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A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications
Contributor(s): Nasa, National Aeronautics and Space Adm (Author)

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 ISBN: 1794088237     ISBN-13: 9781794088238
Publisher: Independently Published
OUR PRICE: $20.69  

Binding Type: Paperback
Published: January 2019
* Out of Print *
Additional Information
BISAC Categories:
- Science | Space Science
Physical Information: 0.09" H x 8.5" W x 11" L (0.28 lbs) 44 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort. NASA/TM-2017-219612, L-20807, NF1676L-26863 Grauer, Jared A. Langley Research Center
 
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