Paper
9 October 2018 Nanosat-based detection and tracking of launch vehicles
Caroline Schweitzer, Max Gulde, Clemens Horch , Norbert Scherer-Negenborn, Karin Stein, Norbert Wendelstein
Author Affiliations +
Proceedings Volume 10794, Target and Background Signatures IV; 107940L (2018) https://doi.org/10.1117/12.2324700
Event: SPIE Security + Defence, 2018, Berlin, Germany
Abstract
Effective sensor technology for space based early warning and detection is a key component in the defense against immediate threats. These sensors have to be designed and optimized based on realistic infrared signatures of both, background (atmospheric, terrestrial) and rocket exhaust plume (or: ballistic missile exhaust plume). In both cases, the lack of observations causes the use of comprehensive simulation tools, either instead or in addition to ground measurement data. In the paper, we will present the preparatory investigations carried out for the conceptual design of an electro-optical (EO) payload based on a nanosatellite platform for the purpose of space-based early warning. Initially, this will comprise a description of the atmospheric simulation tool used at Fraunhofer IOSB, the application of those, and the assessment of detection and tracking algorithms. We will then give a short side note about ground measurement data. To conclude the paper, the experimental spacecraft based on nanosatellite technology (name: ERNST) will be introduced with a special focus on the EO payload designed by Fraunhofer EMI.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Caroline Schweitzer, Max Gulde, Clemens Horch , Norbert Scherer-Negenborn, Karin Stein, and Norbert Wendelstein "Nanosat-based detection and tracking of launch vehicles ", Proc. SPIE 10794, Target and Background Signatures IV, 107940L (9 October 2018); https://doi.org/10.1117/12.2324700
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Missiles

Sensors

Satellites

Mid-IR

Atmospheric modeling

Clouds

Detection and tracking algorithms

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