Miniature 360-degree Multispectral/Hyperspectral Staring Imaging System

Navy SBIR 20.2 - Topic N202-110

Naval Air Systems Command (NAVAIR) - Ms. Donna Attick [email protected]

Opens: June 3, 2020 - Closes: July 2, 2020 (12:00 pm ET)



N202-110       TITLE: Miniature 360-degree Multispectral/Hyperspectral Staring Imaging System


RT&L FOCUS AREA(S): General Warfighting Requirements (GWR)



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 miniature 360-degree Multispectral/Hyperspectral staring imaging system with discriminate classification capabilities for use on Navy manned and unmanned aircraft.


DESCRIPTION: U.S. Navy manned and unmanned aircraft platforms have a need for 4p steradian coverage for situational awareness while performing their required missions. In addition, airborne surveillance systems need to meet multiple mission requirements for automatic detection, track, and identification of a variety of objects to include aircraft, missiles, and obstructions hazardous to flight. There is a need for reduced size multispectral/hyperspectral imaging to provide a capability to conduct search, detection, classification, localization, tracking, and attack of surface ships and surfaced submarines in both clear and adverse weather, and in both the littoral and blue water environments. Small target examples are anti-aircraft missiles, Tier 1 Unmanned Aerial Systems (UAS), patrol craft, and submarines. Systems that are integrated onto airborne platforms need to meet stringent requirements for size, weight, power, and cost (SWaP-C); as well as aircraft requirements for environmental conditions such as vibration, shock, heat, altitude, etc. These requirements vary from aircraft to aircraft, but hold a common theme of reduced SWaP-C sensors to meet a number of aircraft requirements. The initial platform requirements will include the P-8A and MQ-4C platforms. The P-8A and MQ-4C will provide air defense capabilities to defend, identify, classify and track air targets and threats to the aircraft. In addition, the aircraft conducts Search and Rescue (SAR) missions. Current system concepts, such as large pods, are normally single purpose and impact mission performance by excessive SWaP-C that limits on-station time by increased drag counts and negative impacts to fuel consumption.

The multispectral/hyperspectral imaging system should provide 4p steradian coverage. The SWaP should be limited to approximately 100 pounds, total volume of 2 cubic feet, and have less than 500 Watts of input power required. Aircraft power requirements in accordance with MIL-STD-704 and MIL-STD-461 should be taken into consideration. Cost should be less than $300K per unit as manufactured. Aircraft environmental conditions in accordance with MIL-STD-810 should be taken into consideration. The sensors need to be external to the aircraft and be low drag as to not increase fuel consumption by more than 1%.��


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 and Security Agency (DCSA). 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 NAVAIR 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 advanced phases of this contract.


PHASE I: Develop a concept of a miniature spectral imaging digital system that can automatically search for air, surface targets and launch transients in littoral and blue water operations. The system should be able to automatically detect and classify multiple targets and provide threat warnings for 4p steradian coverage. The Phase I effort will include prototype plans to be developed under Phase II.


PHASE II: Further refine the architecture and algorithms developed in Phase I and develop a working prototype to include high-level surveillance requirements for automatic detection, tracking, and identification over 4p steradians of aircraft, missiles and flight obstructions, software development, initial system testing, and a lab or ground-based demonstration.


Work in Phase II may become classified. Please see note in the Description section.


PHASE III DUAL USE APPLICATIONS: Perform final testing and transition the developed technology to appropriate Navy manned and unmanned aircraft platforms. Hyperspectral sensing has a multitude of application in commercial remote sensing. These include commercial aircraft and ground vehicle surveillance for collision avoidance, manufacturing safety systems, and inspection and surveillance systems.



1. Stein, D., Schoonmaker, J., and Coolbaugh, E. �Hyperspectral Imaging for Intelligence, Surveillance, and Reconnaissance.� SSC San Diego, Aug 2001.


2. Anderson, R.C., Malila, W., Maxwell, R. & Reed, L.K. �Military Utility of Multispectral and Hyperspectral Sensors.� Infrared Information Analysis Center Environmental Research Institute of Michigan, November 1994.


3. Wang, Z., Nasrabadi, N.M. & Huang, T.S. �Discriminative and compact dictionary design for Hyperspectral Image classification using learning VQ framework.� 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 3427-3431.








KEYWORDS: Multispectral, Hyperspectral, Remote Sensing, Optics, Imaging, Surveillance



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