Damn Yankees – Advanced C4ISR Sensor System Radio Frequency Machine Learning (RFML) Capabilities and Methods

The field of artificial intelligence / machine learning (AI / ML) has rapidly advanced over the last decade. Radio Frequency (RF) signal processing, spectrum characterization, signal classification, and specific emitter identification are important areas of application and development due to the increasingly complex nature of the modern RF environment. There have been efforts to develop AI / ML-assisted tactical decision aids for warfighters, based in part on the products of AI / ML RF signal processing in combination with conventional sources of tactical information such as what is generated by electronic support (ES) systems, radar, Automatic Identification System (AIS) for maritime vessels and Automatic Dependent Surveillance – Broadcast (ADS-B) for aircraft. 

The Office of Naval Research (ONR) is actively advancing the Rough Casper program, which focuses on developing remotely and autonomously operated C4ISR nodes. These nodes are designed for deployment on both manned and unmanned surface vessels, as well as shore-based locations. Equipped with a suite of advanced sensors including – passive RF sensors, radar, electro-optic/infrared (EO/IR) systems, and Automatic Identification System/Automatic Dependent Surveillance – Broadcast (AIS/ADS-B) receivers, these nodes are intended to generate and transmit critical tactical intelligence to remote command centers. The primary objective of this initiative is to enhance the autonomy of these remote nodes while ensuring that the tactical information they provide is timely, accurate, and actionable. Achieving this goal will require significant advancements in edge processing and sensor fusion capabilities. Additionally, improving sensor performance and refining track fusion, to seamlessly integrate onboard and offboard data will be crucial in reducing bandwidth demands on over-the-horizon data links. By addressing these challenges, the Rough Casper program aims to deliver a more efficient, resilient, and intelligent C4ISR infrastructure to support naval operations.

08/24/2023: Request for White Papers Released
09/18/2023: White Papers Due
03/22/2024: Solution Selected
10/08/2024: Request for Proposal Released
11/06/2024: Proposal Submitted
TBD: Awarded