Full Text:
<2170>
Summary: 
<1619>
CLC number: TN911
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2016-09-20
Cited: 0
Clicked: 5995
An enhanced mixed modulated Lagrange explicit time delay estimator with noisy input
| ||||||||||||||
Wei Xia, Ju-lei Zhu, Wen-ying Jiang, Ling-feng Zhu. An enhanced mixed modulated Lagrange explicit time delay estimator with noisy input[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(10): 1067-1073.
@article{title="An enhanced mixed modulated Lagrange explicit time delay estimator with noisy input",
author="Wei Xia, Ju-lei Zhu, Wen-ying Jiang, Ling-feng Zhu",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="17",
number="10",
pages="1067-1073",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500417"
}
%0 Journal Article
%T An enhanced mixed modulated Lagrange explicit time delay estimator with noisy input
%A Wei Xia
%A Ju-lei Zhu
%A Wen-ying Jiang
%A Ling-feng Zhu
%J Frontiers of Information Technology & Electronic Engineering
%V 17
%N 10
%P 1067-1073
%@ 2095-9184
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500417
TY - JOUR
T1 - An enhanced mixed modulated Lagrange explicit time delay estimator with noisy input
A1 - Wei Xia
A1 - Ju-lei Zhu
A1 - Wen-ying Jiang
A1 - Ling-feng Zhu
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 17
IS - 10
SP - 1067
EP - 1073
%@ 2095-9184
Y1 - 2016
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1500417
Abstract: The mixed modulated Lagrange explicit time delay estimation (MMLETDE) algorithm provides an efficient time delay estimation between narrowband or sinusoidal signals. However, it does not explicitly consider the additive measurement noise at the input, which actually exists in practice. Aiming at this issue, an enhanced MMLETDE algorithm is proposed for noisy inputs based on the unbiased impulse response estimation technique, assuming that the noise power ratio is known {a priori}. Simulation results show that for narrowband signals or sinusoids over a wide frequency range, the proposed algorithm with a small filter order performs well in moderate and high noise scenarios.
[1]Benesty, J., Chen, J., Huang, Y., 2004. Time-delay estimation via linear interpolation and cross correlation. IEEE Trans. Speech Audio Process., 12(5):509-519.
[2]Carter, G.C., 1987. Coherence and time delay estimation. Proc. IEEE, 75(2):236-255.
[3]Chakraborty, M., So, H.C., 2007. New adaptive algorithm for delay estimation of sinusoidal signals. IEEE Signal Process. Lett., 14(12):984-987.
[4]Chen, S., Ho, K.C., 2013. Achieving asymptotic efficient performance for squared range and squared range difference localizations. IEEE Trans. Signal Process., 61(11):2836-2849.
[5]Cheng, Z., Tjhung, T.T., 2003. A new time delay estimator based on ETDE. IEEE Trans. Signal Process., 51(7):1859-1869.
[6]Dooley, S.R., Nandi, A.K., 1999. Adaptive subsample time delay estimation using Lagrange interpolators. IEEE Signal Process. Lett., 6(3):65-67.
[7]Jamalabdollahi, M., Zekavat, S., 2015. Time of arrival estimation in wireless sensor networks via OFDMA. Vehicular Technology Conf., p.1-6.
[8]Knapp, C.H., Carter, G.C., 1976. The generalized correlation method for estimation of time delay. IEEE Trans. Acoust. Speech Signal Process., 24(4):320-327.
[9]Li, X., Ma, X., Yan, S., et al., 2012. Super-resolution time delay estimation for narrowband signal. IEEE Proc. Radar Sonar Navig., 6(8):781-787.
[10]Patwari, N., Ash, J.N., Kyperountas, S., et al., 2005. Locating the nodes: cooperative localization in wireless sensor networks. IEEE Signal Process. Mag., 22(4):54-69.
[11]Piersol, A.G., 1981. Time delay estimation using phase data. IEEE Trans. Acoust. Speech Signal Process., 29(3):471-477.
[12]Regalia, P.A., 1994. An unbiased equation error identifier and reduced-order approximations. IEEE Trans. Signal Process., 42(6):1397-1412.
[13]Sadler, B., Kozick, R., 2006. A survey of time delay estimation performance bounds. IEEE Workshop on Sensor Array and Multichannel Processing, p.282-288.
[14]So, H.C., 2001. LMS based algorithm for unbiased FIR filtering with noisy measurements. Electron. Lett., 37(23):1418-1420.
[15]So, H.C., 2002. Noisy input-output system identification approach for time delay estimation. Signal Process., 82(10):1471-1475.
[16]So, H.C., Ching, P.C., 2001. Comparative study of five LMS-based adaptive time delay estimators. IEEE Proc. Radar Sonar Navig., 148(1):9-15.
[17]So, H.C., Ching, P.C., Chan, Y.T., 1994. A new algorithm for explicit adaptation of time delay. IEEE Trans. Signal Process., 42(7):1816-1820.
[18]So, H.C., Ching, P.C., Chan, Y.T., 1995. An improvement to the explicit time delay estimator. Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, p.3151-3154.
[19]Widrow, B., Steams, S.D., 1985. Adaptive Signal Processing. Prentice-Hall, Inc., Englewood Cliffs, NJ,
[20]Zhong, S., Xia, W., Song, J.X., et al., 2013. Super-resolution time delay estimation in multipath environments using normalized cross spectrum. Int. Conf. on Communications, Circuits and Systems, p.288-291.
[21]Zhong, S., Xia, W., He, Z.S., et al., 2014. Time delay estimation in the presence of clock frequency error. Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, p.2977-2981.
[22]Zhong, S., Xia, W., He, Z.S., 2015. Multipath time delay estimation based on Gibbs sampling under incoherent reception environment. IEICE Trans. Fundam. Electron. Commun. Comput. Sci., E98.A(6):1300-1304.
ORCID: 
Open peer comments: Debate/Discuss/Question/Opinion
<1>