Department of the navy (don) 18. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions introduction

TECHNOLOGY AREA(S): Battlespace, Information Systems, Sensors

ACQUISITION PROGRAM: Naval Oceanography Operations Command ASW Reach-Back Cell

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 5.4.c.(8) of the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.

OBJECTIVE: Develop and transition key building blocks of a Multi-Dimensional Ambient Noise Model.

DESCRIPTION: In light of an increasingly competitive undersea operational arena, the Navy is in need of a replacement for the current omni-directional ambient noise model. The envisioned replacement will be a Multi-Dimensional Ambient Noise Model that in full form predicts the vector and statistics of the temporally dependent ambient noise field as a function of location, direction, and season over a broad range of tactical frequencies (10s of Hz to 100s of kHz) and operational environments. The fully formed model will include a comprehensive understanding of sea surface, volume, and bottom noise generation, attenuation and propagation to the underwater sound field (included but not limited to: biologics, acoustic seafloor loss mechanisms, and scattering). Additionally, the model and supporting database will be formed and informed via data assimilation from multiple sources (included but not limited to: Automatic Identification System (AIS) data, marine weather, dedicated passive listening systems, and feeds from tactical Navy sensors).

Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. Owned and Operated with no Foreign Influence as defined by DOD 5220.22-M, National Industrial Security Program Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Security Service (DSS). The selected contractor and/or subcontractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances, in order to perform on advanced phases of this contract as set forth by DSS and ONR in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material IAW DoD 5220.22-M during the advance phases of this contract.

PHASE I: Develop a framework for a Multi-Dimensional Ambient Noise Model (MDANM). Analyze and specify the sonar or other data requirements necessary to develop and support it. In addition, provide details of the proposed techniques to be used to estimate one or more of the key MDANM parameters to include strategies for how this data can be obtained operationally. Identify architecture, protocols, and formats for MDANM output to the next-generation Submarine Tactical Decision Aid (STDA). Phase I should include plans for a prototype MDANM to be created in Phase II.

PHASE II: Using operational sonar or other measurement data, refine the methodology and conduct proof-of-concept demonstrations and tests to estimate one or more of the key MDANM parameters and the impact of the increased granularity (in location down to a 5-km scale and direction to 10 degrees) of the predicted noise field on the design and operation of a candidate operational sonar system. Develop partnerships with Program Executive Office Integrated Warfare Systems Undersea Systems (PEO IWS-5) and other stakeholders in development of next-generation tactical decision aid (Advanced Processer Build – 2021 - APB 21).

It is probable that the work under this effort will be classified under Phase II (see Description section for details).

PHASE III DUAL USE APPLICATIONS: The Phase III effort will require coordination with the Naval Surface Warfare Center, Carderock Division to add the MDANM to the STDA for submarines, and potentially to the Sonar Performance Predictions Functional Segment (SPPFS-STDA) for surface ship configurations and the STDA for Integrated Undersea Surveillance System (IUSS), or STDA-I, for surveillance systems.

REFERENCES:

1. Carey, W. M., J. W. Reese, et al. (1997). "Mid·frequency measurements of array signal and noise characteristics." IEEE J. Ocean. Eng. 22(3): 548-565.

2. Carey, W. M. and R. A. Wagstaff (1986). "Low-frequency noise fields." J. Acoust. Soc. Am. 80(5): 1522-1526.

3. Cox, H. (1973). "Spatial correlation in arbitrary noise fields with application to ambient sea noise." J. Acoust. Soc. Am. 54(5): 1289- 1301.

KEYWORDS: Noise; Sonar; Submarine; Sensor; Environment; Adaptive

TECHNOLOGY AREA(S): Human Systems, Information Systems

ACQUISITION PROGRAM: PMW 120, PMW 150, MC3, Future Integrated Training Environment (FNC)

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 5.4.c.(8) of the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.

OBJECTIVE: Objective is to mature a simulation capability that can play smart red forces against smart blue forces in order to develop decision support tools and reverse engineer legacy simulator entity behavioral and models to support “fair fights” (1). Entity behavior and models and one or more decision support tools will be “built” and verified by allowing an artificial intelligence (AI) capability to watch thousands of “games” played between smart agents (1). A condition when the differences between the performance characteristics of two or more interoperating simulations have significantly less effect on the outcome of a simulated situation than the actions taken by or resources available to the simulation participants.

DESCRIPTION: The goal of the topic is to develop warfighting decision support tools and reverse-engineering processes by allowing AI technology to observe automated smart red forces compete with smart blue forces within a simulation. Just as computer-based chess games are able to make optimal moves given the current state of the board and the most likely future state, a military decision support aid should suggest modifications to current plans and predict future outcomes given current content of the common tactical and intelligence picture. It is expected but not required that deep learning be used to learn optimal actions relative to a set of measures of effectiveness (MOEs) and measures of performance (MOPs).

Reverse-engineering processes are needed to develop accurate behavioral and entity models in legacy simulations. For example, over the past decade the Marine Corps has procured a number of individual simulator systems that are either proprietary in nature, or have dissimilar behavioral and entity models. As the Marine Corps moves towards a common architecture within a live, virtual, and constructive paradigm it is necessary that entities behaviors and models are normalized to ensure fair fights. Unlike chess boards, there are different representations of environments within each simulation that are used during virtual and constructive simulation. In is critical for training and wargaming that these representations have similar entity behaviors and models.

To generate adequate and relevant training data, the behaviors and models of actors in the simulation need to be controlled by smart agents that can run much faster than real time. The Phase I effort will be somewhat bounded, involving three agent platoons against three opposing platoons, each trying to secure an area of interest. Initial positions for the six units should be random. Other random variables should include weather, maneuver obstacles, terrain, equipment failures, and readiness levels. Both virtual and constructive simulators must be used. Performers can be sponsored for simulations (e.g., OneSAF) mission simulator if desired and needed.

Mission simulators are increasingly capable in terms of programmable behaviors and interactions. While AI software has been demonstrated to beat humans at games of increasing complexity (Tic-Tac-Toe to Go), agents have not been developed that can support decision making in the context of a military mission. Confounding this challenge, there are several legacy Marine Corps simulators that exist with different entity behaviors and models that are not easily configurable to interoperate.

Specific technical challenges include model normalization and model development relevant to a high-dimensional, continuous state space involving an adversarial agent.

Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. Owned and Operated with no Foreign Influence as defined by DOD 5220.22-M, National Industrial Security Program Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Security Service (DSS). The selected contractor and/or subcontractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances, in order to perform on advanced phases of this contract as set forth by DSS and ONR in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material IAW DoD 5220.22-M during the advance phases of this contract.

PHASE I: Determine feasibility for the development of an operationally relevant model normalization tools and a model based decision support tool. Conduct a detailed analysis of literature and commercial capabilities. For a bounded number of legacy models, actors, and behaviors, conduct a lab-based proof of concept demonstration. During the Phase I effort, performers are expected to identify metrics to verify performance of model normalization and decision support tools with the goal of reducing technical risk associated with building a working prototype, should work progress. Performers should produce Phase II plans with a technology roadmap and milestones for prototype development.

PHASE II: Produce a prototype system based on the preliminary design from Phase I. The prototype should enable human users to compete against agents or agents against each other within relevant Naval mission simulations. The system must be able to bring in legacy models for specific behaviors and entities. Additionally, the system must provide explanatory evidence for decision recommendations in terms of extrapolated measures of performance/effectiveness. The performance of agents will be measured by comparing simulation outcomes. During Phase II, the small business may be given specific scenarios by the Government to validate capabilities. An offeror should assume that the prototype system will need to run as a distributed application with a mature design for the human computer interface. Phase II deliverables will include a working prototype of the system (source code and executable), software documentation including a user’s manual, and a demonstration using a Naval operational scenario of interest.

It is probable that the work under this effort will be classified under Phase II (see Description section for details).

PHASE III DUAL USE APPLICATIONS: Produce a final prototype capable of deployment to training centers, operational command and control centers, and as a virtual application. The system should be adapted to transition as a component to a larger system or as standalone commercial product. The small business, working with transition and commercialization partners, should provide a means for performance evaluation with metrics for analysis (e.g., accuracy of decision support) and method for operator assessment of product interactions (e.g., display visualizations). The Phase III system should have an intuitive human computer interface. The software and hardware should be modified and documented in accordance with guidelines provided by engaged programs of record and commercial partners. Researchers are encouraged to publish Science and Technology (S&T) contributions.

Technology development will be applicable to the commercial gaming market, particularly to games with adversarial interaction involving a large, continuous feature space. The private sector also faces similar challenges with hierarchical modeling architectures that include legacy products.

REFERENCES:

1. Abar, S., et al. “Agent Based Modelling and Simulation tools: A review of the state-of-art software”, Computer Science Review 24 (2017) 13–33

2. Liebowitz, J. “Sharing the Solution”, Computers ind. Engng 16, NO. 4, pp. 587-593, 1989

3. Pan, Y. “Heading toward Artificial Intelligence 2.0”, Engineering 2 (2016) 409–413

4. Brynielsson, J. “Using AI and games for decision support in command and control”, Decision Support Systems 43 (2007) 1454–1463

5. DoD Modeling and Simulation Glossary. accessed on 25 June 2017. https://www.msco.mil/MSReferences/Glossary/TermsDefinitionsE-H.aspx

KEYWORDS: Artificial Intelligence; Warfighting Simulation; Modeling; Training; Agent Based Models; Gaming; Decision Support

N181-084

TITLE: Auditory Situation Awareness Training Tool

TECHNOLOGY AREA(S): Human Systems

ACQUISITION PROGRAM: PM – Infantry Combat Equipment, Ground Combat Element Systems Marine Corps SYSCOM (PM ICE GCES MCSC)

OBJECTIVE: Develop an auditory situation awareness (ASA) training-measurement system that will both measure and provide practice for the Marine warfighter and Naval ship deck crew member in maintaining auditory situation awareness when using tactical communication and protection systems (TCAPS), communications headsets, hearing protection devices (HPDs), or with the open ear.

DESCRIPTION: Although the Navy as well as other military branches recognizes the importance of providing appropriate HPDs, communications headsets and TCAPS to soldiers to prevent noise-induced hearing loss, currently there is neither a standard nor generally agreed-upon method to measure auditory situation awareness afforded by such devices, nor agreement on the elements such a test would include. This topic looks to develop such measurement techniques and contribute to the development of appropriate standards. It has been clearly demonstrated in several empirical human factors experiments that certain advanced HPDs and TCAPS compromise the wearer's auditory situation awareness, as compared to that provided by the open ear, for various tasks which may include detection, recognition/identification, localization, and pass-through communications (1,2,3,4). With these scientific data in hand which demonstrate the deleterious effects of certain HPDs and TCAPS on the hearing of signals and speech, it is now incumbent in future procurement of such devices to evaluate them with an objective test battery prior to selection and deployment. Furthermore, it is essential to train personnel who must accomplish missions which depend upon auditory situation awareness, about how to improve their situation awareness on multiple task elements with the open ear alone, and with a particular HPD or TCAPS which might be assigned to them. It has already been demonstrated in a recent dissertation experiment that the human hearing sense has "plasticity," and can indeed be trained to improve performance on complex localization and recognition/identification tasks, both with and without occlusion of the ear (5,6).

An ideal measurement-training system is anticipated to be a fully automated system that will provide an immersive simulation that employs both visual displays and auditory cues for the recognition/identification element and localization element of auditory situation awareness. The system should be operable by a Marine or Navy "trainee" who will be assigned a TCAPS or an HPD, and not require a laboratory experimenter or technician to oversee the measurement and training. The system should be able to stop/pause when the trainee reaches certain predetermined performance level, and provide continuous performance feedback at all times. Performance milestone criteria will be required in order to determine when the trainee can advance to the next level, or simply needs to be assigned a different product due to training difficulties. The system should also incorporate a modular design so that additional signals and background noises can be easily added after final system development, to render the system applicable to a variety of mission scenarios for which personnel training would be beneficial. The system should also include a software module to semi-automate the system's acoustical calibration.

The proposed training system's display must be auditory only (no visual strobe or other light displays). The auditory localization signals will be highly directional, and vectored toward the listener, so as to not disturb others in the vicinity. Signals are preferred to be at a supra-threshold level, to ensure reliable detection and then localization, but loud presentations are unnecessary and undesirable. Care must be taken in design not to disturb others who are in the vicinity. For this reason, both the to-be localized signals and any added background sounds will be presented at levels that are only slightly higher than that of ambient sound of the installation facility. The basic localization test signal sounds may be the composite signal sounds (as used in other test batteries), and should include both low and high frequency components to take advantage of interaural time and interaural level differences, respectively. Task/mission specific sounds are desirable as well. In addition to maintaining signal levels at supra-threshold but not disturbingly loud levels, the installation kit may employ sound absorbing curtains or lightweight baffles to limit sound leakage to nearby rooms.

The training system hardware and control laptop should be designed so that entire kit will fit into two "suitcase-style" standard aluminum or plastic storage cases, with a maximum size of 4ft L x 3ft W x 2ft H each. It is expected that the loudspeaker setup will be mounted on an expandable, gimbaled, telescoping, or other design that can be quickly "broken-down" into transportable configuration. Once assembled, which should require less than 15 minutes, followed by five minutes of calibration, the fully installed loudspeaker system should be less than about 6.5ft in diameter with a trainee seated at the center. Disassembly should require approximately the same amount of time as assembly.

The training-measurement system will provide immediate performance feedback with the goal of improving the wearer's auditory situation awareness, both with the open ear and while occluded with a TCAPS or HPD, in order to familiarize the user with the device and improve their situation awareness performance prior to deployment. The auditory situation awareness system must include objective, quantitative measurement on at least the tasks of auditory recognition/identification and localization. The system will afford introduction of various background noise spectra at different sound levels to simulate a variety of mission environments that are typically encountered by Marine and Naval personnel. The sound level of both background noise and the test-training signals will be adjustable so that multiple signal-to-noise ratios can be evaluated. For the recognition/identification task, the system should allow the use of highly realistic, mission-specific sounds that would be encountered in the environments of interest where HPDs or TCAPS may be employed. For the localization task, the system should provide measurement and training in both azimuthal plane (i.e., 360-degrees in horizontal) and frontal elevation. Loudspeakers should be arranged with at least 15-degrees of separation for both subtests. For both measurement and training purposes, the system will provide metrics of both accuracy (correctness of response) as well as response time, and immediate trial-by-trial feedback on both types of metrics will be seamlessly provided to the trainee during a testing-training session. The system will have the dual capability of being amenable to application for personnel training purposes or for device evaluation and procurement decisions, or both.

PHASE I: Demonstrate the feasibility of a training-measurement system that will measure performance, both accuracy and response time, for the recognition/identification and localization components of auditory situation awareness. This will be applicable to military trainees with HPDs, headsets, and TCAPS under at least 3 signal-to-noise ratios and various background noises, and compare the performance to the open ear. For the sound localization element, the system will measure at least 15-degrees of separation or smaller, in 360-degrees of azimuth and 60-degrees of frontal elevation. It should measure at least similar ASA task elements as in a prior-developed DRILCOM1 test battery or similar, and test various combinations of visual displays and control input devices. It shall establish situation awareness performance goals and milestones of performance. The outcomes of Phase I report will yield a Phase II developmental schedule that contains discrete milestones for actual system development and plans for a prototype in Phase II.

PHASE II: Develop a prototype training-measurement system that incorporates both visual and auditory displays in accordance with the Phase II developmental schedule created in Phase I. Conduct a full ergonomics task analysis review (i.e., not requiring human subject testing) to ensure the training system’s capabilities are accommodated, primarily by measuring inter-device differences via physical microphone-analyzer testing to ascertain the signals' acoustical characteristics in-situ. The training system should be fully automated and a user should be able to initiate the training program and finish without any major intervention/control from a trainer; this will also be subjected to a task analytic review. The system should include semi-automated calibration program that will enable calibration of the system by a minimally trained experimenter.

PHASE III DUAL USE APPLICATIONS: Develop a fully automated training system with a calibration program and hardware installation kit that is intended for use by an individual trainee on themselves for practice and learning purposes. The installation kit will enable installation of the training-measurement system by one having minimal technical skills in acoustics and without extensive effort. The modular program will allow future increments of the training scenarios and their associated performance metrics to accommodate training for various missions that could be encountered, making the system useful for a variety of military MOS (Military Occupation Specialties). The system will provide a means to train warfighters with various devices and with the open ear on the two auditory situation awareness tasks, and a means to measure the initial performance levels that soldiers with a device can be expected to achieve without any training.