Improved Generalized Cross Correlation Phase Transform Algorithm for Time Difference of Arrival Estimation

Tan, Chee Sheng; Mohd‐Mokhtar, Rosmiwati; Arshad, Mohd Rizal

doi:10.1007/978-981-13-3708-6_26

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…The GCC-PHAT weighting method [ 12 , 33 , 34 , 35 , 36 ] can achieve better delay estimation results when the signal-to-noise ratio is high and the reverberation is weak. This leads to false peaks and increases the delay estimation error.…”

Section: Theoretical Introduction Of Delay Estimation Optimization Al...mentioning

confidence: 99%

Optimization Algorithm for Delay Estimation Based on Singular Value Decomposition and Improved GCC-PHAT Weighting

Wang

et al. 2022

Sensors

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The accuracy of time delay estimation seriously affects the accuracy of sound source localization. In order to improve the accuracy of time delay estimation under the condition of low SNR, a delay estimation optimization algorithm based on singular value decomposition and improved GCC-PHAT weighting (GCC-PHAT-ργ weighting) is proposed. Firstly, the acoustic signal collected by the acoustic sensor array is subjected to singular value decomposition and noise reduction processing to improve the signal-to-noise ratio of the signal; then, the cross-correlation operation is performed, and the cross-correlation function is processed by the GCC-PHAT-ργ weighting method to obtain the cross-power spectrum; finally, the inverse transformation is performed to obtain the generalized correlation time domain function, and the peak detection is performed to obtain the delay difference. The experiment was carried out in a large outdoor pool, and the experimental data were processed to compare the time delay estimation performance of three methods: GCC-PHAT weighting, SVD-GCC-PHAT weighting (meaning: GCC-PHAT weighting based on singular value decomposition) and SVD-GCC-PHAT-ργ weighting (meaning: GCC-PHAT-ργ weighting based on singular value decomposition). The results show that the delay estimation optimization algorithm based on SVD-GCC-PHAT-ργ improves the delay estimation accuracy by at least 37.95% compared with the other two methods. The new optimization algorithm has good delay estimation performance.

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Section: Theoretical Introduction Of Delay Estimation Optimization Al...mentioning

confidence: 99%

Optimization Algorithm for Delay Estimation Based on Singular Value Decomposition and Improved GCC-PHAT Weighting

Wang

et al. 2022

Sensors

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show abstract

Sound source localization of harmonic sources in entire 3D space using just 5 acoustic signals

Thakur

Singh

2022

Applied Acoustics

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Modified Frequency-Sliding Generalized Cross Correlation for Time Delay Difference Estimation of Microphone Array

Song,

2023

IEEE Sensors J.

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Improved Generalized Cross Correlation Phase Transform Algorithm for Time Difference of Arrival Estimation

Cited by 4 publications

References 2 publications

Optimization Algorithm for Delay Estimation Based on Singular Value Decomposition and Improved GCC-PHAT Weighting

Optimization Algorithm for Delay Estimation Based on Singular Value Decomposition and Improved GCC-PHAT Weighting

Sound source localization of harmonic sources in entire 3D space using just 5 acoustic signals

Modified Frequency-Sliding Generalized Cross Correlation for Time Delay Difference Estimation of Microphone Array

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