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FTOM-2D: A two-dimensional approach to model the detailed thermal behavior of nonplanar surfaces

: Bartos, Bernd; Stein, Karin


Stein, K.U. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Target and Background Signatures : 23 - 24 September 2015, Toulouse, France
Bellingham, WA: SPIE, 2015 (Proceedings of SPIE 9653)
ISBN: 9781628418637
Paper 96530G, 7 pp.
Conference "Target and Background Signatures" <2015, Toulouse>
Conference Paper
Fraunhofer IOSB ()
thermal object; semi-empirical model; FTOM-2D; non-planar surface

The Fraunhofer thermal object model (FTOM) predicts the temperature of an object as a function of the environmental conditions. The model has an outer layer exchanging radiation and heat with the environment and a stack of layers beyond modifying the thermal behavior. The innermost layer is at a constant or variable temperature called core temperature. The properties of the model (6 parameters) are fitted to minimize the difference between the prediction and a time series of measured temperatures. The model can be used for very different objects like backgrounds (e.g. meadow, forest, stone, or sand) or objects like vehicles. The two dimensional enhancement was developed to model more complex objects with non-planar surfaces and heat conduction between adjacent regions. In this model we call the small thermal homogenous interacting regions thermal pixels. For each thermal pixel the orientation and the identities of the adjacent pixels are stored in an array. In this version 7 parameters have to be fitted. The model is limited to a convex geometry to reduce the complexity of the heat exchange and allow for a higher number of thermal pixels. For the test of the model time series of thermal images of a test object (CUBI) were analyzed. The square sides of the cubes were modeled as 25 thermal pixels (5 × 5). In the time series of thermal images small areas in the size of the thermal pixels were analyzed to generate data files that can easily be read by the model. The program was developed with MATLAB and the final version in C++ using the OpenMP multiprocessor library. The differential equation for the heat transfer is the time consuming part in the computation and was programmed in C. The comparison show a good agreement of the fitted and not fitted thermal pixels with the measured temperatures. This indicates the ability of the model to predict the temperatures of the whole object.