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23 June 2000 Controlled decimation of digital elevation data and subsequent in-flight verification
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Abstract
Many of today's and tomorrow's real-time aviation applications are demanding for accurate and reliable databases. Common TAWS implementations such as EGPWS or integrated navigation systems such as Dasa's Integrated Navigation and Flight Guidance System16 depend essentially on terrain elevation databases. Regarding these applications, the resolution, accuracy, and precision of available data are of primary concern. On the other hand, 4D Synthetic Vision Systems (SVS) require performance optimized terrain models for a real-time visualization. The content of such databases need to be reduced and accessible in a real-time format. In 4D SVS, safety critical terrain databases are essential. Even higher accuracy is required for more demanding tasks such as low-level flights, precision approaches, or landings. In this paper a process is described to accomplish the contradictory demands of accuracy and visualization performance. The complexity of hi- resolution terrain models is reduced to enhance the rendering performance. Two different decimation approaches are explained and the resulting terrain databases is described. Each representation of the generated elevation shapes comprises a coarser quantity of input data. A statistical error analysis of resulting altitude errors is presented. The presented results represent both an offline verification with highly accurate databases and a comparison with altimeter data measured by airplane sensors during flight trials. To evaluate the different databases and to examine specific terrain resolutions, multiple flight trials were performed.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thorsten Wiesemann, Jens Schiefele, Ludwig May, Felix E. Mehler, and Wolfgang Kubbat "Controlled decimation of digital elevation data and subsequent in-flight verification", Proc. SPIE 4023, Enhanced and Synthetic Vision 2000, (23 June 2000); https://doi.org/10.1117/12.389359
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