scholarly journals Envelope and Wavelet Transform for Sound Localisation at Low Sampling Rates in Wireless Sensor Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
O. M. Bouzid ◽  
G. Y. Tian ◽  
J. Neasham ◽  
B. Sharif
Keyword(s):  
Wavelet Transform ◽  
Time Delay ◽  
Sampling Rate ◽  
Time Delay Estimation ◽  
Wireless Sensor ◽  
Estimation Accuracy ◽  
Memory Space ◽  
Time Frequency ◽  
Sound Localisation ◽  
Huge Data

High sampling frequencies in acoustic wireless sensor network (AWSN) are required to achieve precise sound localisation. But they are also mean analysis time and memory intensive (i.e., huge data to be processed and more memory space to be occupied which form a burden on the nodes limited resources). Decreasing sampling rates below Nyquist criterion in acoustic source localisation (ASL) applications requires development of the existing time delay estimation techniques in order to overcome the challenge of low time resolution. This work proposes using envelope and wavelet transform to enhance the resolution of the received signals through the combination of different time-frequency contents. Enhanced signals are processed using cross-correlation in conjunction with a parabolic fit interpolation to calculate the time delay accurately. Experimental results show that using this technique, estimation accuracy was improved by almost a factor of 5 in the case of using 4.8 kHz sampling rate. Such a conclusion is useful for developing precise ASL without the need of any excessive sensor resources, particularly for structural health monitoring applications.

scholarly journals Wavelet transform-based cross-correlation in the time-delay estimation applications

2021 ◽  
Vol 2142 (1) ◽  
pp. 012019
Author(s):  
S B Sharkova ◽  
V A Faerman
Keyword(s):  
Wavelet Transform ◽  
Time Delay ◽  
Cross Correlation ◽  
Fourier Transforms ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Practical Case ◽  
Discrete Fourier Transforms ◽  
Time Frequency ◽  
Dyadic Wavelet

Abstract The article discusses the application of wavelet analysis for the time-frequency time-delay estimation. The proposed algorithm is wavelet transform-based cross-correlation time delay estimation that applies discrete time wavelet transform to filter the input signal prior to computation of cross-correlation function. The distinguishing feature of the algorithm that it uses the variation of continuous wavelet transform to process the discrete signals instead of dyadic wavelet transform that is normally applied to the case. Another feature that the implication of convolution theorem is used to compute coefficients of the wavelet transform. This makes possible to omit redundant discrete Fourier transforms and significantly reduce the computational complexity. The principal applicability of the proposed method is shown in the course of a computational experiments with artificial and real-world signal. So the method demonstrated expected selectivity for the signals localized in the different frequency bands. The application of the method to practical case of pipeline leak detection was also successful. However, the study concluded that this method provides no specific advantages in comparison with the conventional one. In the future, alternative applications in biological signal processing will be considered.

A Combined Interpolation Method for Cross Correlation Based Particle Velocity Measurement

2012 ◽  
Vol 508 ◽  
pp. 67-70
Author(s):  
Gang Yang ◽  
Wei Dong Li ◽  
Yu Tao Wang ◽  
Ming Yu Li
Keyword(s):  
Correlation Function ◽  
Velocity Measurement ◽  
Cross Correlation ◽  
Interpolation Method ◽  
Sampling Rate ◽  
Time Delay Estimation ◽  
Parametric Models ◽  
Center Frequency ◽  
Estimation Accuracy ◽  
Particulate Solids

Cross correlation techniques have been proved to be a valuable tool for online continuous velocity measurement of particulate solids in pneumatic pipelines. In order to reduce computational complexity the sampling frequency is usually kept as low as possible, and the peak in the correlation function is found by interpolating the correlation function. Parabola functions are commonly used as parametric models of the cross correlation function in time delay estimation. However, the parabolic-fit interpolation method introduces a bias at low sampling rate to the center frequency ratio of input signal. In this paper, a combined interpolation method is proposed to improve the estimation accuracy. Experiments are carried out to evaluate the performance of the proposed interpolation method for low sampling rate. The experimental results have been promising and have shown the potential of the proposed method for particle flow velocity measurements.

Time Delay Estimation Using Continuous Wavelet Transform Coefficients

2017 ◽  
Vol 23 (2) ◽  
pp. 1299-1303 ◽  
Author(s):  
A. B Osman ◽  
M Ovinis ◽  
F. M Hashim ◽  
Kh Mohammed ◽  
H Osei
Keyword(s):  
Wavelet Transform ◽  
Time Delay ◽  
Continuous Wavelet Transform ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Continuous Wavelet ◽  
Transform Coefficients

A Biologically Inspired Coupled Microphone Array for Sound Source Bearing Estimation

2017 ◽  
Vol 140 (1) ◽  
Author(s):  
Yaqiong Zhang ◽  
Ming Yang ◽  
Xinlei Zhu ◽  
Na Ta ◽  
Zhushi Rao
Keyword(s):  
Time Delay ◽  
Sound Source ◽  
Microphone Array ◽  
Time Delay Estimation ◽  
Estimation Accuracy ◽  
Coupling Mechanism ◽  
Mechanical Coupling ◽  
Bearing Estimation ◽  
Localization Ability ◽  
Output Filter

The Ormia ochracea, a species of parasitic fly, has a remarkable localization ability despite the tiny interaural distance compared with the incoming wavelength. The mechanical coupling between its ears enhances the differences of the two received signals, the main cues to locate the source. Inspired by the coupling mechanism, we present a miniature coupled two-microphone array for estimating sound source horizontal bearing. The coupled array consists of a standard two-microphone array and a two-input, two-output filter which implements the coupling. The relationship between filter parameters and time delay magnification is investigated to provide theoretical support for array design. With appropriate parameters, the time delay of received signals can be linearly magnified. Based on the linear magnification, we present a method for estimating source direction using the coupled array. The influence of time delay magnification on time delay estimation accuracy is explored through the general cross-correlation (GCC) method. Experiments are conducted to verify the coupled array and demonstrate its advantages on improving the resolution of estimation of time delay and accuracy of bearing estimation compared with the standard array with the same element spacing.

A Fast and Efficient Time-Delay Estimation Algorithm for Sound Localization

2011 ◽  
Vol 474-476 ◽  
pp. 1201-1204 ◽  
Author(s):  
Guan Qun Liu ◽  
Ru Bo Zhang ◽  
Dong Xu
Keyword(s):  
Time Delay ◽  
Sound Localization ◽  
Cross Correlation ◽  
Estimation Algorithm ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Important Research ◽  
Memory Space ◽  
Important Research Topic ◽  
Original Time

Time-delay estimation is an important research topic of sound localization. According to the specificity of time-delay in sound localization, a fast and efficient time-delay estimation algorithm is proposed based on the principle of fast linear cross correlation. Relative to the original time-delay estimation algorithm based on fast linear cross correlation, the proposed algorithm has enormous advantages in the time complexity and space complexity. The computing speed is twice faster than the original time-delay estimation algorithm, while the size of the memory space used is half of the original time-delay estimation algorithm.

Sign in / Sign up

Export Citation Format

Share Document