Paper
25 May 2005 Methods for validation of optical signature models
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Abstract
When using prediction programs for optical signatures, it is necessary to include validations to find estimates of the uncertainties and define the regions of validity. In this paper we present two paths of development of validation methods: The objective of the first path is to analyze and validate the differences between simulated and measured images, through image features such as edge concentration and different energy measures. In particular, aspects that are important for detection, classification and identification of targets are considered. The second path concerns development of methods for quantifying the propagation of input data uncertainties to output parameters in computational predictions. Two commercial codes have been used for the modeling: RadThermIR for thermal predictions of the targets and CAMEO-SIM for the radiometry and rendering. A recently developed interface between the two codes has been utilized. For the validation of spatial statistics, several feature values have been computed for a measured image and for the corresponding simulated image. It was found that the agreement was quite good. The work on propagation of uncertainties in computational predictions has resulted in a number of proposed methods. In this paper we present two different methods: one based on linear error propagation and one based on the Monte Carlo method. The results are according to expectations for both types of methods and show that a large part of the uncertainty in predicted temperature emanates from input parameter uncertainties for the considered test case.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Claes Nelsson, Erik Andersson, David Boerjesson, Patrik Hermansson, Sten Nyberg, Stefan Sjoekvist, and Thomas Winzell "Methods for validation of optical signature models", Proc. SPIE 5811, Targets and Backgrounds XI: Characterization and Representation, (25 May 2005); https://doi.org/10.1117/12.603775
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Cited by 1 scholarly publication.
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KEYWORDS
Monte Carlo methods

Temperature metrology

Sensors

Computer simulations

Error analysis

Electro optical modeling

Infrared signatures

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