Down selection of climatic data for infrared signature modelling

Ian L. Kermonde; Frank Drost; Rodney A. J. Borg

doi:10.1117/12.2304657

26 April 2018 Down selection of climatic data for infrared signature modelling

Ian L. Kermonde, Frank Drost, Rodney A. J. Borg

Author Affiliations +

Proceedings Volume 10625, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIX; 106250C (2018) https://doi.org/10.1117/12.2304657
Event: SPIE Defense + Security, 2018, Orlando, Florida, United States

Abstract

The Infrared signature of a defence platform is strongly influenced by environmental conditions. This paper will outline two alternative methods to select a subset of climatic data to represent a large dataset as an input for Infrared signature modelling. A binning and ranking algorithm first presented by Vaitekunas and Kim (2013) will be compared with a genetic algorithm. The results for five different geographic locations will be assessed by comparing the cumulative distribution functions of the subset and the original dataset. Quantile-Quantile plots and the Kolmogorov-Smirnov statistic will be used to assess the solutions for the two different algorithms.

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Citation Download Citation

Ian L. Kermonde, Ian L. Kermonde, Frank Drost, Frank Drost, Rodney A. J. Borg, Rodney A. J. Borg, "Down selection of climatic data for infrared signature modelling", Proc. SPIE 10625, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIX, 106250C (26 April 2018); doi: 10.1117/12.2304657; https://doi.org/10.1117/12.2304657

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