classifying signals, determining source locations, and adapting to new threat signatures on the fly. We anticipate achieving high accuracy in signal identification, even for signals only 10dB above the noise floor, and the ability to process signal events on edge devices.Our team brings unparalleled expertise in AI/ML, signal processing, and military technology integration. We will leverage our experience in adapting these algorithms for DoD applications to ensure rapid development and deployment.This project has the potential to provide the U.S. Army with a transformative capability in electronic warfare, enhancing spectrum management, threat detection, and situational awareness in contested electromagnetic environments. Moreover, the flexible nature of our approach will allow for quick adaptation to emerging threats and new operational requirements.