TY - JOUR
T1 - Dynamic Eigenimage Based Background and Clutter Suppression for Ultra Short-Range Radar
AU - Ehrnsperger, Matthias G.
AU - Noll, Maximilian
AU - Punzet, Stefan
AU - Siart, Uwe
AU - Eibert, Thomas F.
N1 - Publisher Copyright:
© 2021 Matthias G. Ehrnsperger et al.
PY - 2021/12/17
Y1 - 2021/12/17
N2 - 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 24GHz. With this background and clutter removal method, it is possible to increase the signal-to-clutter-ratio (SCR) by 4.9dB compared to standard PCA with mean removal (MR).
AB - 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 24GHz. With this background and clutter removal method, it is possible to increase the signal-to-clutter-ratio (SCR) by 4.9dB compared to standard PCA with mean removal (MR).
UR - http://www.scopus.com/inward/record.url?scp=85122010767&partnerID=8YFLogxK
U2 - 10.5194/ars-19-71-2021
DO - 10.5194/ars-19-71-2021
M3 - Article
AN - SCOPUS:85122010767
SN - 1684-9965
VL - 19
SP - 71
EP - 77
JO - Advances in Radio Science
JF - Advances in Radio Science
ER -