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Information management and target detection for multisensor airborne platforms

: Jäger, K.; Hebel, Marcus; Armbruster, W.; Bers, K.-H.

Postprint urn:nbn:de:0011-n-1007610 (1.1 MByte PDF)
MD5 Fingerprint: 20897c2b40df91c6e49c046bf24fd3f2
Copyright 2006 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: 26.9.2009

Kadar, I. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Signal processing, sensor fusion, and target recognition XV : 17 - 19 April 2006, Kissimmee, Florida, USA
Bellingham, WA: SPIE, 2006 (Proceedings of SPIE 6235)
ISBN: 0-8194-6291-8
ISBN: 978-0-8194-6291-6
Paper 62350J
Conference "Signal Processing, Sensor Fusion, and Target Recognition" <15, 2006, Kissimmee/Fla.>
Conference Paper, Electronic Publication
Fraunhofer FOM ( IOSB)
sensor fusion; target detection; information management; knowledge base; moving platform

Future military helicopters will be provided with multiple information sources for self-protection and reconnaissance, e.g. imaging IR, laser radar and GPS. In addition, knowledge bases like maps, aerial images, geographical information (GIS) and other previously acquired data can be used for the interpretation of the current scenario. To support the mission, results of data fusion and information management have to be presented to the pilot in an appropriate way. This paper describes concepts and results of our work on IR and laser data fusion for airborne systems. Data is gathered by forward-looking sensors mounted in a helicopter. For further improvement, fusion with collateral information (laser elevation data, aerial images) is used for change detection and definition of regions of interest with respect to the stored and continuously updated database. Results are demonstrated by the analysis of an exemplary data set, showing a scenario with a group of vehicles. Two moving vehicles are detected automatically in both channels (IR, laser) and the results are combined to achieve improved visualization for the pilot.