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Proceedings Paper

Reliable ISR algorithms for a very-low-power approximate computer
Author(s): Ross S. Eaton; Jonah C. McBride; Joseph Bates
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Paper Abstract

The Office of Naval Research (ONR) is looking for methods to perform higher levels of sensor processing onboard UAVs to alleviate the need to transmit full motion video to ground stations over constrained data links. Charles River Analytics is particularly interested in performing intelligence, surveillance, and reconnaissance (ISR) tasks using UAV sensor feeds. Computing with approximate arithmetic can provide 10,000x improvement in size, weight, and power (SWAP) over desktop CPUs, thereby enabling ISR processing onboard small UAVs. Charles River and Singular Computing are teaming on an ONR program to develop these low-SWAP ISR capabilities using a small, low power, single chip machine, developed by Singular Computing, with many thousands of cores. Producing reliable results efficiently on massively parallel approximate machines requires adapting the core kernels of algorithms. We describe a feature-aided tracking algorithm adapted for the novel hardware architecture, which will be suitable for use onboard a UAV. Tests have shown the algorithm produces results equivalent to state-of-the-art traditional approaches while achieving a 6400x improvement in speed/power ratio.

Paper Details

Date Published: 31 May 2013
PDF: 13 pages
Proc. SPIE 8713, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications X, 871312 (31 May 2013); doi: 10.1117/12.2016009
Show Author Affiliations
Ross S. Eaton, Charles River Analytics, Inc. (United States)
Jonah C. McBride, Charles River Analytics, Inc. (United States)
Joseph Bates, Singular Computing, LLC (United States)


Published in SPIE Proceedings Vol. 8713:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications X
Daniel J. Henry; Davis A. Lange; Dale Linne von Berg; S. Danny Rajan; Thomas J. Walls; Darrell L. Young, Editor(s)

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