clutter removal
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2021 ◽  
Vol 19 ◽  
pp. 71-77
Author(s):  
Matthias G. Ehrnsperger ◽  
Maximilian Noll ◽  
Stefan Punzet ◽  
Uwe Siart ◽  
Thomas F. Eibert

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).



2021 ◽  
Author(s):  
Pongsathorn Chomdee ◽  
Akkarat Boonpoonga ◽  
Titipong Lertwiriyaprapa


Author(s):  
Kaya Kanemaru ◽  
Hiroshi Hanado ◽  
Katsuhiro Nakagawa


Author(s):  
Seshagiri D ◽  
Dyana A ◽  
K P Ray ◽  
Surendra Pal


2021 ◽  
Author(s):  
Baichuan Huang ◽  
Shuai D. Han ◽  
Abdeslam Boularias ◽  
Jingjin Yu




Author(s):  
John J. Pantoja ◽  
Eder F. Ruiz ◽  
Felix Vega ◽  
Daniel Chaparro-Arce ◽  
Chaouki Kasmi


2021 ◽  
Author(s):  
Asif Awaludin ◽  
Tiin Sinatra ◽  
Ginaldi A. Nugroho ◽  
Fadli Nauval


2021 ◽  
Vol 112 ◽  
pp. 179-192
Author(s):  
Anamiya Bhattacharya ◽  
Deepak Putrevu ◽  
Dharmendra Kumar Pandey ◽  
Arundhati Misra


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