Computer models have been developed and used to predict the performance of vehicles equipped with advanced fuel and power train technologies such as hybrid electric or fuel cells. However, simulations that describe the interaction of the vehicle with the rest of the vehicle fleet and infrastructure are just emerging. This paper documents the results of an experiment to demonstrate the utility of these types of simulations. The experiment examined the business case of fielding hybrid electric, high-mobility multipurpose wheeled vehicles (HE HMMWVs) in a future Army organization. The hypothesis was that fielding HE vehicles would significantly reduce fuel consumption due to the economy offered by the HE technology and reducing the number of generators as a result of using the vehicles to generate electrical power. The Logistical and Combat Systems Simulation (LOCSS) was used to estimate differences in fuel consumption and associated equipment during a 72-hour operation with and without HE HMMWVs. There was a 25 percent reduction in fuel consumption over the systems examined. However, due to the relatively low density of the HE vehicles in the organization, the total difference in fuel consumption was not operationally significant; and the savings in fuel costs did not overcome the additional procurement costs over a twenty-year life cycle.
Proc. SPIE. 5808, Algorithms for Synthetic Aperture Radar Imagery XII
KEYWORDS: Signal to noise ratio, 3D acquisition, Detection and tracking algorithms, Data modeling, Synthetic aperture radar, Computer simulations, Clouds, 3D modeling, Device simulation, 3D image processing
Methods of generating more literal, easily interpretable imagery from 3-D SAR data are being studied to provide all weather, near-visual target identification and/or scene interpretation. One method of approaching this problem is to automatically generate shape-based geometric renderings from the SAR data. In this paper we describe the application of the Marching Tetrahedrons surface finding algorithm to 3-D SAR data. The Marching Tetrahedrons algorithm finds a surface through the 3-D data cube, which provides a recognizable representation of the target surface. This algorithm was applied to the public-release X-patch simulations of a backhoe, which provided densely sampled 3-D SAR data sets. The performance of the algorithm to noise and spatial resolution were explored. Surface renderings were readily recognizable over a range of spatial resolution, and maintained their fidelity even under relatively low Signal-to-Noise Ratio (SNR) conditions.