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.
Computer programs for prediction of optical signatures of targets and backgrounds are valuable tools for signature assessment and signature management. Simulations make it possible to study optical signatures from targets and backgrounds under conditions where measured signatures are missing or incomplete. Several applications may be identified: Increase understanding, Design and assessment of low signature concepts, Assessment of tactics, Design and assessment of sensor systems, Duel simulations of EW, and Signature awareness. FOI (the Swedish Defence Research Agency) study several methods and modeling programs for detailed physically based prediction of the optical signature of targets in backgrounds. The most important commercial optical signature prediction programs available at FOI are CAMEO-SIM, RadThermIR, and McCavity. The main tasks of the work have been: Assembly of a database of input data, Gain experience of different computer programs, In-house development of complementary algorithms and programs, and Validation and assessment of the simulation results. This paper summarizes the activities and the results obtained. Some application examples will be given as well as results from validations. The test object chosen is the MTLB which is a tracked armored vehicle. It has been used previously at FOI for research purposes and therefore measurement data is available.
The ignition of LOVA gun propellants at low loading densities is of interest for future gun systems with insensitive modular charges. The ignition system in conventional propellant systems is traditionally optimized for high loading densities. There is a need to be able to control the ignition for the envelop of the system, to reduce unburnt propellant at low loading densities and, at the same time, avoid pressure waves at high loading densities. Plasma ignition is interesting for this application, with the possibility to vary ignition energy and with the plasma plume penetrating deep into the propellant bed to achieve uniform ignition. This paper presents results from plasma ignition experiments in a 45-mm gun system, using NL008, an RDX-based CAB-LOVA propellant. The plasma igniter is a capillary jet type, driven by a pulse-forming network. A zero-dimensional model for the plasma igniter has been developed and will be discussed in the context of the experiments.
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