Passive positioning of sound target based on HBT interference

Liu, Mengran; Nie, Linru; Li, Shanqiang; Wen, Jia

doi:10.1063/1.5121737

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…In 2017, Hong et al (2017) successfully detected the energy of a single phonon using HBT interference. In 2019, Liu et al (2019) successfully introduced HBT interference to airborne acoustic localization and experimentally verified the rationality and superiority of the method used in acoustic fields.…”

Section: Introductionmentioning

confidence: 95%

Underwater target passive acoustic localization method based on Hanbury Brown–Twiss interference

Liu

Zeng

Jian

et al. 2022

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Purpose Acoustic signals of the underwater targets are susceptible to noise, reverberation, submarine topography and biology, therefore it is difficult to precisely locate underwater targets. This paper proposes a new underwater Hanbury Brown-Twiss (HBT) interference passive localization method. This study aims to achieve precise location of the underwater acoustic targets. Design/methodology/approach The principle of HBT interference with ultrasensitive detection characteristics in optical measurements was introduced in the field of hydroacoustics. The coherence of the underwater target signal was analyzed using the HBT interference measurement principle, and the corresponding relationship between the signal coherence and target position was obtained. Consequently, an HBT interference localization model was established, and its validity was verified through simulations and experiments. Findings The effects of different array structures on the localization performance were obtained by simulation analysis, and the simulations confirmed that the HBT method exhibited a higher positioning accuracy than conventional beamforming. In addition, the experimental analysis demonstrated the excellent positioning performance of the HBT method, which verified the feasibility of the proposed method. Originality/value This study provides a new method for the passive localization of underwater targets, which may be widely used in the field of oceanic explorations.

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Section: Introductionmentioning

confidence: 95%

Underwater target passive acoustic localization method based on Hanbury Brown–Twiss interference

Liu

Zeng

Jian

et al. 2022

Self Cite

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“…After considering the advantages and disadvantages of traditional positioning methods, it is clear that a single traditional algorithm is no longer suitable for complex positioning requirements. Therefore, in 2019, Liu et al [26] introduced the HBT [27] interference principle from optics into the acoustic field and proposed a positioning method based on HBT interference in the acoustic field. This method analyzes the coherence of the signal to eliminate the influence of noise on passive target positioning, and it calculates the normalized correlation function to describe the coherence of the field, thus achieving accurate positioning of weak target sound sources.…”

Section: Introductionmentioning

confidence: 99%

Minimum Variance Distortionless Response—Hanbury Brown and Twiss Sound Source Localization

Liu

Zhao

2023

Applied Sciences

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Sound source target localization is an extremely useful technique that is currently utilized in many fields. The Hanbury Brown and Twiss (HBT) interference target localization method based on sound fields is not accurate enough for localization at low signal-to-noise ratios (below 0 dB). To address this problem, this paper introduces Minimum Variance Distortionless Response (MVDR) beamforming and proposes a new MVDR-HBT algorithm. Specifically, for narrowband signals, the inverse of the correlation matrix of the sound signal is calculated, and a guiding vector is constructed to compute the MVDR direction weights. These direction weights are then used to weight the correlation function of the HBT algorithm. Subsequently, the MVDR-HBT algorithm is extended from narrowband signals to broadband signals. As a result, the directivity of the HBT algorithm is optimized for wide- and narrowband signals, resulting in improved localization accuracy. Finally, the target localization accuracy of the MVDR-HBT algorithm is analyzed through simulation and localization experiments. The results show that the MVDR-HBT algorithm can accurately determine the direction of a sound source, with localization errors at different positions that are smaller than those produced by HBT. The localization performance of MVDR-HBT is considerably better than that of HBT, further verifying the simulation results. This study provides a new idea for target localization within an acoustic propagation medium (air).

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A sound source localization method based on improved second correlation time delay estimation

Liu¹,

Zeng²,

Jian³

et al. 2023

Meas. Sci. Technol.

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Sound source localization system based on microphone array has important applications in audio and video conference, security monitoring and intelligent cockpit. However, the sound source localization method based on time difference of arrival is susceptible to the 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 (SCOT) and the Roth processor (ROTH). The position of sound target is calculated from the time delay. Aiming at the moving target, extended Kalman filter (EKF) is introduced to track the moving trajectory of sound source. The static and moving sound source localization 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 (HQC) algorithm. The static sound source positioning errors of the proposed algorithm under -10dB SNR are respectively 3.97m and 5.86m smaller than those of the HQC algorithm and the SQC algorithm. The moving sound source localization trajectory based on the proposed algorithm is still closest to the real track under -10dB SNR. These indicates 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 sound source localization in low SNR environment.

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Passive positioning of sound target based on HBT interference

Cited by 3 publications

References 16 publications

Underwater target passive acoustic localization method based on Hanbury Brown–Twiss interference

Underwater target passive acoustic localization method based on Hanbury Brown–Twiss interference

Minimum Variance Distortionless Response—Hanbury Brown and Twiss Sound Source Localization

A sound source localization method based on improved second correlation time delay estimation

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