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Low-cost multi-camera module and processor array for the ultra-fast framerate recognition, location, and characterization of explosive events
Author(s): Cedric Yoedt; Carlos Maraviglia; Sungjoo Park; Kevin Cox
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Paper Abstract

In the image processing world the detection, location, and identification of explosive events is accomplished usually by single detectors, single element detector arrays, or higher cost cameras (primarily infrared). Imaging systems have been limited by the too few event frames, high costs of components, and poor false alarm rates. For the last three years NRL’s Advanced Techniques Digital Technologies section has been researching ultra-fast framerate explosive event detection. NRL has designed, fabricated, and tested a multi-sensor array of low cost camera modules, each with its own field programmable gate array processor, which are then networked together to implement a system capable of imaging explosive events at 16-30kHz framerates in real time. These camera modules work in the visible band and open up the possibility of exploiting 30-60 frames of an explosive event. With this array it is possible not only to image burning gases and high intensity flashes but also low signature moving effluent and airborne particles. By using processors behind each camera module it is possible to leverage different parts of the algorithm to accomplish computationally expensive operations on individual frames. Networking the array together allows further distribution of the processing for further temporal analysis. Finally all of the resulting images are sent to a central processor where the final parts of the algorithm are completed. The cost of this system once optimized for production will be close to that of acoustic systems but with much higher precision.

Paper Details

Date Published: 27 April 2018
PDF: 9 pages
Proc. SPIE 10646, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 106460Z (27 April 2018); doi: 10.1117/12.2304459
Show Author Affiliations
Cedric Yoedt, U.S. Naval Research Lab. (United States)
Carlos Maraviglia, U.S. Naval Research Lab. (United States)
Sungjoo Park, U.S. Naval Research Lab. (United States)
Kevin Cox, Space-Ground System Solutions (United States)

Published in SPIE Proceedings Vol. 10646:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII
Ivan Kadar, Editor(s)

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