Title :
Adaptive time delay estimation with noise suppression for sinusoidal signals
Author_Institution :
Dept. of Comput. Eng. & Inf. Technol., City Univ. of Hong Kong, Kowloon, China
Abstract :
A least mean square algorithm is devised for time delay estimation between noisy sinusoidal signals received at two spatially separated sensors. Two adaptive finite impulse response (FIR) filters whose coefficients are samples of a sine function are used for delay modeling as well as noise suppression. The convergence behavior and variance of the estimated delay are also derived. Computer simulations are presented to validate the theoretical derivations of the proposed estimator for static and linearly varying delays.
Keywords :
FIR filters; adaptive filters; adaptive signal processing; convergence of numerical methods; delay estimation; interference suppression; least mean squares methods; FIR filter coefficients; LMS-style algorithm; adaptive finite impulse response filters; adaptive time delay estimation; convergence; delay modeling; estimated delay variance; least mean square algorithm; linearly varying delays; noise suppression; propagation delay; sinusoidal signal delay estimation; spatially separated sensors; static delays; Adaptive filters; Computer simulation; Delay effects; Delay estimation; Delay lines; Finite impulse response filter; Information technology; Least mean square algorithms; Signal to noise ratio; Sonar navigation;
Conference_Titel :
Circuits and Systems, 2002. MWSCAS-2002. The 2002 45th Midwest Symposium on
Print_ISBN :
0-7803-7523-8
DOI :
10.1109/MWSCAS.2002.1186885
