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Detection and Classification of Small Moving Objects Floating in/on Water Using Long Wave Infrared Imaging Polarimetry or Combination of Radio, Laser Detection and Ranging Radar Technologies

Description:

TECHNOLOGY AREA(S): Info Systems, 

OBJECTIVE: Develop sensor technologies with object recognition capabilities that can identify and distinguish, count and geographically locate small objects (<3 inches to >3 feet) floating in riverine environments using long wave infrared imaging polarimetry or a combination of radio, laser detection and ranging radar technologies for above and below water detection. 

DESCRIPTION: Technologies with object detection capabilities sensitive enough to identify fast moving objects floating on the surface of water (or just below the surface) can offer important capabilities to understand the environment, upstream activities, and add to competencies for future military readiness and the warfighter. In this way micro-object detection can be used to inform warfighter threat avoidance, maneuverability and mobility. To meet the operational challenges and emerging dangers of the future the armed forces must be able to detect threats quickly and precisely. Because floating river debris is varied, generally comprised of small objects, often fast-moving, and complicated by the refractive properties of light on water, it requires quick and exacting sensor recognition capabilities. Sensors with this type of fidelity have potential for use by soldiers in theater as part of their protection system gear, and in military vehicles and sea faring vessels to identify objects on land and floating on the surface of water that pose a threat. Sensors with object detection capabilities are an emerging technology currently used to service a number of efforts including self-driving cars, autonomous maze solving robots, detection of large surfaces on the bottom of the ocean and for the commercial fisheries, the ability to identify fish. However, this capability has not yet been fully exploited for accurate small object detection. Developing the technology proposed here will introduce new methods for greater accuracy of small object identification in complex environments both on land and at sea. The goal here is to innovate methods for small object detection in the complex and fast moving environments of riparian landscapes. This effort should consider long wave infrared imaging polarimetry or a combination of radio, laser detection and ranging radar technologies for optimal above- and below-water object detection. The method should be able to distinguish small objects, identify debris quantities and types and geographically locate individual debris materials. The desired solution is a technology that can be used by the warfighter on land and at sea to advance current capabilities and increase security. 

PHASE I: Develop a basic proof-of-concept capability, in a stand-alone prototype, with sensor capabilities to identify a limited number of small objects commonly found floating in riverine environments, and count and geographically locate individual items of debris. Development and testing of initial prototype can be done in a lab environment with a small pool of still water (at least 2 feet deep and several feet across). 

PHASE II: The contractor will expand capabilities of the prototype developed in Phase 1. This prototype version should work in the field on small streams (several feet deep with surface areas of a few feet to yards across). Capabilities should include the ability to identify and distinguish between a greater number of objects, record numbers of each item sighted and geospatially locate each material. 

PHASE III: The contractor will create a sensor product suitable for use on large rivers (yards across and several feet deep) and military vehicles and sea faring vessels with the expanded capabilities developed in Phase 2. Products will be applied to existing systems and contain a prototype for classification, training and safety certifications, and business case analysis for future acquisition activities. 

REFERENCES: 

1: Harchanko J., Pezzaniti L., Chenault D., Eades G.(2008). Comparing a MWIR and LWIR polarimetric imager for surface swimmer detection. Proceedings of SPIE – The Internatrional Society for Optical Engineering. Retrieved from http://www.polarissensor.com/app/uploads/2016/04/MWIR-versus-LWIR-for-Surface-Swimmer-Detection.pdf

KEYWORDS: Sensors, Object-detection, Machine Learning, Intelligence, Moving Water, Fusion, GPS 

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