DON27BZ02-NV009 TITLE: Distributed Multispectral Event-Driven Integrated Sensing and Communications
OUSW (R&E) CRITICAL TECHNOLOGY AREA(S): Quantum and Battlefield Information Dominance (Q-BID)
COMPONENT TECHNOLOGY PRIORITY AREA(S): Integrated Sensing and Cyber
PROJECTED CMMC LEVEL REQUIREMENT: Level 2 (Self)
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 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 distributed multispectral event-driven integrated sensing and communications capability that can timely provide robust detection of a wide range of objects and integrate into existing onboard sensors to expand operational battlespace.
DESCRIPTION: The Navy Aegis Program Office is interested in expanding battlespace awareness to support cross-domain operations through the integration of remote passive sensors. Currently, these sensors rely on real-time frame-based processing that generates large volumes of data, requiring significant processing power and energy and creating constraints for resource-limited hardware platforms with finite battery life, processing capabilities, and memory. In addition, transmitting large volumes of data over dynamic communication links can introduce delays and encounter bandwidth limitations that cannot meet time-critical operational needs. The complexity of the battlespace and electromagnetic environment further presents challenges for robust detection, classification, and identification. Advanced remote passive-sensor technologies that enable efficient and distributed sensing and processing will support multidomain operations by providing timely and resilient battlespace awareness. Successful technologies will be transitioned to the Aegis Combat System (ACS) to enhance distributed sensing, accelerate decision-making, and enable cross-domain operations.
The Navy is seeking to develop Multispectral Integrated Neuromorphic Sensing and Communications (MINSC) technology to support endurant remote sensing capability. MINSC is an event-driven sensor featuring low-probability-of-intercept (LPI) data transmission that can timely identify a wide range of objects and transmit the information to remote platforms to integrate into the existing decision-making process. Neuromorphic computing can provide energy efficient, parallel processing, and low-latency framework for passive sensing, edge computing, and remote inference.
Neuromorphic sensors deliver high temporal resolution, asynchronous, energy and bandwidth efficient data inspired by biological vision. The Navy seeks to build an Event-Driven Energy-Efficient Ecosystem to support Endurant Long-Range Sensing and Communications capability. Solutions can be software, neuromorphic hardware, and/or end-to-end neuromorphic system that can deliver robust information and fuse with existing sensors to provide improved tracking, detection, classification, and identification. The Navy is open to innovative ideas of novel system design that can make decisions locally and communicate sparingly or timely send out the event-driven information for remote inference. The intended capability is an integrated remote passive-sensing capability that performs event-driven local sensing and processing, communicating only the information necessary to enhance remote awareness, and fuses with existing sensors to improve tracking, detection, classification and identification.
Distributed MINSC will provide advantages in dynamic environment and resilience to noise and debris associated with military applications. Incorporating event-based multispectral remote sensors with onboard sensors will expand operational battlespace, contribute to robust Common Operational Picture (COP) and enhance situational awareness. It will integrate with the Aegis and permit realistic testing of all threat types and configurations in a dynamic testing environment. Track visualization will be delivered through the existing ACS console Graphical User Interfaces (GUIs). The solution will support current operator track management and decision-making and integrate with the AEGIS Test Bed (ATB) to facilitate system evaluation against more advanced threats. The solution will provide an enhanced capability to address targets in all configurations and optimal engagement options to the sailors, which will increase mission capability and effectiveness against the latest threats.
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 32 U.S.C. § 2004.20 et seq., National Industrial Security Program Executive Agent and Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Counterintelligence and Security Agency (DCSA) formerly 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. This will allow contractor personnel to perform on advanced phases of this project as set forth by DCSA and PAE MS 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 during the advanced phases of this contract IAW the National Industrial Security Program Operating Manual (NISPOM), which can be found at Title 32, Part 2004.20 of the Code of Federal Regulations.
PHASE I: Develop a design concept for MINSC technology for remote, instant, and robust reporting of objects of interest. Demonstrate the feasibility in meeting the requirements in the Description to support the tests and operational environments. Establish feasibility through analysis and modeling. Consider Design for Manufacturing (DFM) framework in the hardware design to simplify production processes throughout the design phase, ensuring design aligns with manufacturing standards. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype solution in Phase II.
PHASE II: Develop and deliver a MINSC prototype based on the results of Phase I. Ensure that the hardware prototype includes firmware and detailed interface specifications to support tests and evaluation in a Government Lab. Support evaluation of the prototype through lab testing, analytical methods, modeling, and simulation (if a simulation model is provided). For software prototype provide an emulator or hardware to demonstrate the technology to be evaluated by Government subject matter experts for validation. Deliver two prototypes at the end of Phase II. Provide a Phase III commercialization/transition plan.
It is probable that the work under this effort will be classified under Phase II (see the Description for details).
PHASE III DUAL USE APPLICATIONS: Support the Navy in transitioning the prototype to allow for further experimentation and refinement for Navy uses. Incorporate the prototype into the AEGIS baseline testing modernization process and/or incorporated into Electronic Support Measures (ESM) in the SEWIP program to include integration into a baseline definition and incorporation of the baselines existing and new threat capabilities, validation, and combat system certification.
Integrated Neuromorphic Sensing and Communications will have applications in FutureG, Autonomous Vehicles, IoT, Surveillance, Robotics and Automation, Wearable Electronics, and Healthcare.
REFERENCES:
KEYWORDS: Neuromorphic Sensors; Neuromorphic Computing; Passive Sensors; Distributed Sensing; Edge Computing; Remote Inference; Remote Sensing
TPOC 1: Simin Feng
simin.feng.civ@us.navy.milTPOC 2: Gerald Lawrence
gerald.s.lawrence2.civ@us.navy.mil
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