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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Karabacak, C. Gurbuz, S.Z. Gurbuz, A.C. Guldogan, M.B. Hendeby, G. Gustafsson, F. |
| Copyright Year | 2004 |
| Abstract | Micro-Doppler radar signatures have great potential for classifying pedestrians and animals, as well as their motion pattern, in a variety of surveillance applications. Due to the many degrees of freedom involved, real data need to be complemented with accurate simulated radar data to be able to successfully design and test radar signal processing algorithms. In many cases, the ability to collect real data is limited by monetary and practical considerations, whereas in a simulated environment, any desired scenario may be generated. Motion capture (MOCAP) has been used in several works to simulate the human micro-Doppler signature measured by radar; however, validation of the approach has only been done based on visual comparisons of micro-Doppler signatures. This work validates and, more importantly, extends the exploitation of MOCAP data not just to simulate micro-Doppler signatures but also to use the simulated signatures as a source of a priori knowledge to improve the classification performance of real radar data, particularly in the case when the total amount of data is small. |
| Sponsorship | IEEE Geoscience and Remote Sensing Society |
| Starting Page | 2125 |
| Ending Page | 2129 |
| Page Count | 5 |
| File Size | 769359 |
| File Format | |
| ISSN | 1545598X |
| Volume Number | 12 |
| Issue Number | 10 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feature extraction Radar cross-sections Doppler radar Doppler effect Mathematical model Legged locomotion motion capture (MOCAP) Classification human micro-Doppler knowledge-based signal processing |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology |
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