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- Title
Dynamic Eigenimage Based Background and Clutter Suppression for Ultra Short-Range Radar.
- Authors
Ehrnsperger, Matthias G.; Noll, Maximilian; Punzet, Stefan; Siart, Uwe; Eibert, Thomas F.
- Abstract
Background and clutter suppression techniques are important towards the successful application of radar in complex environments. We investigate eigenimage based methodologies such as principal component analysis (PCA) and apply it to frequency modulated continuous wave (FMCW) radar. The designed dynamic principal component analysis (dPCA) algorithm dynamically adjusts the number of eigenimages that are utilised for the processing of the signal. Furthermore, the algorithm adapts towards the number of objects in the field of view as well as the estimated distances. For the experimental evaluation, the dPCA algorithm is implemented in a multi-static FMCW radar prototype that operates in the K-band at 24 GHz. With this background and clutter removal method, it is possible to increase the signal-to-clutter-ratio (SCR) by 4.9 dB compared to standard PCA with mean removal (MR).
- Subjects
RADAR; PRINCIPAL components analysis; SIGNAL processing; BISTATIC radar
- Publication
Advances in Radio Science, 2021, Vol 19, p71
- ISSN
1684-9965
- Publication type
Academic Journal
- DOI
10.5194/ars-19-71-2021