Range-doppler radar target detection using denoising within the compressive sensing framework
Akin Sevimli, R.
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27385
European Signal Processing Conference
- Conference Paper 
European Signal Processing Conference, EUSIPCO
Compressive sensing (CS) idea enables the reconstruction of a sparse signal from a small set of measurements. CS approach has applications in many practical areas. One of the areas is radar systems. In this article, the radar ambiguity function is denoised within the CS framework. A new denoising method on the projection onto the epigraph set of the convex function is also developed for this purpose. This approach is compared to the other CS reconstruction algorithms. Experimental results are presented1. © 2014 EURASIP.
Showing items related by title, author, creator and subject.
Duman, K.; Eryildirim, A.; Cetin, A.E. (2009)In this paper, a novel descriptive feature parameter extraction method from synthetic aperture radar (SAR) images is proposed. The new approach is based on region covariance (RC) method which involves the computation of a ...
Duman, K.; Çetin, A.E. (2010)Target detection in SAR images using region covariance (RC) and codifference methods is shown to be accurate despite the high computational cost. The proposed method uses directional filters in order to decrease the search ...
Range-Doppler radar target detection using compressive sensing [Sikiştirilmiş algilama kullanarak Uzaklik-Doppler radar hedef tespiti] Sevimli, R.A.; Tofighi, M.; Cetin, A.E. (IEEE Computer Society, 2014)Compressive sensing (CS) idea enables the reconstruction of a sparse signal from small number of measurements. CS approach has many applications in many areas. One of the areas is radar systems. In this article, the radar ...