The requirement for realistic simulation of military scenarios arises from a dearth of suitable and accessible measured data. Furthermore, measurement campaigns are restricted by the trial locality and availability of appropriate targets. Targets located in and around tree-lines are of particular interest, as they present scenarios that conventional broadband sensor systems find problematic. Utilising the spectral component of scenes, through the use multi- or hyperspectral technologies, can be beneficial in detecting these difficult targets.
In this paper we describe the use of a Monte Carlo ray-tracing model (FLIGHT) to simulate forest scenes. This model is capable of calculating the interesting BRDF properties specific to forests. Targets are also incorporated in these simulations, and we describe contrast discrimination of the target from the background. This technique has application for targets in deep hide as well as at the forest edge (i.e., in a tree-line).
Assessment methods that can be applied to simulated hyperspectral imagery are investigated, to determine how realistic these scenes are in comparison to measurement. This is of key importance in ensuring that simulated imagery, as well as measured data, can be used to assess algorithmic techniques to detect and discriminate targets. Statistical assessment measures are discussed that utilise the spatial and spectral properties of the image.
The Advanced Technology Centre (ATC) is responsible for developing IR signature prediction capabilities for its parent body, BAE SYSTEMS. To achieve this, the SIRUS code has been developed and used on a variety of projects for well over a decade. SIRUS is capable of providing accurate IR predictions for air breathing and rocket motor propelled vehicles. SIRUS models various physical components to derive its predictions. A key component is the radiance reflected from the surface of the modeled vehicle. This is modeled by fitting parameters to the measured Bi-Directional Reflectance Function (BDRF) of the surface material(s). The ATC have successfully implemented a parameterization scheme based on the published OPTASM model, and this is described. However, inconsistencies between reflectance measurements and values calculated from the parameterized fit have led to an elliptical parameter enhancement. The implementation of this is also described. Finally, an end-to-end measurement-parameterization capability is described, based on measurements taken with SOC600 instrumentation.
A method for the non-intrusive determination of temperature and concentrations of the exhaust gases of aeroengines will be presented. A MIROR-type FTIR spectrometer is used to measure spectra of the IR radiation emitted by the hot gases in the exhaust. New evaluation software, specially developed for this application, is described. The software permits line-by-line radiative transfer modeling of the radiance emitted by the exhaust of these engines. Least squares fitting routines are then used to match the measured with the modeled spectrum, thereby determining the unknown quantities, i.e., temperature and species concentrations. Results of measurements aboard aircraft are presented. The achieved accuracy in temperature is estimated to be better than 1 percent. Comparison of the values determined for the NOx emission index with results from correlation models show deviations of 15 to 20 percent and are thus within the accuracy limits claimed for both methods.
Conference Committee Involvement (1)
European Symposium on Optics and Photonics for Defence and Security