Autonomous Onboard Processing Hostile Fire Sensor System

Navy SBIR 22.1 - Topic N221-016
NAVAIR - Naval Air Systems Command
Opens: January 12, 2022 - Closes: February 10, 2022 (12:00pm est)

N221-016 TITLE: Autonomous Onboard Processing Hostile Fire Sensor System

OUSD (R&E) MODERNIZATION PRIORITY: General Warfighting Requirements (GWR);Microelectronics

TECHNOLOGY AREA(S): Electronics;Materials / Processes;Weapons

OBJECTIVE: Develop and deliver chip-scale multifunction midwave infrared (MWIR) metasurface optics sensor system for detecting and geolocating hostile fire to be mounted on, or installed within, small battery operated Group 1 unmanned air vehicles (UAV) and self-guiding target munitions.

DESCRIPTION: Especially when first engaged, it is often difficult for a soldier, UAV operator, or autonomous self-guiding target munitions to quickly ascertain from where hostile fire has originated. This confusion prevents a quick geolocation and effective auto target coordinates handoff to counter and eliminate hostile fire.

Traditional uncooled microbolometer technologies for small arms bullet detection do not have the potential performance on small battery operated Group 1 UAVs and self-guiding target munitions mainly due to the bullet’s large thermal time constants. Fast detector response times are required to detect fast moving objects at peak energy.

This SBIR topic seeks to improve upon the detection and geolocation capabilities of standard broadband optics sensors such as uncooled microbolometer heat detectors by distinguishing between a hostile fire signal and self-emitting blackbody radiation.

To this end, a chip-scale multifunction MWIR metasurface optics hostile fire sensor system for hostile fire detection and geolocation is needed. Demonstrate a thorough understanding of the computational targeting cue algorithms embedded with optics models that minimize calibration and computational processing of spectra needed to make the chip-scale multifunction MWIR metasurface optics hostile fire sensor system successful. As part of the effort, a sensor system design concept should be developed using available existing chip-scale optical components.

Because this topic sensor system is meant to be carried/installed on battery operated Group 1 UAVs (e.g., UVision Hero-20, Teledyne FLIR R80D SkyRaider) and self-guiding target munitions, it must be extremely light weight, low power, and possess an appropriate form factor: this is of primary importance in not degrading other Group 1 UAV and self-guiding target munitions’ performance. Additionally, it should be compatible and not interfere with other sensing systems such as acoustic, electro-optical and infrared sensors.

The sensor system need not be imaging, but must provide at least angular direction to the origin of the hostile fire event. In order to provide the user with the best chance of quickly identifying and engaging the threat, the sensor system should minimally be capable of identifying the angle to the threat with < 30° resolution and < ±15° error, but ideally < 5° resolution with < ±2.5° error. This must be balanced against Size, Weight, Power, and Cost (SWAP-C); horizontal angular (azimuth) resolution is more important than vertical (zenith).

The time lag between the shot and geolocating origin data to the user/or other UAV/self-guiding target munitions system components should be minimal, ideally < 50 ms. Of course, probability of detection at tactically relevant ranges for small arms (500–600 m), such as common assault rifles and carbines, and medium arms (1–1.5 km), such as large rifles and machine guns, should be maximized (> 90% minimum, ideally > 95%) and false alarms close to zero. Other features, such as weapons identification, the ability to squelch alerts generated from friendly fire, and range to target, are desirable. The system must minimally operate within the entire UAV and self-guiding target munitions flight/performance envelope.

Appropriate algorithms to be incorporated into the design are to provide, at a minimum: (a) angular direction to the origin of hostile fire event in all-weather day/night conditions; (b) a least probability of detection versus range; (c) angular resolution and error; (d) time to detect; (e) geo-location; and (f) sources of false alarms and potential mediation.

Testing during later stages of development must include valuation of brass board system using live fire and controlled motion studies over a wide range of relevant background environments.

PHASE I: Demonstrate the feasibility of a complete chip-scale multifunction MWIR metasurface optics hostile fire sensor system design using only components which are commercial off-the-shelf (COTS) or those that could reasonably be designed and fabricated within the time and budget constraints. The sensor design need not be optimized for SWAP-C at this stage, but it must show extensibility to small battery operated UAVs and self-guiding target munitions systems. A complete and thorough understanding of the algorithms necessary to make the sensor system successful must be demonstrated. Rigorous modeling should be performed to estimate sensor system performance, including at least probability of detection versus range, angular resolution and error, time to detect, geolocation, and any other features. Sources of false alarms and potential mediation should be well thought out and incorporated into the design. The Phase I effort will include prototype plans to be developed under Phase II.

PHASE II: Using the results of Phase I, fabricate and deliver a prototype chip scale multifunction MWIR metasurface optics hostile fire sensor system. Prototype should minimally meet requirements for a minimum of TRL 4: component and/or breadboard validation operating in a laboratory environment. All required sensors must be carried or installed small battery operated UAVs, but processing and power may be external at this stage, so long as a detailed design path is provided to show that it can all be integrated into the small battery operated UAVs and self-guiding target munitions (full integration is preferred). Probability of detection, angular resolution and error, and time to detect shall be measured through live-fire testing at close-to-moderate distance, at least 50–1000 m. False alarm mitigation techniques should also be laboratory or field tested when possible.

Perform data collection for the purposes of evaluating sensor and system performance at appropriate program intervals, to include live fire testing. Cameras and sensors must be appropriately calibrated and characterized including sensor pose. Live fire testing shall occur at relevant system ranges and locations relative to system or sensor. Testing during later stages of development must include valuation of brass board system using live fire and controlled motion studies over a wide range of relevant background environments.

Algorithms must minimally include detection, tracking, spatiotemporal registration, motion stabilization. Algorithms shall be capable of running in real time in SWAP-C appropriate hardware as in a postprocessing mode (e.g., on a desktop computer for analysis and precollected data).

PHASE III DUAL USE APPLICATIONS: Transition applicable techniques and processes to a production environment with the support of an industry partner. Finalize a sensor design with appropriate SWAP-C and form factor based on human factors testing. Determine the best integration path as a capability upgrade to existing or future systems, including firmware and interfaces required to meet sensor interoperability protocols for integration into candidate systems as identified by the Navy.

From a military application, this system gives small battery operated UAVs and self-guiding target munitions the capability to provide accurate azimuth, elevation, and range information about hostile fire shot line as well as the geolocation of the hostile file origin to blue forces and if equipped encounter and eliminate hostile fire sources.

From the commercial application, this systems capability will be able to detect smoke and fire at speeds comparable to or faster than conventional detection systems. This makes them a good choice in settings like laboratories, chemical plants, refineries, and boiler rooms where it is critical to detect smallest temperature changes or hidden pockets of embers at an early stage.


  1. Tidhar, G. (2013). Hostile fire detection using dual-band optics. SPIE Newsroom.
  2. Li, X., Greenberg, J. A., & Gehm, M. E. (2019). Single-shot multispectral imaging through a thin scatterer. Optica, 6(7), 864-871.
  3. Stancic, I., Bugaric, M., & Perkovic, T. (2017). Active IR system for projectile detection and tracking. Advances in Electrical and Computer Engineering, 217(4) 125–130.
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  5. Blake, T. A., Kelly, J. F., Gallagher, N. B., Gassman, P. L., & Johnson, T. J. (2009). Passive standoff detection of RDX residues on metal surfaces via infrared hyperspectral imaging. Analytical and bioanalytical chemistry, 395(2), 337-348.
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  7. Snarski, S., Menozzi, A., Sherrill, T., Volpe, C., & Wille, M. (2010, May). Results of field testing with the FightSight infrared-based projectile tracking and weapon-fire characterization technology. In Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IX (Vol. 7666, p. 76662C). International Society for Optics and Photonics.
  8. Department of Defense. (2013, September 16). Defense Acquisition Guidebook (pp. 848–849). Department of Defense.

KEYWORDS: Hostile Fire; chip-scale; metasurface; unmanned air vehicle; UAV; optics; munitions


The Navy Topic above is an "unofficial" copy from the overall DoD 22.1 SBIR BAA. Please see the official DoD Topic website at for any updates.

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