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5 May 2017 Synthetic vision display with integral sonic boom predictions
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Synthetic vision systems are becoming common in the business jet community. The perspective display of terrain information provides a display of complex information in a visual manner that pilots are accustomed to. Research and flight testing is underway to allow low noise supersonic business jet operations. Widespread acceptance will require regulatory changes, the ability for pilots to predict, and manage where the generated sonic boom will impact people on the ground. A display of the sonic boom impact will be needed for preflight and inflight planning. This paper details the CONOPS, algorithm development, and human machine considerations of a synthetic vision display design incorporating a sonic boom carpet. Using a NASA developed algorithm, sonic boom prediction, Mach cut-off, and sound pressure levels are calculated for current and modified flights plans. The algorithm information is transformed into georeferenced objects, presented on navigation and guidance displays, where pilots can determine whether the current flightplan avoids the generation of sonic booms in noise-sensitive areas. If pilots maneuver away from the flightplan, a dynamically computed predicted boom carpet is presented in which the algorithm is fed an extrapolation of the current flightpath. The resulting depiction is a sonic boom footprint which changes location as the aircraft maneuvers. Using a certain lookahead time for the prediction, the pilot has the ability to shift the location where boom intensity will be at a maximum. Considerations of allowable sound levels for various locations on the ground are incorporated for comparison of the realtime and predicted sonic boom.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Laura M. Smith-Velazquez, Erik Theunissen, and Tim Etherington "Synthetic vision display with integral sonic boom predictions", Proc. SPIE 10197, Degraded Environments: Sensing, Processing, and Display 2017, 1019708 (5 May 2017);

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