PL RFI for RF_EW Capabilities to Support_Army Initiatives_Final.pdf

SPECIAL NOTICE: Program Executive Office Intelligence, Electronic Warfare and Sensors Request For Information Radio Frequency/Electronic Warfare Artificial Intelligence Capabilities to Support Army Initiatives.

1. SYNOPSIS

The United States (U.S.) Army, Program Executive Office Intelligence, Electronic Warfare and Sensors (PEO IEW&S), Project Manager Intelligence & Analytics (PM IS&A) in conjunction with Project Manager Electronic Warfare & Cyber (PM EW&C) are issuing this Request For Information (RFI) as a means of conducting market research to help scope a future contract activity, in partnership with Chief Digital and Artificial Intelligence Office (CDAO), and the Department of the Army, G2 / Intelligence Surveillance Reconnaissance Task Force to train and deliver models to Army programs.

1.1. INTRODUCTION

REQUEST FOR INFORMATION ONLY. The purpose of this posting is to notify industry of an RFI. Project Linchpin enables the Army to deliver trusted solutions for AI-enabled systems through a secure Artificial Intelligence Operations and Artificial Intelligence Services (AIOPs+) while maximizing the Department of Defense (DoD) and Intelligence Community (IC) investments. Project Linchpin creates a collaborative yet competitive environment of industry and Government partners to establish the AIOPs+ ecosystem and creates new opportunities for inclusion into the ecosystem through rapid agile acquisition and contracting approaches.

PM EW&C oversees the acquisition of integrated Intelligence, Electronic and Cyber Warfare capabilities. These capabilities provide spectrum and dominance for the U.S. Army. PM EW&C manages a diverse portfolio across five product management offices, responsible for developing, acquiring, producing, fielding, and sustaining Programs of Record and Quick Reaction Capabilities. Their work includes analyzing, planning, organizing, and executing Electronic Warfare (EW) operations, focusing on degrading, disrupting, neutralizing, or destroying enemy capabilities.

2. DISCLAIMER

THIS IS NOT A NOTICE OF Request for Proposal (RFP) ISSUANCE. Responses to this request are voluntary and will not affect any contractor's ability to submit a proposal if, or when, an RFP is released for a future effort. The requested information is for planning purposes only and does NOT constitute a commitment, implied or otherwise, that a procurement action will be issued. It is issued to invite industry to share their thoughts with the Government on training AI models for Army Programs.

No entitlement to payment by the Government of direct or indirect costs or charges will arise as a result of the submission of information in response to this request.

Information received will not be considered confidential/proprietary unless marked accordingly.

Company proprietary data will be reviewed by Government employees and authorized representatives only. The Government shall not be liable for or suffer any consequential damages for any improperly identified proprietary information. No award will be made as a result of this request. This request is for informational purposes only to promote exchanges of information with industry in accordance with Federal Acquisition Regulation (FAR) part 15.201. The Government

Intelligence Capabilities to Support Army Initiatives.

will not pay for any information and/or materials received in response to this request for information and is in no way obligated by the information received.

3. RESPONSE INSTRUCTIONS

Responses related to this Government issued RFI are due no later than 15 July 2024, 5:00pm (close of business) in the form of a whitepaper.

Responses shall be sent via email address to: usarmy.apg.peo-iews.mbx.linchpin@army.mil;

Subject Line: “Project Linchpin RF EW Capabilities to Support Army Initiatives RFI #5”.

The whitepaper should not exceed 7 pages, not including the cover. The whitepaper must address the following information requests listed below.

The Government is requesting the following information from Industry:

1. Please include the following Company overview information with your response:

a. Company name, NAICS, and CAGE code.

b. Company size and locations.

c. Traditional/non-traditional defense contractor.

d. Point of contact and email address.

2. A narrative that describes how the software solution will:

a. Satisfy each item in the desired capabilities and features listed in paragraph 5.

b. The ability to host the software solution in a virtual environment, to include a commercial cloud or fixed hardware. Please include CPU, RAM, and storage requirements for the software solution.

4. BACKGROUND

The Army’s pivot to Large-Scale Combat Operations (LSCO) has underscored a critical need for modernized electromagnetic warfare software capable of performing EW tasks at speed, to develop convergence by leveraging software-based technologies needed to achieve future decision domi-nance and overmatch against our adversaries. A key role of EW is to provide combat information to commanders at echelon enabling them to make rapid and accurate decisions. This is done through signal detection, identification and/or classification and location of friendly, neutral and adversary emitters operating in the electromagnetic spectrum to enable targeting with lethal and nonlethal effects.

5. REQUESTED INFORMATION

Use the following assumptions to answer the questions to the best of your knowledge. Please in-clude any additional assumptions or recommendations.

• Scope of work: Support 1x – medium sized AI project; roughly ~$7.5 to ~$15M which will cover multiple AI products, solutions, and services.

Intelligence Capabilities to Support Army Initiatives.

• There is limited to no labeled data available. Available data may sit at the Controlled Unclassified Information (CUI), SECRET and/or TOP SECRET level.

• Government provides the taxonomy for classification.

• Government securely manages the data (e.g. Government data doesn’t leave Government environments).

• Government manages the infrastructure, accreditation, onboarding.

• Government manages hybrid compute environment; cloud compute resources for projects should be estimated.

5.1. RF Data/Data Labeling

5.1.1. Please include specific solutions, products or tools, and services.

5.1.2. What is your company’s approach to Radio Frequency (RF) data management

(e.g. data acquisition, generation, storage, access, retrieval for model training)?

5.1.3. Does your company use synthetic RF data and if so how is it generated?

5.1.4. What is your approach for RF data labeling?

5.1.5. How many labelers are required to label data?

5.1.6. What skillset do the labelers need?

5.2. Model Training for RF Detection and Recognition

5.2.1. Please include specific solutions, products or tools, and services, and timeline to produce an initial model for operational feedback.

5.2.2. What is your company’s approach to training models?

5.2.3. What is your approach to fine-tuning models?

5.2.4. What open-source models do you leverage?

5.2.5. What non-open source pretrained models or frameworks do you leverage?

5.2.6. What open-source data sets do you leverage to train?

5.2.7. What is your approach for spoofing detection?

5.2.8. What initial models or frameworks would you like to have available

5.2.9. What is the minimum computing resource required to train a model using an en-terprise approach?

i. What is the recommended computing resource desired to train a model using an enterprise approach?

5.2.10. What is the minimum computing resource required to run model inference in a tactical environment?

i. What are the recommended computing resources desired to run model infer-ence in a tactical environment?

ii. What are your assumptions about the model parameters and model architec-ture for estimating compute needs and wants for inference in tactical envi-ronments?

5.2.11. What is the recommended team size to train models?

i. What skillset does each team member need?

5.3. Test & Evaluation (T&E)

5.3.1. What is your company’s T&E approach?

5.3.2. Does your approach include closed loop testing? (Yes/No)

i. If yes, how?

Intelligence Capabilities to Support Army Initiatives.

5.3.3. What tools do you use for T&E?

5.3.4. What assumptions do you make about operating environment for your T&E, e.g.

sandbox testing, congested electromagnetic environments, physical terrain?

i. What use cases do you assume for T&E?

5.3.5. What gaps do you see in RF/EW AI T&E capabilities?

5.3.6. What metrics does your leverage?

5.3.7. Does your approach include adversarial T&E? (Yes / No)

i. If yes, how?

5.3.8. What is the recommended team size for T&E?

5.3.9. What skillset does each team member need?

5.4. Cost, Contracting, and Intellectual Property (IP)

5.4.1. What is the annual cost and business model to deliver trained models?

5.4.2. What is your IP strategy, understanding that models will be continuously trained on Government data?

i. What does the Government own?

ii. What does industry own?

5.4.3. How should the Government contract for model training capabilities and services?

6. SUMMARY

To address these capability needs Project Linchpin is requesting information on radio fre-quency/electronic warfare object detection and recognition to support Army initiatives. Specifi-cally, Project Linchpin is interested in identifying companies to support enterprise model training with models integrated and deployed in various form fit factors in the tactical environment.

7. QUESTIONS

Questions regarding this announcement shall be submitted in writing by e-mail to usarmy.apg.peo-iews.mbx.linchpin@army.mil; Subject Line: “QUESTIONS: Project Linchpin RF EW Capabili-ties to Support Army Initiatives RFI #5”. Verbal questions will NOT be accepted. Questions will be answered by posting answers to the https://sam.gov; accordingly, questions shall NOT contain proprietary or classified information. The Government does not guarantee that questions received after 21 June 2024 will be answered. Interested parties are invited to subscribe to the website to ensure they receive any important information updates connected with this RFI.