A sound source localization method based on improved second correlation time delay estimation
Open accessAbstract
The sound source localization (SSL) system based on the microphone array has important applications in audio and video conference, security monitoring and intelligent cockpit. However, the SSL method based on time difference of arrival is susceptible to ambient noise. Therefore, an improved second correlation delay estimation algorithm is proposed in this paper. The pure source signal is obtained by wavelet denoising, and then the time delay is calculated by the second correlation time delay estimation algorithm with the weighting functions of the smoothed coherence transform and the Roth processor. The position of the sound target is calculated from the time delay. Aiming at the moving target, an extended Kalman filter is introduced to track the moving trajectory of the sound source. The static and moving SSL simulations are conducted and the results of the proposed algorithm are compared with those of the single-weighted quadratic correlation (SQC) algorithm and the high-power quadratic correlation algorithm. The static sound source positioning errors of the proposed algorithm under −10 dB SNR are respectively 3.97 m and 5.86 m smaller than those of the HQC algorithm and the SQC algorithm. The moving SSL trajectory based on the proposed algorithm is still closest to the real track under −10 dB SNR. This indicates that the proposed algorithm has high precision and strong robustness for sound source location in the low signal-to-noise ratio (SNR) environment. In the experiment, the proposed algorithm can accurately calculate the direction of arrival (DOA) of static sound source and stably track DOA of moving sound source. This is consistent with the simulation results, which further verifies the effectiveness and practicability of the algorithm. This novel algorithm with high time delay estimation accuracy is of great significance for SSL in low SNR environment.
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Traditional weighting functions and the generalized cross-correlation algorithm have limited time delay estimation effect at a low SNR.
“Due to the limited time delay estimation effect of the traditional weighting function and generalized cross-correlation algorithm at a low SNR, many scholars have studied various improved weighting functions [7,8,9,10].”
From Research on the Improvement of the Signal Time Delay Estimation Method of Acoustic Positioning for Anti-Low Altitude UAVs (2025) · cites this paper as [10]
The Introduction states that the SQC and HQC methods use generalized weighting functions but still fail to estimate time delay accurately at low SNR. It does not make the same finding about traditional weighting functions or the generalized cross-correlation algorithm as a whole; Section 2.2 instead uses a weighted generalized cross-correlation function in the proposed method. No page numbers are available in our copy. (LLM, conf=0.84)
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Research works printed but not linked: 8
- Nguyen L, Miro J V and Qiu X 2019 Multilevel B-splines-based learning approach for sound source localization IEEE Sens. J. 19 3871-81 · DOI
- Yan Q, Chen J, Ottoy G and De Strycker L 2018 Robust AOA based acoustic source localization method with unreliable measurements Signal Process. 152 13-21 · DOI
- Bharathi B M R and Mohanty A R 2018 Underwater sound source localization by EMD-based maximum likelihood method Acoust. Aust. 46 193-203 · DOI
- Thomas B and Hunter A 2022 Coherence-induced bias reduction in synthetic aperture sonar along-track micronavigation IEEE J. Ocean. Eng. 47 162-78 · DOI
- Liu M, Nie L, Li S and Jia W 2019 Passive positioning of sound target based on HBT interference AIP Adv. 9 105120 · DOI
- Sadeghi M, Behnia F and Amiri R 2020 Optimal sensor placement for 2D range-only target localization in constrained sensor geometry IEEE Trans. Signal Process. 68 2316-27 · DOI
- Fiebig W and Dabrowski D 2020 Use of acoustic camera for noise sources localization and noise reduction in the industrial plant Arch. Acoust. 45 111-7 · DOI
- Mlynski R and Kozlowski E 2019 Localization of vehicle back-up alarms by users of level-dependent hearing protectors under industrial noise conditions generated at a forge Int. J. Environ. Res. Public Health 16 394 · DOI
Cited by
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Liu, M., Yu, J., & Yang, Z. (2025) · Sensors · doi:10.3390/s25092735 · Cited by 4 · see citing works
Self-citation
- Authors
- Liu, M., Zeng, Q., Jian, Z., Peng, Y., & Nie, L.
- Affiliations
- Hubei University of Technology (CN)
- Corresponding author
- Liu, Mengran
- Zeng, Qiang
- Jian, Zeming
- Nie, Lei
- ORCID
- Venue
- Measurement Science and Technology
- Publisher
- IOP Publishing
- Published
- 2023-01-04
- Volume
- 34
- Issue
- 4
- Pages
- 045102
- ISSN
- 0957-0233 (ISSN-L)
- 1361-6501
- OpenAlex
- W4309905913
- Cited by
- 17
- References
- 0
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 3 · 2023: 4
- FWCI
- 1.61
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Measurement Science and Technology (publishedVersion)
- Funders
- Scientific Research Foundation of Hubei University of Technology (GCRC2020010)
- Green Industry Technology Leading Project of Hubei University of Technology (XJ2021004901)
- National Natural Science Foundation of China (51805154)
- Topics
- Physical Sciences › Computer Science › Signal Processing › Direction-of-Arrival Estimation Techniques
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Physical Sciences › Computer Science › Signal Processing › Music and Audio Processing
- Keywords
- sound localization, microphone array, time difference of arrival, wavelet denoising, direction of arrival estimation, extended Kalman filter, low signal-to-noise ratio, ambient noise robustness
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