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

2. Iwamiya, R., Mumm, H., Ollerton, B., Riegle, B., and Colket, C. “CMS-2 to Ada Translator Evaluation Final Report.” Handle.dtic.mil. Technical Document 2984 September 1997, NRAD and SPAWAR. 30 March 2017. http://www.dtic.mil/get-tr-doc/pdf?AD=ADA331889

KEYWORDS: CMS-2Y Computer Software Language for Tactical Operations; X86 COTS Hardware; Linux Operating System in the ATB; CMS-2Y Tactical Code; Emulation, Virtualization, and Compilation Using Open Source Code; Critical Updates of AEGIS

N181-031

TITLE: AEGIS Combat System Optimization through Advanced Modeling of Software-Only Changes

TECHNOLOGY AREA(S): Battlespace, Electronics, Sensors

ACQUISITION PROGRAM: Program Executive Office Integrated Warfare System (PEO IWS) 1.0 – AEGIS Combat System.

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 modeling and analysis software to optimize software-only changes in the Anti-Air Warfare (AAW) system design to address new re-designs of Anti-Ship Cruise Missiles (ACSMs) threats.

DESCRIPTION: U.S. Navy AEGIS surface combatants must consistently upgrade their system software and design to pace the threat. A cost-effective method to optimize combat system designs uses modeling platforms to characterize and test various software and hardware configurations as well as proposed changes to the combat system. While models exist, and can go into extensive detail on radar detection and tracking performance and missile performance, there are continuous threat upgrades that exploit vulnerabilities in system design. Combat system development must be able to quickly optimize and overcome failures in combatting these threats effectively and efficiently. Tweaks in AEGIS Combat System (ACS) design, including missile guidance, seeker pointing, illumination design, and other shipboard combat system controls, can provide quick software-only fixes that provide large gains in overall AEGIS performance against the latest ASCM threats. In this manner, the AAW combat capability of the ACS can be improved via software-only upgrades. Software optimization of AAW weapons and components such as Evolved Sea Sparrow Missile (ESSM), Standard Missile (SM-2), Close-in Weapons System (CIWS), Electronic Warfare (EW) systems, and other ACS elements, could result in the upgrade of the ACS in a cost-effective manner. Current upgrade processes involve man-driven engineering analysis to determine the best options for inserting new upgrades or system improvements. This process is manual, labor intensive, and has inputs from disconnected sources driving the timeline associated with analysis and decisions for software insertions. Because the AAW system is a highly complex system with multiple interactions, human cognitive processing lacks the ability to perform the necessary calculations to provide the best software upgrade recommendations. The Navy seeks to automate current processes and make them more data-driven to field capability as quickly as possible, make the most optimal improvements to AAW within the capabilities of the Navy’s current weapons, and provide integrated data analysis to enable better integrate and ensure performance of future weapons.

A software tool that integrates outputs of current and future models and uses goal-seeking behaviors to improve recommendations for software-only optimization of the AAW capability within the ACS is needed. It will integrate with the AEGIS Test Bed (ATB) to facilitate system evaluation against more advanced and prolific threats. This will enable shortening of testing and certification timelines for new AEGIS baselines as compared to current timelines. This tool shall allow for small tweaks to current design parameters such as missile guidance, seeker pointing, illumination design, and other shipboard combat system controls, such that rapid prototyping of AEGIS design and software upgrade recommendations can occur within days versus weeks or months as in the current process. Design parameters affecting performance metrics including Miss Distance, Probability of Kill, and Probability of Raid Annihilation should be integrated within the tool such that a direct link is established between software design modifications and AAW/ACS system performance. The software tool will need to run 100,000 simulations at a time and use that data to recommend optimized changes to software parameters for AAW design to improve performance metrics for Miss Distance and Probability of Kill by 10% and close the gap in the Probability of Raid Annihilation (PRA) by 10%.

This technology will enable computer-aided optimization of AEGIS design and provide better capability from current designs, saving lifecycle costs for AEGIS in the future. The only alternative is performing this optimization of Combat System performance manually, which would be cost-prohibitive. This topic enables a cost-effective way to optimize and avoids future lifecycle upgrade costs.

The Phase II effort will likely require secure access, and NAVSEA will process the DD254 to support the contractor for personnel and facility certification for secure access. The Phase I effort will not require access to classified information. If need be, data of the same level of complexity as secured data will be provided to support Phase I work.

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 NAVSEA 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: Define and develop a concept for modeling and analysis software to provide recommendations for software-only changes in the AAW system design to address new re-designs of ACSMs threats. The concept must show it will feasibly support the test environments identified in the Description. Feasibility will be established through assessment of the approaches to provide recommendations in reduced timelines, to accurately represent the performance metric improvements driven by proposed software only changes, and the approach to integrate the capability into the ATB environment. The Government will provide access to the ATB environment. Also develop a Plan of Action and Milestones (POA&M) to design, develop, validate, and integrate the proposed software application into the AEGIS combat system test environments. The Phase I Option, if awarded, will include the initial design specifications and capabilities description to build a prototype system in Phase II. Develop a Phase II plan.

PHASE II: Based on the results of Phase I and the Phase II Statement of Work (SOW), design, develop and deliver a prototype modeling and simulation software tool for recommending software-only design changes to the AAW system. Implement the prototype into an existing Government-approved modeling and simulation environment such as the ATB to validate performance. The prototype system must be capable of demonstrating the implementation and integration into the AAW weapons and components such as Evolved Sea Sparrow Missile (ESSM), Standard Missile (SM-2), Close-in Weapons System (CIWS), Electronic Warfare (EW) systems, and other ACS elements as described in the Description. The demonstration will be conducted in a Government-provided facility. The company will prepare a Phase III development plan to transition the technology for Navy use and Program of Record.

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: Support the Government in transitioning the technology to Navy use and allow for further experimentation and refinement. The contractor will validate the possible upgrades to system design via optimization and recommend those designs for fielding. Implementation will be a fully functional software tool for the ACS.

Optimization of this type of software systems can be utilized in factories that incorporate varying production and delivery schedules.

REFERENCES:

1. Li, X., Fu, S., and Fan, H. “Optimization of an Advanced Guidance Scheme for Long-Range AAMs Based on SPSO.” Sun Z., Deng Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 254. Springer, Berlin, Heidelberg 23 March 2017. http://link.springer.com/chapter/10.1007/978-3-642-38524-7_38

2. Zhijun, Li, Yuanqing, Xia, Chun-Yi, Su, Jun, Deng, Jun, Fu, and Wei, He. “Missile Guidance Law Based on Robust Model Predictive Control Using Neural-Network Optimization.” 23 March 2017. https://www.researchgate.net/publication/265473271_Missile_Guidance_Law_Based_on_Robust_Model_Predictive_Control_Using_Neural-Network_Optimization

KEYWORDS: Combat Capability of AEGIS; Better Pace ACSM Threats; Software-only Upgrades for AAW systems; Complex AAW; Standard Missile; ESSM

N181-032

TITLE: Electroactive Polymer Actuators for Unmanned Undersea and Surface Vehicles

TECHNOLOGY AREA(S): Ground/Sea Vehicles

ACQUISITION PROGRAM: PMS 485, Maritime Surveillance Systems Program Office

OBJECTIVE: Develop and demonstrate an electroactive polymer-based rotary actuator that can survive high levels of shock (5 to 10 g) on any of the three-axis while also being compact (less than 15mm diameter), sealed against seawater at 1000m depth, and operable with low power consumption (less than 0.25A at 12 VDC).

DESCRIPTION: The purpose of this project is to develop and demonstrate the use of electroactive polymer (EAP)-based actuators for Unmanned Undersea and Surface Vehicles (UxV) control surfaces in a high sea-state ocean environment. Unlike conventional surface ships, UxVs are expected to survive and operate in (rather than retreat from) extreme ocean environmental conditions (World Meteorological Organization (WMO) sea-state 7 and above). The UxV’s control surfaces and actuators must be capable of sustaining high levels of force and acceleration incurred when being tossed and dropped by large waves while also being sufficiently compact and lightweight to be integrated into the platform. For example, if an UxV is operating in a WMO sea-state 8 environment, it could ride atop a 10-meter wave and fall to the ocean surface, which generates forces large enough to damage mechanically conventional control surface actuator components. Conventional commercial actuator components are comprised of a motor and gearing; the gears and associated bearings are especially vulnerable to damage under high shock levels.

A key applicable technology to address this need is the material family generally termed “Electroactive Polymers” (EAP), which change in size or shape upon application of an electrical stimulus or generate a voltage when strain is induced in the material. Best known for use as “artificial muscle” actuators for experimental robots, these materials can potentially sustain large forces such as actuators.

PHASE I: Develop a concept for an EAP-based actuator. Determine the technical feasibility of this concept by modeling the actuator and demonstrating analytically that it should meet performance and durability requirements, based upon the ocean environment and mission duration requirements that will be provided by the Navy. Alternatively, a laboratory scale model proof of concept may be fabricated, tested, and demonstrated. The Phase I Option, if awarded, will include the initial design specifications and capabilities description to build a prototype solution in Phase II. Develop a Phase II plan.

PHASE II: Based upon the Phase I results and the Phase II Statement of Work (SOW), develop, fabricate, and deliver a set of prototype EAP actuators. Install and test these actuators in a Government-provided UxV, with the technical resources of Navy laboratories available to the performer as needed. The Navy will provide the technical specifications and interface documentation required for the integration of the actuators into the target UxV. Complete the design, fabrication, and testing of the functionality of the prototype actuators. Using lessons learned from laboratory tests, fabricate a set of EAP actuators that will be installed and tested at sea in an UxV. Provide support for testing and performance analysis. Prepare a Phase III development plan to transition the technology for Navy production and potential commercial use.

PHASE III DUAL USE APPLICATIONS: Building on the work of Phase II, design a production-ready set of EAP actuators to be integrated into a specific UxV design identified by the Navy (e.g., Hydroid Remus 600 or Teledyne Webb Slocum sea glider) or by a commercial UxV manufacturer that has teamed with the small business for this project. Develop and build production equipment and processes capable of producing the actuators at a volume and cost that is appropriate with expected demand. Build a set of actuators and perform First Article Testing prior to delivery to the Navy lab or UxV manufacturer. Support integration, lab test, and sea test of the UxV. Based upon test results, revise the design if necessary and deliver the first lot of actuators.

The Navy uses commercial UxV platforms and tethered Remotely Operated Vehicles (ROVs), which are also used by the oil industry and ocean scientists. EAP actuators could be installed into ruggedized variants of commercial UxVs and ROVs. EAP actuators could also provide control surfaces for other sea craft.

REFERENCES:

1. Ashley, Steven. “Artificial Muscles.” Scientific American (October 2003), 289, 52-59, doi:10.1038/scientificamerican1003-52. https://ndeaa.jpl.nasa.gov/nasa-nde/nde-aa-l/clipping/Scientific-Ameican-article-Oct-03.pdf

2. Biggs, J., Danielmeier, K., Hitzbleck, J., Krause, J., Kridl, T., Nowak, S., Orselli, E., Quan, X., Schapeler, D., Sutherland, W. and Wagner, J. “Electroactive Polymers: Developments of and Perspectives for Dielectric Elastomers.” Angewandte Chemie International Edition, 52: 9409–9421. doi:10.1002/anie.201301918. Date of access: 7 March 2017; https://www.researchgate.net/profile/James_Biggs3/publication/251235423_Electroactive_Polymers_Developments_of_and_Perspectives_for_Dielectric_Elastomers/links/004635346f86e08410000000.pdf

3. French, Daniel. “Analysis of Unmanned Undersea Vehicle (UxV) Architectures and an Assessment of UxV Integration into Undersea Applications.” Thesis, Naval Postgraduate School, Sept. 2010. http://www.dtic.mil/dtic/tr/fulltext/u2/a531528.pdf

KEYWORDS: Electroactive Polymer (EAP); Dielectric Elastomer; Artificial Muscles; Actuator; Unmanned Undersea Vehicle (UUV); Unmanned Surface Vehicle (USV)

N181-033

TITLE: Virtual Assistant for Combat System Console Operators Utilizing Artificial Intelligence Algorithms

TECHNOLOGY AREA(S): Human Systems

ACQUISITION PROGRAM: Program Executive Office, Future Combat Systems (IWS 7.0)

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 a virtual assistant tool for combat system console operators that will improve efficiency and provide recommended actions using artificial intelligence algorithms.

DESCRIPTION: Artificial Intelligence (AI) has advanced significantly with the development of “Deep Learning” algorithms. These algorithms have led to the commercial development and deployment of a number of software AI products such as Siri, Cortana, and Alexa, which endeavor to assist individuals in accomplishing routine daily tasks with a minimum of confusion, reduction in required time, or specifically directed research. These algorithmically based products eliminate the need for individuals to execute specific internet searches for time, weather, locating and playing music, and setting schedules and alarms. The Navy seeks implementation of a combat system console operator virtual assistant within the AEGIS combat system that leverages current AI algorithms and can develop new AI algorithms as required, along with a suitable modular system software architecture.

The current tasking of a combat systems console operator includes (but may not be limited to) coordinating with other console operators (via voice or text); monitoring target track data (consisting of both organic and external radar and other sensor-sourced track data); and identifying tracks and selecting those that represent a potential threat requiring engagement by various shipboard weapons systems. Additional activities include assigning weapons to specific tracks; monitoring the success and/or failure of those engagements; and re-scheduling failed engagements if sufficient time exists. This tasking represents an overwhelming workload. Given the potential growth in the number of target tracks introduced into the battlespace by the emerging development of low-cost unmanned aerial vehicles (UAVs), as well as newly developed adversarial tactics that utilize large-scale saturation raids, the potential for a console operator to suffer “information overload” has become a serious point of concern. As a result, this can cause a catastrophic failure mode within the ship self-defense scenario.

The virtual assistant will help prevent console operator overload by replacing some tasks currently performed by human operators that could be more efficiently executed by intelligent automated software. Examples of these tasks are monitoring radar tracks for unexpected variations and monitoring the Common Operational Picture (COP) for potential blue-on-blue or de-confliction issues. These are better handled, at least in part, by software algorithms, which can operate ceaselessly without the otherwise vigilant efforts required by human interface. In essence, the virtual assistant will act as the operator’s proxy within the battlespace for certain required actions in the digital domain.

The operator should be able to configure the individual virtual assistant to set up tasks and goals, and provide customized alerts. The virtual assistant, once configured, should be capable of automatically presenting context-based options for actions to complete specific mission functions. The configuration cache for a virtual assistant should be portable, allowing the operator to access the virtual assistant from one console to another console and potentially from one platform to another platform, enabling the operator to develop his own personal optimal virtual assistant configuration. An operator should be able to carry this configuration cache with him from posting to posting (across multiple ship postings), and load/update/reconfigure this configuration cache as needed. It could reasonably be considered part of his personnel profile. Ultimately, each operator’s virtual assistant might exist as a persistent presence within the battlespace digital domain, executing when the operator is disconnected or off-duty, and running pre-selected background tasks (hereafter referred to as virtual assistant “autonomous” mode). The results will be available for review when the operator logs in to a console or otherwise digitally connects to the battlespace digital domain.

This capability would enable the virtual assistant to support training utilizing the operator’s past performance to develop enhanced training scenarios focused on improving operator proficiency. The virtual assistant, as a software component running within the combat system cyber security enclave, will be subject to the same cyber security restrictions implemented to secure other software components within the combat system. There may also be additional “virtual assistant” specific functional constraints defined and implemented within the cyber security enclave to restrict virtual assistant originated actions when the virtual assistant is operating in unattended (autonomous) mode.

The software algorithms and architecture of the virtual assistant should possess certain architectural attributes. The overall virtual assistant software architecture, as well as any algorithms implemented with it should be self-contained (for example, the software should be capable of operating independently within the combat systems computer network, without requiring external connectivity to non-organic servers) and have minimal impact on the performance of the combat system. Both the virtual assistant software architecture and any AI algorithms developed should be well documented, and conform to open systems architectural principles and standards. The virtual assistant software architecture should provide a well-defined and documented applications program interface (API) between the architecture and any other combat systems (CS) applications or CS software infrastructure, allowing easy portability to other CS architectures (such as Ship Self-Defense System [SSDS] and the Future Surface Combatant [FSC] combat system that is currently in the planning stage). The operator must be provided with potential warning notifications as well as the capability to automatically select multiple tracks (either the entire group, or through specific track negation within a selected group) based on predicted common track sector of origin, current track bearing, track identification (ID), or track behavior. The virtual assistant will be capable of providing potential warning notifications as well as an automatic monitoring capability for communications (e.g., radio, database). The virtual assistant will be capable of learning from the current tactical situation, and make future warnings, recommendations, and actions based on past tactical behavior of both the tracked entities and the console operator. Input will be through either voice command or the tactical console control functionality. The virtual assistant will have specifically configured settings that can be saved by the operator such that both the virtual assistant’s learned behavioral patterns and the operator’s preferences for future use are restored when the operator logs in to a console.