一种基于LMS自适应滤波的互相关时延估计优化算法

doi:10.16180/j.cnki.issn1007-7820.2020.06.006

Abstract

Abstract:

In multi-station time difference positioning system, when using the cross-correlation method based on LMS adaptive filtering for time delay estimation, the fixed step factor has a large contradiction between convergence speed and steady-state offset, which affects the accuracy of delay estimation. Aiming at this problem, a cross-correlation time delay estimation optimization algorithm based on piecewise variable step size LMS adaptive filtering and Hilbert difference was proposed in this study. Firstly, the piecewise variable step size LMS adaptive filtering was used to filter the signal, then the filtered signal was cross-correlated, and finally the peak of the correlation function was sharpened by the Hilbert difference method to obtain higher delay estimation accuracy. Under the same conditions, the time delay estimation accuracy of different algorithms was simulated and analyzed. The results showed that the proposed optimization algorithm had higher delay estimation accuracy, and the prediction accuracy could be improved by 2.2% compared with the traditional method under different SNR, indicating proposed algorithm presented good anti-noise performance.

Key words: TDOA location, adaptive filtering, CC, VSS-LMS, time delay estimation, Hilbert difference

CLC Number:

TN95

WEI Wenliang,MAO Yulong. Cross-correlation Time Delay Estimation Optimization Algorithm Based on LMS Adaptive Filtering[J].Electronic Science and Technology, 2020, 33(6): 29-34.

Figures/Tables 12

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References 16

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SNR	算法1	算法2	算法3
20 dB	1.035×10^-6 s	1.030×10^-6 s	1.015×10^-6 s
10 dB	1.040×10^-6 s	1.025×10^-6 s	1.020×10^-6 s
0 dB	1.060×10^-6 s	1.030×10^-6 s	1.025×10^-6 s
-5 dB	-	1.085×10^-6 s	1.040×10^-6 s

时延估计方法	真实时延	估计均值	估计均值标准差	估计误差
算法1	1	1.034	0.034	3.4%
算法2	1	1.030	0.030	3.0%
算法3	1	1.012	0.012	1.2%

时延估计方法	真实时延	估计均值	估计均值标准差	估计误差
算法1	1	1.037 75	0.037 75	3.775%
算法2	1	1.031 00	0.031 00	3.100%
算法3	1	1.013 25	0.013 25	1.325%

时延估计方法	真实时延	估计均值	估计均值标准差	估计误差
算法1	1	1.053 00	0.053 00	5.300%
算法2	1	1.033 25	0.033 25	3.325%
算法3	1	1.020 75	0.020 75	2.075%

时延估计方法	真实时延	估计均值	估计均值标准差	估计误差
算法1	1	-	-	-
算法2	1	1.061 25	0.061 25	6.125%
算法3	1	1.031 00	0.031 00	3.100%

Cross-correlation Time Delay Estimation Optimization Algorithm Based on LMS Adaptive Filtering

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