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Computation and visualization concept for reconnaissance requirement

: Eckel, S.; Geisler, J.

Postprint urn:nbn:de:0011-n-791978 (1.4 MByte PDF)
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Copyright 2008 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Created on: 28.8.2009

Kim, M.S. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Defense and security 2008: Special Sessions on Food Safety, Visual Analytics, Resource Restricted Embedded and Sensor Networks, and 3D Imaging and Display : 17 - 18 March 2008, Orlando, Florida, USA
Bellingham, WA: SPIE, 2008 (Proceedings of SPIE 6983)
ISBN: 978-0-8194-7181-9
Paper 69830D
Defense and Security Conference (DSS) <2008, Orlando/Fla.>
Conference Paper, Electronic Publication
Fraunhofer IITB ( IOSB) ()

The quantity and variety of sensors, available for reconnaissance and surveillance is larger than ever before. However, increasing the number of sensors results in escalating costs and efforts to analyze the sensor data. Hence it is obvious that with an increasing number of available sensors the task to determine where reconnaissance requirement is highest and what sensor combination to use in order to close the information gap becomes more and more complex. Therefore semiautomated systems are needed to assist the commander of reconnaissance sources. Nevertheless the final decision about sensor deployment is often made by humans. Thus a module is needed to display the current situation to the decision maker in a way that allows him to understand the situation at first glance. Using knowledge about what men are better at, and what machines are better at, we developed on the one hand a mathematical model that allows us determine decision relevant measures in reconnaissance tasks. On the other hand a visualization concept for reconnaissance requirement, which visualizes in an intuitive way where reconnaissance requirement is highest, has been developed.