Title :
Tracking performance of leakage LMS for chirped signals
Author :
Ting, LK ; Cowan, C.F.N. ; Woods, R.F. ; Cork, P.R. ; Sprigings, C.J.
Author_Institution :
Sch. of Electr. & Electron. Eng., Queen´´s Univ., Belfast, UK
fDate :
6/23/1905 12:00:00 AM
Abstract :
The initial frequency pass-band of the LMS filter remains whilst tracking a non-stationary chirped signal. This past memory effect causes unwanted white noise to leak through the initial residual pass-band of the adaptive filter. A leakage term is applied to the LMS algorithm to remove the memory effect of the tracking filter which leads to a reduction in the noise power at the output of the adaptive filter. This reduced noise power is reflected in an improved SNR (signal-to-noise ratio) of a low SNR chirped signal compared to the standard LMS algorithm
Keywords :
adaptive filters; adaptive signal processing; filtering theory; least mean squares methods; prediction theory; tracking filters; white noise; LMS algorithm; LMS filter; SNR; adaptive LMS predictor; adaptive filter; leakage LMS; leakage term; memory effect; noise power reduction; nonstationary chirped signal tracking; past memory effect; residual pass-band; signal-to-noise ratio; tracking filter; tracking performance; white noise; Adaptive filters; Chirp; Frequency; Least squares approximation; Noise reduction; Radar applications; Radar tracking; Signal detection; Signal processing; Signal to noise ratio;
Conference_Titel :
Signal Processing Systems, 2001 IEEE Workshop on
Conference_Location :
Antwerp
Print_ISBN :
0-7803-7145-3
DOI :
10.1109/SIPS.2001.957335
