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Proceedings Paper

Decomposing radar measurements through comprehensive response modeling
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Paper Abstract

Radars are used for various purposes, and we need flexible methods to explain radar response phenomena. In general, modeling radar response and backscatterers can help in data analysis by providing possible explanations for measured echoes. However, extracting exact physical parameters of a real world scene from radar measurements is an ill-posed problem. Our study aims to enhance radar signal interpretation and further to develop data classification methods. In this paper, we introduce an approach for finding physically sensible explanations for response phenomena during a long illumination. The proposed procedure uses our comprehensive response model to decompose measured radar echoes. The model incorporates both a radar model and a backscatterer model. The procedure adapts the backscatterer model parameters to catch and reproduce a measured Doppler spectrum and its dynamics at a particular range and angle. A filter bank and a set of features are used to characterize these response properties. The procedure defines a number of point-scatterers for each frequency band of the measured Doppler spectrum. Using the same features calculated from simulated response, it then matches the parameters-the number of individual backscatterers, their radar cross sections and velocities-to joint Doppler and amplitude behavior of the measurement. Hence we decompose the response toward its origin. The procedure is scalable and can be applied to adapt the model to various other features as well, even those of more complex backscatterers. Performance of the procedure is demonstrated with radar measurements on controlled arrangement of backscatterers with a variety of motion states.

Paper Details

Date Published: 11 May 2009
PDF: 10 pages
Proc. SPIE 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII, 73361K (11 May 2009); doi: 10.1117/12.818990
Show Author Affiliations
Ilkka Venäläinen, Tampere Univ. of Technology (Finland)
Juha Jylhä, Tampere Univ. of Technology (Finland)
Ville Väisänen, Tampere Univ. of Technology (Finland)
Juho Vihonen, Tampere Univ. of Technology (Finland)
Marja Ruotsalainen, Tampere Univ. of Technology (Finland)
Ari Visa, Tampere Univ. of Technology (Finland)


Published in SPIE Proceedings Vol. 7336:
Signal Processing, Sensor Fusion, and Target Recognition XVIII
Ivan Kadar, Editor(s)

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