N211-039 TITLE: 24/7 Reachback Artificial Intelligence Support Environment for Anti-submarine Warfare (ASW)
RT&L FOCUS AREA(S): General Warfighting Requirements
TECHNOLOGY AREA(S): Information Systems
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 3.5 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 24/7 reachback artificial intelligence (AI) support environment to modernize anti-submarine warfare (ASW) in-service and logistics troubleshooting both to support the large variety of fielded baselines and configurations; enable machine learning to inform best fixes; and drive future design improvements to tactical sonar suites.
DESCRIPTION: A 24/7 Reachback AI Support Environment can modernize the in-service and logistics support (ILS) infrastructure so that sailors and ILS personnel have rapid alignment regarding the particular baseline and configuration in question. Commercial AI support tools are increasingly used in industry but these tools are specific to the industry in which it is created. The tools are needed for ASW support. The modernized environment would be based on an ontology that allows for data mining and machine learning regarding issues with greatest Fleet impact, both from a standpoint of understanding the breadth and scope of impact as well as elevating the most appropriate fixes.
As the 24/7 Reachback AI Support Environment accrues information, evidence collected could drive design improvements.
The technology sought will increase mission capability by accelerating resolution of system casualties identified by sailors across the many different fielded variants. The technology will also create a Navy-wide database on which artificial intelligence and machine learning can operate to identify root causes to inform future acquisition decisions related to improving system availability.
Navy surface combatants engage in anti-submarine warfare (ASW) using variants of the AN/SQQ-89, a complex system of systems composed of processing software, processing hardware, and sensitive sensor arrays. When operating properly, the ASW sensor suite gives a Fleet combatant a powerful capability to detect, classify, localize, and attack submerged threats.
The in-service and logistics infrastructure for the AN/SQQ-89 has evolved over decades, building on the Cold War sonar capability fielded in the 1950s as the AN/SQQ-26 sonar. In the two decades since the end of the Cold War, a majority of fielded AN/SQQ-89 systems were legacy systems, with problems that had remained relatively stable.
Initial introduction of the A(V)15 modernization to the AN/SQQ-89 in 2009 brought modernized capabilities that the Fleet welcomed, including introduction of the Multi-Function Towed Array (MFTA). The A(V)15 leverages commercial off-the-shelf (COTS) processing hardware. Though relatively inexpensive and very powerful from a processing standpoint, COTS infrastructure drives a relatively rapid pace of technology updates.
The rapid pace of updates required by COTS infrastructure has enabled introduction of numerous improvements. However, the proliferation of distinct variants has made the ILS challenge increasingly complex. Support personnel using infrastructure designed to support legacy baselines have identified potential for significant improvement in in-service and logistics support (ILS) outcomes should a modernized reachback capability be developed.
When problems arise, sailors seek reachback support from ILS personnel who work 24/7 to provide timely guidance to resolve Fleet casualty reports (casreps). When new parts are required, the ILS team speeds them on their way. It is crucial that communication between the Fleet and the ILS team is robust, ensuring that the ILS specialist is 1) troubleshooting based on the proper baseline and configuration and all pertinent data; and 2) ensuring that any replacement parts are appropriate to the baseline and configuration in question. As diagnosis of many system casualties involve interaction with displays, it is important that the ILS specialist have ready access to the particular displays associated with the system the Fleet sailors are attempting to fix.
The technology will be tested using the IWS 5.0 Advanced Capability Build (ACB) step testing process. The seminal transition event will be validation by the Government that the technology performs as required. Testing will include user exploration of the tool, examination of the fault isolation capabilities and associated accuracy, and comparison of the tool menus to the tactical system menus to ensure consistency.
Finally, the information accrued by the modernized reachback capability should be organized into an ontological framework that facilitates machine learning and artificial intelligence to enable analysis of casualties across the Fleet, their root causes, and prioritization of investments to make the overall system more robust. A particular challenge, required to be provided by the new tool, is providing timely and appropriate ILS for the MFTA. As a towed sensor, the MFTA operates hundreds of feet below the ocean surface, necessarily deployed and retrieved through the punishing conditions in the wake of the combatant. The OK-410 handling system associated with the MFTA, while robust, has numerous moving parts. The MFTA operates in the ocean depths where submerged threats often seek to hide, and is therefore particularly valued by the Fleet. Initial transition of the 24/7 Reachback AI Support Environment will likely focus on systems related to MFTA and other towed systems.
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 Counterintelligence Security Agency (DCSA). 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 DCSA 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: Develop a concept for a 24/7 Reachback AI Support Environment that meets the requirements in the Description section. The concept will show feasibility through analytical modeling; developing and documenting infrastructure concepts; proposed ontological framework; and architectures that support both sailors, ILS specialists, and analysts. The Phase I Option, if exercised, will include the initial system specifications and a capabilities description to build a prototype in Phase II.
PHASE II: Develop and deliver a prototype 24/7 Reachback AI Support Environment with embedded machine learning meeting the requirements for ASW as stated in the Description. Demonstrate the prototype performance across a subset of the total SQQ-89 ILS historical findings and demonstrate the prototype is fit for use by Fleet operators, ILS specialists, and acquisition analysts as discussed in the Description. If needed, coordination with the Government will occur to conduct testing at a Government or company-provided facility to validate the prototype capability. Data sets extracted from Cruiser/Destroyer casualty reports will be used to validate the prototype�s capabilities. The Government will provide the data. Demonstration of the prototype performance will take place at a Government- or company-provided facility.
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 Navy in transitioning the technology to Navy use in ASW. Demonstrate and report on performance during laboratory testing. Integrate the prototype into the IWS 5.0 surface ship ASW combat system ILS infrastructure, which will drive updates to sensor systems, handling equipment, and the Advanced Capability Build (ACB) program used to update the AN/SQQ-89 Program of Record.
This technology can be used to support a broad range of commercial and military industries where support originally designed for complex legacy systems needs to be modernized to include a proliferation of unique models.
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KEYWORDS: In-service and Logistics Support; Artificial Intelligence; Anti-Submarine Warfare; ASW; Machine Learning; Casualty Reports; Towed Systems