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Vision Processor for Helmet System (VPHS)
Title: Senior Electrical Engineer
Phone: (408) 888-0587
Email: j.davey@saphotonics.com
Title: Chief Financial Officer
Phone: (970) 778-2353
Email: a.singewald@saphotonics.com
ABSTRACT: Digital binocular helmet-mounted display (HMD) systems are now available that allow high resolution wide field-of-view (WFOV) digital imagery to be displayed on high resolution microdisplays. These digital HMD systems require sensor preprocessing, optical distortion correction, and image processing between the sensor inputs and the microdisplay outputs. Sensors on the helmet can be visible near infrared (VNIR), short-wavelength infrared (SWIR), long-wavelength infrared (LWIR), or millimeter wave sensors and can have their images fused to provide a composite multispectral image. This fused image can provide increased situational awareness by combining the significant features from each sensor into a composite fused image presented to the eyes. Currently there are no vision processors that perform all the necessary computation for sensor image fusion within the size, weight, and power constraints required for a helmet mounted system. What is needed is a small, light weight, low power, vision processor for helmet systems (VPHS) so the entire digital vision system can be helmet mounted without impacting helmet ergonomics. The SA Photonics VPHS system will be implemented on a seventh generation device with size, weight, power, and cost (SWaPC) savings. The VPHS system will perform image processing for at least two sensor inputs and two microdisplay outputs. BENEFIT: There are multiple benefits to the Air Force in having a Vision Processor for Helmet System (VPHS). Implementation of seventh generation devices Complete helmet mounted digital vision system with<1 frame latency Reduced size, power, and weight compared to previous generation processors Up to four high resolution sensor inputs Up to two high resolution microdisplay outputs Graphics engine for symbology overlays System data link to platform using single link Additional object detection and feature detection
* Information listed above is at the time of submission. *