Title :
Block Least Mean Squares processing of noise radar waveforms
Author :
Michal Meller;Stanislaw Tujaka
Author_Institution :
Telecommunications Research Institute S.A., Department of Signal and Information Processing, Poligonowa 30, 04-051 Warsaw, Poland
Abstract :
Noise radars usually employ correlation processing of waveforms. However, vulnerability to clutter is a serious disadvantage of this approach. This paper considers using Least Squares (LS) based methods. In particular, highly efficient Block Least Mean Squares (Block LMS) algorithm is studied in details. The formula for integration gain of Block LMS is derived. Compared to analogue quantity for correlation processing, it shows significant advantage of the proposed solution in terms of robustness to clutter. The Doppler response of the algorithm is analyzed, which - under proper choice of algorithm parameters - is identical to that of correlation approach. Simulation experiments confirm that when heavy clutter is present, the proposed method outperforms correlation processing significantly.
Keywords :
"Least squares approximation","Matched filters","Radar signal processing","Clutter","Signal processing","Signal processing algorithms","Doppler radar","System identification","Least squares methods","Robustness"
Conference_Titel :
Radar Conference, 2009 IEEE
Print_ISBN :
978-1-4244-2870-0
Electronic_ISBN :
2375-5318
DOI :
10.1109/RADAR.2009.4976926