Beamforming and its applications in steered-response power (SRP) technology, such as steered-response power delay and sum (SRP-DAS) and steered-response power phase transform (SRP-PHAT), are widely used in sound source localization. However, their resolution and accuracy still need improvement. A novel beamforming method combining SRP and multi-channel cross-correlation coefficient (MCCC), SRP-MCCC, is proposed in this paper to improve the accuracy of direction of arrival (DOA). Directional weight (DW) is obtained by calculating the MCCC. Based on DW, suppressed the non-incoming wave direction and gained the incoming wave direction to improve the beamforming capabilities. Then, sound source localizations based on the dual linear array under different conditions were simulated. Compared with SRP-PHAT, SRP-MCCC has the advantages of high positioning accuracy, strong spatial directivity and robustness under the different signal–noise ratios (SNRs). When the SNR is −10 dB, the average positioning error of the single-frequency sound source at different coordinates decreases by 5.69%, and that of the mixed frequency sound sources at the same coordinate decreases by 5.77%. Finally, the experimental verification was carried out. The results show that the average error of SRP-MCCC has been reduced by 8.14% and the positioning accuracy has been significantly improved, which is consistent with the simulation results. This research provides a new idea for further engineering applications of sound source localization based on beamforming.
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.
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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