RESUMO
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.
RESUMO
According to the demands of current pipeline detection systems, the above-ground marker (AGM) system based on sound detection principle has been a major development trend in pipeline technology. A novel MEMS acoustic vector sensor for AGM systems which has advantages of high sensitivity, high signal-to-noise ratio (SNR), and good low frequency performance has been put forward. Firstly, it is presented that the frequency of the detected sound signal is concentrated in a lower frequency range, and the sound attenuation is relatively low in soil. Secondly, the MEMS acoustic vector sensor structure and basic principles are introduced. Finally, experimental tests are conducted and the results show that in the range of 0°~90°, when r = 5 m, the proposed MEMS acoustic vector sensor can effectively detect sound signals in soil. The measurement errors of all angles are less than 5°.
