HR001122S0016.pdf

Broad Agency Announcement

Fiddler

STRATEGIC TECHNOLOGY OFFICE

HR001122S0016

March 3, 2022

TABLE OF CONTENTS

PART I: OVERVIEW INFORMATION

PART II: FULL TEXT OF ANNOUNCEMENT

I. Funding Opportunity Description

A. Program Overview B. Program Metrics

II. Award Information A. General Award Information B. Fundamental Research

III. Eligibility Information A. Eligible Applicants B. Organizational Conflicts of Interest C. Cost Sharing/Matching D. Other Eligibility Criteria

IV. Application and Submission Information A. Address to Request Application Package B. Content and Form of Application Submission

V. Application Review Information A. Evaluation Criteria B. Review of Proposals

VI. Award Administration Information A. Selection Notices and Notifications B. Administrative and National Policy Requirements C. Reporting D. Electronic Systems

VII. Agency Contacts VIII. Other Information

IX. APPENDIX 1: PROPOSAL SLIDE SUMMARY

X. APPENDIX 2: CLASSIFIED ADDENDUM REQUEST FORM

XI. APPENDIX 3: VOLUME 1 COVER SHEET TEMPLATE

PART I: OVERVIEW INFORMATION

Federal Agency Name – Defense Advanced Research Projects Agency (DARPA), Strategic Technology Office (STO) Funding Opportunity Title – Fiddler Announcement Type –Initial announcement Funding Opportunity Number – HR001122S0016 Catalog of Federal Domestic Assistance Numbers (CFDA) Not applicable Dates o Posting Date: March 3, 2022 o Proposers Day: March 11, 2022 o Deadline to Request Classified Addendum: March 17, 2022 by 5:00 PM (EST) o Abstract Due Date and Time: March 24, 2022, by 5:00 PM (EDT) o Questions Due Date and Time: April 12, 2022 by 5:00 PM (EDT) o Deadline to Notify Security of Intent to Submit a Classified Proposal: April 29, 2022 by 5:00 PM (EDT) o Proposal Due Date and Time: May 6, 2022, by 5:00PM (EDT)

DARPA is soliciting innovative research proposals to develop novel algorithms that can rapidly create synthetic imagery of targets for training Automatic Target Recognition (ATR) algorithms that operate on Synthetic Aperture Radar (SAR) imagery. The effort will develop software that can train on a sparse set of SAR imagery of an object, such as a commercial ship, and use the results of that training to create imagery of the same object under different viewing conditions.

Anticipated individual awards – Multiple awards are anticipated.

Types of instruments that may be awarded – Procurement Contract or Other

Transaction Additional information: This program will be conducted at the Controlled Unclassified

Information (CUI) level and/or higher and only U.S. persons are allowed to work on this program. Proposers must request the BAA classified addendum, which includes the Fiddler Security Classification Guide (SCG), prior to submitting an abstract or a proposal. The classified addendum contains critical information necessary for an abstract or proposal response, and it is highly unlikely that a proposer will be successful without reviewing that document prior to any submission. See APPENDIX 2 of this BAA for instructions on how to request the Classified Addendum.

Agency contact Points of Contact

The BAA Coordinator for this effort can be reached at:

HR001122S0016@darpa.mil

DARPA/STO

ATTN: HR001122S0016

675 North Randolph Street Arlington, VA 22203-2114 mailto:HR001122S0016@darpa.mil

PART II: FULL TEXT OF ANNOUNCEMENT

I. Funding Opportunity Description

This publication constitutes a Broad Agency Announcement (BAA) as contemplated in Federal Acquisition Regulation (FAR) 6.102(d)(2) and 35.016 and 2 CFR § 200.203. Any resultant award negotiations will follow all pertinent law and regulation, and any negotiations and/or awards for procurement contracts will use procedures under FAR 15.4, Contract Pricing, as specified in the BAA.

Under Fiddler, the Defense Advanced Research Projects Agency (DARPA) is soliciting innovative proposals in the following technical areas: SAR, synthetic image generation, ATR, and image domain transfer. Proposed research should investigate innovative approaches that enable revolutionary advances in science, devices, or systems. Specifically excluded is research that primarily results in evolutionary improvements to the existing state of practice.

Proposers must request the BAA classified addendum, which includes the Fiddler Security Classification Guide (SCG), prior to submitting an abstract or a proposal. The classified addendum contains critical information necessary for an abstract or proposal response, and it is highly unlikely that a proposer will be successful without reviewing that document prior to any submission. See APPENDIX 2 of this BAA for instructions on how to request the Classified Addendum.

Proposers are strongly encouraged to submit an abstract in advance of a full proposal.

A. Program Overview

Background

Investments by the commercial and government sectors are leading to a rapid growth in earth-observation satellites and remote-sensing data. In particular, SAR can produce high-resolution images of the earth at night and in all-weather conditions. This unique imaging capability makes SAR particularly useful for time-critical applications including change-detection after natural disasters and identifying illegal fishing operations.

The objective of the Fiddler program is to improve automatic object recognition in SAR images.

Object recognition often requires significant examples to train machine learning (ML) classification algorithms. Obtaining training data can be time consuming, expensive, and even impossible in dynamic conditions.

The use of machine learning and computer vision methods to generate training data for dynamic maritime environments is of particular interest to this program. Performer methods will learn from real SAR images to generate or render synthetic SAR images at new imaging geometries and configurations. Performers will then demonstrate the generation of diverse training data from a few real examples, to rapidly train robust SAR object detection methods. Potential benefits to generating diverse training sets versus traditional methods are shown in Figure 1.

Figure 1. Benefits of Generated vs. Real Images

Maritime Challenges

SAR is a powerful tool that enables remote monitoring of the health and security of our oceans and coastal regions. Recently, the use of machine learning, and specifically convolutional neural networks, have demonstrated significant advances in maritime object detection in SAR images.

Once detected, machine learning methods have demonstrated some success at maritime object classification, but they remain brittle. Figure 2 shows examples of maritime object detection and types of objects that are routinely classified.

Machine learning methods rely on large numbers of example images to learn (train) to identify that object in future images. Object classification methods typically fail when asked to classify an object that is in a state that was not previously seen in the training data. For stationary objects, such as many terrestrial objects-of-interest, large training sets can be acquired over time to cover many of the possible imaging variations. Maritime environments are much more challenging because most objects-of-interest and the background scene are always in motion. This limits today’s classification techniques to broad classes of objects. In addition, many interesting applications of terrestrial SAR, such as change detection and optical-SAR registration, are not yet possible in maritime environments.

Figure 2. Examples of Maritime SAR Imaging1, Detection2, and Type Classification3

Software for Synthetic Image Generation

Performers will develop software and algorithms to produce diverse SAR-image training examples of an object from sparse real image examples. Splitting the training data generation and the subsequent machine-learning application is important for scaling this capability across new sensors and applications.

Figure 3. Block Diagram and Description of the Performer’s Software

Figure 3 outlines the software module to be developed. The internal structure of the software module will be defined by the performer. It is envisioned that it will contain the following portions:

Object learning portion that will learn relevant features of a new object from real SAR image examples. Examples could include statistical feature extraction, autoencoders, volumetric methods, and inverse imaging.

Object model that stores relevant information learned about the object. Examples could include a latent feature space, physical feature space, 3D point-cloud, coordinate-based neural representations, or surface models.

New image generation portion that will generate or render new SAR images at specific imaging parameters when requested. Examples could include generative networks, electromagnetic simulation, and neural rendering.

A common interface with the software module will be required to allow for testing and evaluation.

The interface will support initializing, loading examples, training, requesting new images, and storing current state. The specific details of the interface will be established early in the program’s

1 Image from https://www.esa.int/ESA_Multimedia/Images/2014/02/Sentinel-1_radar_modes 2 Kiruba K. "A Survey on Ship Detection in Remote Sensing Images" Journal of Analysis and Computation (JAC), Volume XII, Issue I, Jan-June 2019 3 Mengyuan Ma, "Ship Classification and Detection Based on CNN Using GF-3 SAR Images" Remote Sens. 2018, 10, 2043 https://www.esa.int/ESA_Multimedia/Images/2014/02/Sentinel-1_radar_modes execution. All complex SAR imagery used or created by this software will be in Sensor Independent Complex Data (SICD) or a similar common format.

Lack of training examples across large look-angles is often the major limiting factor for object recognition in SAR images. A simple example in Figure 4 shows the notional inputs and outputs of the software to produce new images of a ship at new look angles. In this case, the image is simply rotated, which has limited utility. The performer software would need to accurately produce an image that represents what the real SAR image at that look angle would be.

Figure 4. Ship Rotation Example

Synthetic Images and Synthetic Training Sets

Image generation already has utility in many applications, such as data visualization and emulation. But for Fiddler it could also generate SAR scenes at specific look angles and resolutions derived from other SAR images taken at fixed look-angles, resolutions, and frequencies. This would enable a more fluid interaction with the data instead of being confined to batch analyzing individual static images.

Under this program, performers will also develop an ATR algorithm to demonstrate the utility of synthetic image generation. The goal is to in increase the probability of correct identification.

Figure 5 gives the general process of comparing the performance difference of an ATR trained with and without synthetic training data. The “diverse image requests” input to the software (SW) module represents systematic calls to generate new images over diversity variables (angles, resolution, etc.). Additional variation to the test data can be added to include common motion and backgrounds (represented as the M and B pentagon blocks).

Figure 5. ATR Performance with and without Synthetic Training Images

Testing and Evaluation

The process in Figure 5 will measure the improvement (or decline) in performance of a single ATR when trained with the synthetic training data set. This metric will be calculated for other ATRs using the same data set to measure the portability of the solution to a variety of ATR methods. While this secondary metric will provide a general measure of utility for training any ATR, it will not be the primary measure of performance.

The primary measure of performance will be how well the synthetic image generation module can recreate a diverse data set from a sparse sampling of that data set. While qualitative and statistical metrics can be useful for measuring image quality and differences, they are not good metrics for measuring the utility of the generated data. To accomplish a quantitative evaluation, an ATR is used to classify images from both the original dataset and the synthetic dataset. The sampling and testing process for how well the performer software recreates the original data set as measured by an ATR is shown in Figure 6.

Figure 6. Software Sampling and Testing Process

In Figure 6, the top path will measure the performance of an ATR when tested with the synthetic dataset (shown as probability of identification PID1). The bottom path will measure the performance of an ATR when tested with the original real dataset (shown as probability of identification PID2). The normalized ratio (PID1 / PID2) will measure how well the synthetic data set accurately recreated the original data set as measured by that specific ATR. Note that it is possible to compute a normalized ratio that is greater than 1.

To ensure that the software creates synthetic imagery that is for training and testing a variety of ATR algorithms, the performer will repeat the processes described above for a suite of pre-trained ATR algorithms. The performer shall either supply a set of ATR algorithms or develop a set of suitable ATR algorithms. The Government will also provide a set of ATR algorithms.

In addition to normalized performance, the performer’s software will also be evaluated on the time it takes to learn a new object from examples and to produce new images. Fast generation of diverse training images will enable fast ATR development and deployment.

Test Harness and Data

A government test harness will automate the process shown in Figure 6 (and 5) for a variety of test conditions. It will batch process testing and evaluation to explore several important variables. For example, the percent of real data that is sampled and provided to the performer software for training is very important. This percent is data and scenario dependent so a target goal is not currently defined. The objective is to achieve the normalized PID of the phase (shown in Table 7) while using as little of the original data as possible.

The government test harness will be provided to the performer for their internal testing and evaluation. The Government will also perform independent evaluations which may include data and ATRs not provided to the performer.

Maritime environments are the primary focus of this program. Objects-of-interest include ships and other objects found in and around littoral waters such as breakwaters, wind farms, piers, ice, islands, and reefs. Terrestrial and coastal objects may also be explored as data sets become available.

Data will be post-detection in the form of image chips (X by Y), where X and Y can each range from 128 to 512 pixels. A variety of scenarios and objectives will be evaluated with the test harness. These can include object type identification, specific object identification, new object identification, etc. Testing scenarios will be developed with performer input once in program execution.

Program Phase Structure

This effort will be executed in three phases: a base period for Phase 1 and separately priced options for the Phase 2 period and the Phase 3 period. The activities in each phase are shown below:

Phase 1 – Images at any angle (15-month base effort)

• The performer will develop software that can train on a sparse set of SAR imagery of an object and create SAR imagery of the same object at any viewing angle.

Phase 2 – Images at any RF (12-month option)

• The performer will develop software that can train on a sparse set of SAR imagery of an object for a limited set of RF characteristics and create SAR imagery of the same object at any viewing angle and at any RF characteristics.

Phase 3 – Increased complexity (12-month option)

• The performer will mature methods that add more combinational complexity and reduce execution times.

Figure 7 depicts how the program will increase in the diversity that the software can support between Phase 1 and Phase 2. Target motion is unavoidable in maritime SAR and will be included throughout the program.

Figure 7. Increase in Diversity from Phase 1 to Phase 2

The program schedule is shown in Figure 8.

Figure 8. Program Schedule

Government Furnished Information (GFI)

The Government will provide an evaluation kit at the start of Phase 1 and will provide an updated version of the kit at the start of Phase 2. The evaluation kit will include the test harness and at least one government-provided ATR algorithm.

The Government will provide SAR imagery of maritime objects at the start of Phase 1 and an additional set of SAR imagery of maritime objects at the start of Phase 2.

DARPA anticipates that there will be multiple awards for the base period (Phase 1).

1. Phase 1

The performer will develop software that can train on a sparse set of SAR imagery of an object and then use that model to generate SAR imagery of the same object at user-specified viewing angles. In this phase the imagery used in testing will have been collected with the same RF characteristics as the sparse training data, where RF characteristics include center frequency, polarization, bandwidth, and cross-range resolution.

The performer will conduct trade studies to develop the processing approach, identify candidate algorithms and techniques for each software component, and conduct analyses and experiments to understand the capabilities and limitations of those candidate techniques to provide the desired component-level performance. Based on these tradeoffs the performer will develop the requirements for the software module.

The performer will present the software architecture and the flow-down of requirements to each software component at a Systems Requirements Review (SRR) three months after contract award. At this review the performer will describe the purpose of each software component and show how the overall system will meet the program metrics. The performer will also identify the key tradeoffs that were conducted to allocate the requirements to each component.

Based on the approach outlined at the SRR, the performer will develop the software Version 1 and conduct experimentation and testing as appropriate. The performer will document the algorithms in an Algorithm Description Document. The performer will deliver a sample set of SAR imagery generated by the initial version of the Phase 1 software for three different objects.

The imagery in the sample set will include a range of viewing angles.

The performers will present a summary of their progress and results at three quarterly program reviews held at month 6, month 9 and month 12 after contract award. At the 12th month quarterly program review, the performer will present a summary of their Phase 1 test and evaluation approach.

The performer will use the test harness to document performance in the Phase 1 final report. The performer will also present a summary of those results at the Phase 1 final review. The performer will deliver Version 1 of the software, including both the offline training module and the online SAR image generation model. The performer will also deliver executable or containerized versions of the ATR algorithms that were used in their Phase 1 assessment.

Additional Considerations

The proposal should describe the candidate algorithms and techniques that the performer proposes to consider during this effort. The proposal should describe the potential benefits and possible risks associated with each candidate algorithm or technique and discuss the analyses and experiments the performer will conduct in Phase 1 to determine which algorithms and techniques are suitable. The proposal should also provide an estimate of the processing resources required to support the proposed approaches.

The intention of this effort is to develop software that can be transitioned to other parts of the Department of Defense. The proposal should identify elements of the final software package for which they are asserting intellectual property rights or data rights restrictions. Those types of claims may restrict the Government's ability to transfer the software to third parties. If there are any such claims the proposal should describe approaches for ensuring that those restrictions will not limit the Government's ability to transition the technology developed under this program.

If the performer has a set of suitable ATR algorithms that they plan to use on this effort, the proposal should describe those algorithms and how they will be used throughout the program. If the set of ATR algorithms that the performer has available is not sufficient, the proposal should describe the ATR algorithms that the performer will develop on this effort and discuss how developing those ATR algorithms will support the program goals. The proposal should identify any data rights restrictions on the ATR algorithms. The use of ATR algorithms with data rights restrictions is acceptable so long as the software developed under this effort can be delivered without those restrictions.

The Phase 1 events are shown in Table 1 and the Phase 1 deliverables are shown in Table 2.

In both tables dates are given in terms of months After Contract Award (ACA).

Table 1. Phase 1 Events Event Venue Date

Phase 1 Kickoff DARPA 1 month ACA Government provides evaluation kit for Phase 1 assessment 1 N/A 1 month ACA

Government provides SAR imagery of maritime objects N/A 1 month ACA

Monthly telephone status updates Telephone As scheduled

System Requirements Review At performer facility or DARPA 3 months ACA

Quarterly Program Review 1 At performer facility or DARPA 6 months ACA

Quarterly Program Review 2 At performer facility or DARPA 9 months ACA

Quarterly Program Review 3 At performer facility or DARPA 12 months ACA

Version 1 software testing At performer facility 14 months ACA

Phase 1 Final Review At performer facility or DARPA 15 months ACA

Table 2. Phase 1 Deliverables Deliverable Due Date Science & Technology Protection Implementation Plan (Draft) With submission of proposal Presentation materials from Kickoff Meeting 24 hours in advance Technical and financial monthly status reports Monthly System Requirements Review (SRR) presentation materials 3 months ACA

Phase 1 Algorithm Description Document for the offline training and online image generation software modules

6 months ACA

Sample set of SAR imagery generated by the initial version of the Phase 1 software.

7 months ACA

Presentation materials from the three Quarterly Reviews (QPRs) 24 hours in advance Version 1 of the software 14 months ACA Executable or containerized version of the ATR algorithm(s) that the performer used in their Phase 1 assessment

15 months ACA

Phase 1 Final Report 15 months ACA

2. Phase 2

In Phase 2 the performer will advance the software to enable it to create SAR imagery at user-specified viewing angles and user-specified RF characteristics for a wide range of RF characteristics. The performer will measure performance using the approach described in this BAA. The imagery used in testing will include imagery collected with RF characteristics that were not in the sparse training data. The performer will deliver Version 2 of the offline training software and the online training software to the Government.

The performer will conduct trade studies to develop the processing approach and identify candidate algorithms and techniques needed to extend the software to support generating imagery for a wide range of RF characteristics. Based on these tradeoffs, the performer will develop the requirements for each software component.

The performer will present the software architecture and the flow-down of requirements to each software component in a Systems Requirements Review (SRR) for the Phase 2 software three months after option award. At this review the performer will describe the purpose of each new software component and show how the overall system will meet the Phase 2 program metrics.

The performer will also identify the key tradeoffs that were conducted to allocate the requirements to each component.

Based on the approach outlined at the SRR, the performer will develop software Version 2 and conduct experimentation and testing as appropriate. The performer will document the algorithms in an Algorithm Description Document that describes the new algorithms that were developed to enable the software to support generating imagery of a wide range of RF characteristics. The performer will deliver a sample set of SAR imagery generated by the initial version of the Phase 2 software for three different objects. The imagery will include a range of viewing angles and a range of RF characteristics.

The performers will present a summary of their progress and results at two quarterly reviews held at month 6 and month 9 after contract award. At the quarterly program review at month 9, the performer will present a summary of their Phase 2 test and evaluation approach.

The performer will use the test harness to measure performance of Version 2 of the software and document the results in the Phase 2 final report. The performer will also present a summary of those results at the Phase 2 final review, The performer will deliver Version 2 of the software, including both the offline training module and the online SAR image generation model. The performer will also deliver executable or containerized versions of any new ATR algorithms that the performer used in their Phase 2 assessment.

Additional Considerations

The proposal should describe the challenges with generating imagery for a wide range of RF characteristics, some of which will not be in imagery in the training data. The proposal should describe the candidate algorithms and techniques that the performer proposes to consider in Phase 2. The proposal should describe the potential benefits and possible risks associated with each candidate algorithm or technique and discuss analyses and experiments the performer will use in Phase 2 to determine which algorithms and techniques are suitable. The proposal should also provide an estimate of the processing resources required to support the proposed approaches.

The Phase 2 events are shown in Table 3, and the Phase 2 deliverables are shown in Table 4. In these tables, dates are given in terms of months After Option Award (AOA).

Table 3. Phase 2 Events Event Venue Date

Phase 2 Kickoff DARPA 1 month AOA Government provides evaluation kit for Phase2 assessment 1 N/A 1 month AOA

Government provides additional SAR imagery of maritime objects N/A 1 month AOA

Monthly telephone status updates Telephone As scheduled Phase 2 Software Development Requirements

Review At performer facility or

DARPA 2 months AOA

Quarterly Program Review 1 At performer facility or DARPA 6 months AOA

Quarterly Program Review 2 At performer facility or DARPA 9 months AOA

Version 2 software testing At performer facility 11 months AOA

Phase 2 Final Review At performer facility or DARPA 12 months AOA

Table 4. Phase 2 Deliverables Deliverable Due Date Presentation materials from Kickoff Meeting 24 hours in advance

Science & Technology Protection Implementation Plan (Update) 1 month AOA

Phase 2 Software Development Requirements Review presentation materials

3 months AOA

Phase 2 Algorithm Description Document for the offline training and online image generation software modules

6 months AOA

Sample set of SAR imagery generated by the initial version of the Phase 2 software.

6 months AOA

Presentation materials from the two Quarterly Reviews (QPRs) 24 hours in advance Version 2 of the software 11 months AOA Executable or containerized version any new ATR algorithm(s) that the performer used in their Phase 2 assessment

12 months AOA

Phase 2 Final Report 12 months ACA

3. Phase 3

The performer will extend software to enable it to create SAR imagery of situations with higher complexity than the Version 2 software. The performer will measure performance using the approach described in this BAA. The performer will deliver Version 3 of the offline training software and the online training software to the Government.

The Phase 3 events are shown in Table 5, and the Phase 3 deliverables are shown in Table 6. In these tables, dates are given in terms of months After Option Award (AOA).

Table 5. Phase 3 Events Event Venue Date

Phase 3 Kickoff DARPA 1 month AOA Government provides SAR imagery of maritime objects for a range of sensor configurations with higher complexity than Phase 2 N/A 1 month AOA

Monthly telephone status updates Telephone As scheduled Phase 3 Software Development Requirements

Review At performer facility or DARPA 2 months AOA

Quarterly Program Review 1 At performer facility or DARPA 6 months AOA

Quarterly Program Review 2 At performer facility or DARPA 9 months AOA

Version 3 software testing At performer facility 11 months AOA

Phase 3 Final Review At performer facility or DARPA 12 months AOA

Table 6. Phase 3 Deliverables Deliverable Due Date Presentation materials from Kickoff Meeting 24 hours in advance

Science and Technology Protection Implementation Plan (Update) 1 month AOA Phase 3 Software Development Requirements Review Presentation Materials

3 months AOA

Phase 3 Algorithm Description Document for the offline training and online image generation software modules

6 months AOA

Sample set of SAR imagery generated by the initial version of the Phase 3 software.

6 months AOA

Presentation materials from the two Quarterly Reviews (QPRs) 24 hours in advance Version 3 of the software 11 months AOA Executable or containerized version of any new ATR algorithm(s) that the performer used in their Phase 3 assessment

12 months AOA

Phase 3 Final Report 12 months ACA

B. Program Metrics

In order for the Government to evaluate the effectiveness of a proposed solution in achieving the stated program objectives, the Government will use the program metrics in Table 7 (primary) and Table 8 (secondary) as the basis for determining whether satisfactory progress is being made to warrant continued funding of the program. The Government has identified these goals with the intention of bounding the scope of effort, while affording the maximum flexibility, creativity, and innovation in proposing solutions to the stated problem.

The Government may make changes to the program metrics and/or goals over the course of the program based on information gained as a result of the research and development or to ensure that the metrics and goals are sufficient to deliver meaningful operational capability.

Table 7. Performance Metrics Metric Phase 1 Phase 2 Phase 3 Normalized Probability of correct Identification (PID), as measured by the government team

>80% >90% >95%

Time required to learn a new object model

48 hours 12 hours 1 hour

Time to generate new image <10 seconds <1.0 seconds <0.1 seconds

Table 8. Secondary Performance Metrics Metric Note Percent performance improvement when training an ATR with synthetic data compared to only original data

See section on Synthetic Training Sets.

This metric is data and scenario dependent.

In general, higher is better.

Percent of data required to meet primary normalized PID metric in table 7

See section on Test Harness and Data This metric is data and scenario dependent.

In general, lower is better.

II. Award Information

A. General Award Information

Multiple awards are anticipated. The amount of resources made available under this BAA will depend on the quality of the proposals received and the availability of funds.

The Government reserves the right to select for negotiation all, some, one, or none of the proposals received in response to this solicitation and to make awards without discussions with proposers. The Government also reserves the right to conduct discussions if it is later determined to be necessary. If warranted, portions of resulting awards may be segregated into pre-priced options. Additionally, DARPA reserves the right to accept proposals in their entirety or to select only portions of proposals for award. In the event that DARPA desires to award only portions of a proposal, negotiations may be opened with that proposer. The Government reserves the right to fund proposals in phases with options for continued work, as applicable.

The Government reserves the right to request any additional, necessary documentation once it makes the award instrument determination. Such additional information may include but is not limited to Representations and Certifications (see Section VI.B.2., “Representations and Certifications”). The Government reserves the right to remove proposers from award consideration should the parties fail to reach agreement on award terms, conditions, and/or cost/price within a reasonable time, and the proposer fails to timely provide requested additional information. Proposals identified for negotiation may result in a procurement contract, or Other Transaction, depending upon the nature of the work proposed, the required degree of interaction between parties, whether or not the research is classified as Fundamental Research, and other factors.

Proposers looking for innovative, commercial-like contractual arrangements are encouraged to consider requesting Other Transactions. To understand the flexibility and options associated with Other Transactions, consult http://www.darpa.mil/work-with-us/contract-management#OtherTransactions.

In accordance with 10 U.S.C. § 4003(f), the Government may award a follow-on production contract or Other Transaction (OT) for any OT awarded under this solicitation if: (1) that participant in the OT, or a recognized successor in interest to the OT, successfully completed the entire prototype project provided for in the OT, as modified; and (2) the OT provides for the award of a follow-on production contract or OT to the participant, or a recognized successor in interest to the OT.

In all cases, the Government contracting officer shall have sole discretion to select award instrument type, regardless of instrument type proposed, and to negotiate all instrument terms and conditions with selectees. DARPA will apply publication or other restrictions, as necessary, if it determines that the research resulting from the proposed effort will present a high likelihood of disclosing performance characteristics of military systems or manufacturing technologies that are unique and critical to defense. Any award resulting from such a determination will include a requirement for DARPA permission before publishing any information or results on the http://www.darpa.mil/work-with-us/contract-management#OtherTransactions program. For more information on publication restrictions, see the section below on Fundamental Research

B. Fundamental Research

It is DoD policy that the publication of products of fundamental research will remain unrestricted to the maximum extent possible. National Security Decision Directive (NSDD) 189 defines fundamental research as follows:

‘Fundamental research’ means basic and applied research in science and engineering, the results of which ordinarily are published and shared broadly within the scientific community, as distinguished from proprietary research and from industrial development, design, production, and product utilization, the results of which ordinarily are restricted for proprietary or national security reasons.

As of the date of publication of this solicitation, the Government expects that program goals as described herein either cannot be met by proposers intending to perform fundamental research or the proposed research is anticipated to present a high likelihood of disclosing performance characteristics of military systems or manufacturing technologies that are unique and critical to defense. Therefore, the Government anticipates restrictions on the resultant research that will require the awardee to seek DARPA permission before publishing any information or results relative to the program.

Proposers should indicate in their proposal whether they believe the scope of the research included in their proposal is fundamental or not. While proposers should clearly explain the intended results of their research, the Government shall have sole discretion to determine whether the proposed research shall be considered fundamental and to select the award instrument type. Appropriate language will be included in resultant awards for non-fundamental research to prescribe publication requirements and other restrictions, as appropriate. This language can be found at http://www.darpa.mil/work-with-us/additional-baa.

For certain research projects, it may be possible that although the research to be performed by a potential awardee is non-fundamental research, its proposed subawardee’s effort may be fundamental research. It is also possible that the research performed by a potential awardee is fundamental research while its proposed subawardee’s effort may be non-fundamental research.

In all cases, it is the potential awardee’s responsibility to explain in its proposal which proposed efforts are fundamental research and why the proposed efforts should be considered fundamental research.

III. Eligibility Information

A. Eligible Applicants

All responsible sources capable of satisfying the Government's needs may submit a proposal that shall be considered by DARPA.

http://www.darpa.mil/work-with-us/additional-baa

Organizations proposing as prime contractors must have a facility clearance (FCL) at the Secret level or higher at the time of proposal submission due to the classified data to be handled on the program. Organizations without an FCL may be on a proposal team as a subcontractor.

1. Federally Funded Research and Development Centers (FFRDCs) and Government Entities

a) FFRDCs FFRDCs are subject to applicable direct competition limitations and cannot propose to this solicitation in any capacity unless they meet the following conditions. (1) FFRDCs must clearly demonstrate that the proposed work is not otherwise available from the private sector. (2) FFRDCs must provide a letter, on official letterhead from their sponsoring organization, that (a) cites the specific authority establishing their eligibility to propose to Government solicitations and compete with industry, and (b) certifies the FFRDC’s compliance with the associated FFRDC sponsor agreement’s terms and conditions. These conditions are a requirement for FFRDCs proposing to be awardees or subawardees.

b) Government Entities Government Entities (e.g., Government/National laboratories, military educational institutions, etc.) are subject to applicable direct competition limitations. Government Entities must clearly demonstrate that the work is not otherwise available from the private sector and provide written documentation citing the specific statutory authority and contractual authority, if relevant, establishing their ability to propose to Government solicitations and compete with industry. This information is required for Government Entities proposing to be awardees or subawardees.

c) Authority and Eligibility At the present time, DARPA does not consider 15 U.S.C. § 3710a to be sufficient legal authority to show eligibility. While 10 U.S.C.§ 4892 may be the appropriate statutory starting point for some entities, specific supporting regulatory guidance, together with evidence of agency approval, will still be required to fully establish eligibility. DARPA will consider FFRDC and Government Entity eligibility submissions on a case-by-case basis; however, the burden to prove eligibility for all team members rests solely with the proposer.

2. Other Applicants Non-U.S. organizations and/or individuals may participate to the extent that such participants comply with any necessary nondisclosure agreements, security regulations, export control laws, and other governing statutes applicable under the circumstances.

B. Organizational Conflicts of Interest

FAR 9.5 Requirements

In accordance with FAR 9.5, proposers are required to identify and disclose all facts relevant to potential OCIs involving the proposer’s organization and any proposed team member (subawardee, consultant). Under this Section, the proposer is responsible for providing this disclosure with each proposal submitted to the solicitation. The disclosure must include the proposer’s, and as applicable, proposed team member’s OCI mitigation plan. The OCI mitigation plan must include a description of the actions the proposer has taken, or intends to take, to prevent the existence of conflicting roles that might bias the proposer’s judgment and to prevent the proposer from having unfair competitive advantage. The OCI mitigation plan will specifically discuss the disclosed OCI in the context of each of the OCI limitations outlined in FAR 9.505-1 through FAR 9.505-4.

Agency Supplemental OCI Policy

In addition, DARPA has a supplemental OCI policy that prohibits contractors/performers from concurrently providing Scientific Engineering Technical Assistance (SETA), Advisory and Assistance Services (A&AS) or similar support services and being a technical performer.

Therefore, as part of the FAR 9.5 disclosure requirement above, a proposer must affirm whether the proposer or any proposed team member (subawardee, consultant) is providing SETA, A&AS, or similar support to any DARPA office(s) under: (a) a current award or subaward; or (b) a past award or subaward that ended within one calendar year prior to the proposal’s submission date.

If SETA, A&AS, or similar support is being or was provided to any DARPA office(s), the proposal must include:

The name of the DARPA office receiving the support;

The prime contract number;

Identification of proposed team member (subawardee, consultant) providing the support; and

An OCI mitigation plan in accordance with FAR 9.5.

Government Procedures

In accordance with FAR 9.503, 9.504 and 9.506, the Government will evaluate OCI mitigation plans to avoid, neutralize or mitigate potential OCI issues before award and to determine whether it is in the Government’s interest to grant a waiver. The Government will only evaluate OCI mitigation plans for proposals that are determined selectable under the solicitation evaluation criteria and funding availability.

The Government may require proposers to provide additional information to assist the Government in evaluating the proposer’s OCI mitigation plan.

If the Government determines that a proposer failed to fully disclose an OCI; or failed to provide the affirmation of DARPA support as described above; or failed to reasonably provide additional information requested by the Government to assist in evaluating the proposer’s OCI mitigation plan, the Government may reject the proposal and withdraw it from consideration for award.

C. Cost Sharing/Matching

Cost sharing is not required; however, it will be carefully considered where there is an applicable statutory condition relating to the selected funding instrument. Cost sharing is encouraged where there is a reasonable probability of a potential commercial application related to the proposed research and development effort.

For more information on potential cost sharing requirements for Other Transactions for Prototype, see http://www.darpa.mil/work-with-us/contract-management#OtherTransactions.

D. Other Eligibility Criteria

The Government requires that proposers maintain facility clearance requirements in order to receive an award. Potential performers will be selected, in part, based on their capability to perform and their security facilities.

IV. Application and Submission Information

A. Address to Request Application Package

This announcement, any attachments, and any references to external websites herein constitute the total solicitation. If proposers cannot access the referenced material posted in the announcement found at www.darpa.mil, contact the administrative contact listed herein.

B. Content and Form of Application Submission

All submissions, including abstracts and proposals must be written in English with type not smaller than 12-point font. Smaller font may be used for figures, tables, and charts. Copies of all documents submitted must be clearly labeled with the DARPA BAA number, proposer organization, and proposal title/proposal short title.

1. Abstract Format

Proposers are strongly encouraged to submit an abstract in advance of a full proposal. The cover sheet should be clearly marked “ABSTRACT,” and the total length should not exceed 7 pages.

The maximum page count excludes the cover page and official transmittal letter but does include any figures, tables, and charts. Official transmittal letter is not required.

Proposers must request the BAA classified addendum, which includes the Fiddler Security Classification Guide (SCG), prior to submitting an abstract or a proposal. The classified addendum contains critical information necessary for an abstract or proposal response, and it is highly unlikely that a proposer will be successful without reviewing that document prior to any submission. See APPENDIX 2 of this BAA for instructions on how to request the Classified Addendum.

Cover sheet to include:

1. BAA number HR001122S0016

2. Technical area: N/A

3. Lead organization submitting proposal http://www.darpa.mil/

4. Type of organization, selected among the following categories: "LARGE

BUSINESS," "SMALL DISADVANTAGED BUSINESS," "OTHER SMALL

BUSINESS," "HBCU," "MI," "OTHER EDUCATIONAL,” or "OTHER

NONPROFIT"

5. Proposer’s reference number (if any)

6. Other team members (if applicable) and type of organization for each

7. Abstract title

8. Technical point of contact to include: salutation, last name, first name, street address, city, state, zip code, telephone, fax (if available), email (if available)

9. Administrative point of contact to include: salutation, last name, first name, street address, city, state, zip code, telephone, fax (if available), email (if available)

10. Estimated funds requested from DARPA for each phase proposed and the total estimated proposed cost; and the amount of cost share (if any)

11. Date abstract was prepared.

There is no required format for the abstract except that it must not exceed 7 pages. Here is an example abstract structure.

{4 pages} Summary of Innovative Claims and Technical Approach:

Succinctly describe the uniqueness and benefits of the proposed approach relative to the current state-of-art and alternative approaches. Describe the technical rationale, technical approach, and constructive plan for accomplishments of technical goals in support of innovative claims, and deliverable production should be summarized. Highlight any related work and how that compares with the proposed effort.

{2 pages} Milestones, Costs, Team

Summarize organization, teaming arrangements, key personnel, and related research. Summarize estimated costs and milestones for the proposed research.

{1 page} Summary of Deliverables and Approach to Intellectual Property:

Deliverables associated with the proposed research and the plans and capability to accomplish technology transition and commercialization. Include in this section all proprietary claims to results, prototypes, intellectual property, or systems supporting and/or necessary for the use of the research, results, and/or prototype. If there are no proprietary claims, this should be stated.

This section should list all technical data, computer software, or computer software documentation to be provided with other than unlimited rights in accordance with DFARS Clause 252.227-7017 IDENTIFICATION AND ASSERTION OF USE, RELEASE, OR

DISCLOSURE RESTRICTIONS (JUNE 1995).

2. Proposal Format

Proposers must request the BAA classified addendum, which includes the Fiddler Security Classification Guide (SCG), prior to submitting an abstract or a proposal. The classified addendum contains critical information necessary for an abstract or proposal response, and it is highly unlikely that a proposer will be successful without reviewing that document prior to any submission. See APPENDIX 2 of this BAA for instructions on how to request the Classified Addendum.

All proposals must be in the format given below. The typical proposal should express a consolidated effort in support of one or more related technical concepts or ideas. Disjointed efforts should not be included into a single proposal. Proposals shall consist of two volumes: 1) Volume I, Technical and Management Proposal (composed of 3 parts), and 2) Volume II, Cost Proposal. Bracketed numbers before each section denote recommended page limits.

NOTE: Non-conforming submissions that do not follow the instructions herein may be rejected without further review.

a) Volume I, Technical and Management Proposal

(1) Section I: Administrative

(a) Cover Sheet to Include

(1) BAA number; HR001122S0016

(2) Technical area; N/A

(3) Lead Organization submitting proposal;

(4) Type of organization, selected among the following categories: “LARGE BUSINESS”, “SMALL DISADVANTAGED BUSINESS”, “OTHER SMALL BUSINESS”, “HBCU”, “MI”, “OTHER EDUCATIONAL”, OR “OTHER NONPROFIT”;

(5) Proposer’s reference number (if any);

(6) Other team members (if applicable) and type of organization for each;

(7) Proposal title;

(8) Technical point of contact to include: salutation, last name, first name, street address, city, state, zip code, telephone, fax (if available), electronic mail (if available);

(9) Administrative point of contact to include: salutation, last name, first name, street address, city, state, zip code, telephone, fax (if available), electronic mail (if available);

(10) Total funds requested from DARPA, and the amount of cost share (if any); AND

(11) Date proposal was submitted.

(b) Official transmittal letter

(2) Section II: Summary of Proposal

A. {3 pages} Technical rationale, technical approach, and constructive plan for accomplishment of technical goals in support of innovative claims and deliverable creation. (In the full proposal, this section should be supplemented by a more detailed plan in Section III of the Technical and Management Proposal.)

B. {2 pages} Innovative claims for the proposed research. This section is the centerpiece of the proposal and should succinctly describe…