Processor design optimization methodology for synthetic vision systems

Bill Wren; Norman G. Tarleton; Peter F. Symosek

doi:10.1117/12.277225

26 June 1997 Processor design optimization methodology for synthetic vision systems

Bill Wren, Norman G. Tarleton, Peter F. Symosek

Proceedings Volume 3088, Enhanced and Synthetic Vision 1997; (1997) https://doi.org/10.1117/12.277225
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

Architecture optimization requires numerous inputs from hardware to software specifications. The task of varying these input parameters to obtain an optimal system architecture with regard to cost, specified performance and method of upgrade considerably increases the development cost due to the infinitude of events, most of which cannot even be defined by any simple enumeration or set of inequalities. We shall address the use of a PC-based tool using genetic algorithms to optimize the architecture for an avionics synthetic vision system, specifically passive millimeter wave system implementation.

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Bill Wren, Norman G. Tarleton, and Peter F. Symosek "Processor design optimization methodology for synthetic vision systems", Proc. SPIE 3088, Enhanced and Synthetic Vision 1997, (26 June 1997); https://doi.org/10.1117/12.277225

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