This notice is published in accordance with Federal Acquisition Regulation Part 10.002 and Subpart 15.201 and is a request for information for conducting market research. All information received will be used for planning purposes only. This notice does not constitute invitation for bids, request for proposals, or request for quotes. The Government will not award a contract based on this notice and will not reimburse interested firms for any costs associated with responses to it. BACKGROUND: Current Army radar systems utilize predetermined waveform schedules and a fixed number of waveforms for search and track functionality. These settings are typically configured prior to deployment and as a result are difficult to change in the field in order to adapt to a rapidly changing threat environment. This leaves the radar system vulnerable to Electronic Warfare (EW) attacks and evolving threat target tactics. The objective of the Artificial Intelligence Radar Enhancement (AIRE) is to overcome these limitations through Artificial Intelligence (AI) and Machine Learning (ML). DESCRIPTION: The AIRE will be an AI based radar scheduler and waveform selector that autonomously manages the search and tracking aspects of a radar system. Solutions can consist of hardware and/or software, but must support integration into existing radar systems. The AIRE should be developed using advanced AI and/or ML techniques, i.e. reinforcement learning. Any candidate solution should address the following capabilities: Maximize the use of radar resources and optimize tracking waveform choice based on the operational environment or engagement constraints. Provide an adaptive search volume and obey a threat priority hierarchy provided by the user. Automatically detect and recognize EW countermeasures that are a threat to the radar system. Alert the radar operator of any detected EW threats and provide information on the type of threat, location of the threat, and the effects on the radar system. Dynamically change the radar's waveforms and beam scheduling in order to adapt to any EW threats while maintaining search and track performance to the greatest extent possible. Allow the customer to deploy antagonistic scenarios and training sets for continued AI learning. Interested firms should be willing to host government personnel and contractors for a product demonstration within 12-18 months. The whitepaper should include an outline of the demonstration details (how, what, etc.). The product should be a Technology Readiness Level (TRL) 3/4. SECURITY REQUIREMENTS: Interested firms must be eligible for a COMSEC account and demonstrate the ability to maintain National Information Security Program standards. Security requirements for any resultant contract will be a facility cleared to the Secret level with authorization to store COMSEC items and individuals with clearance eligibility to the Secret level. A sufficient number of individuals will require access to COMSEC. Potential solutions sought shall have full National Security Agency (NSA) approved Type-1 and Advanced Encryption Standard (AES) level encryption capability. This RFI is for planning purposes only and shall not be considered as an IFB, RFQ, or RFP. Additionally, there is no obligation on the part of the Government to acquire any products described in this RFI. Your response to this RFI is voluntary and will be treated only as information for the Government to consider. You will not be entitled to payment for direct or indirect costs that you incur in responding to this RFI. This request does not constitute a solicitation for proposals or the authority to enter into negotiations to award a contract. No funds have been authorized, appropriated, or received for this effort. The Army may use the information provided to develop its acquisition strategy. Interested parties are responsible for adequately marking proprietary, restricted, or competition sensitive information contained in their response. The Government will not pay for the information submitted in response to this RFI. If a solicitation is released for the supplies or services described herein, then it will be synopsized through the government point of entry (GPE) web site. It is the responsibility of the potential offerors to monitor this site for additional information pertaining to this potential requirement. RESPONSES: Interested parties are requested to respond to this RFI with an unclassified white paper on 8.5 x 11 inch paper with fonts no smaller than 10 point, one inch margins, in PDF, HTML, MS Word or PowerPoint formats. The white paper will contain no more than 10 pages in length including tables, charts, and figures. Each page of the submission shall contain a document identifier in the document header. Respondents should ensure to label any information contained in the white paper considered to be proprietary. The white paper shall describe the responder's capabilities and potential materiel/services solution that meets the criteria referenced in this document. The whitepaper should include what is available for a demonstration within a year, what will be available within five years, and what will be available long term (after 2028). The whitepaper should also include, at a minimum, the interfaces, AI/ML methodology, hardware requirements (size, weight, power, processing), rough order of magnitude cost, current development timeline and compatible/proposed radar system requirements of the AI/ML application. Ideal responses will include answers to the following questions: What AI/ML techniques are utilized in the product? What data sources have been used in training the AI? How is product currently tested and rated? Has the product been integrated with an existing radar system? Has the product been trained on for a specific target set (i.e., UAS)? Is the product currently in use in a fielded system? Please include the parties experience with AI/ML and or radar systems including number of years in the field with the response. Responses are due no later than April 15, 2022, 4:00 PM EDT. All responses should be submitted electronically using PDF, HTML, MS Word or PowerPoint formats to the POC, Tawanda Agee, at the following e-mail address: tawanda.l.agee.civ@army.mil.
