Title :
Range-doppler radar target detection using denoising within the compressive sensing framework
Author :
Sevimli, R. Akin ; Tofighi, Mohammad ; Cetin, A. Enis
Author_Institution :
Dept. of Electr. & Electron. Eng., Bilkent Univ., Ankara, Turkey
Abstract :
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.
Keywords :
Doppler radar; graph theory; object detection; radar signal processing; set theory; signal denoising; signal reconstruction; CS algorithms; compressive sensing framework; convex function; denoising method; epigraph set; radar ambiguity function; range-Doppler radar target detection; sparse signal reconstruction; Compressed sensing; Matching pursuit algorithms; Noise reduction; Radar imaging; Signal processing algorithms; Vectors; Ambiguity Function; Compressive Sensing; Denoising; Radar Signal Processing;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon