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

fYear

2014

fDate

1-5 Sept. 2014

Firstpage

1950

Lastpage

1954

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European

Conference_Location

Lisbon

Type

conf

Filename

6952710