No abstract

No abstract

This paper uses LabVIEW as a software platform combined with the PXIe-4497 sound and vibration acquisition card to design a sound source localization system. Using the sounding device as sound source, the data is received by the microphone array. After the processing of the sound source localization system, the sound image is added with the video to achieve the locating of the sound source. The system consists of three modules: sound pressure data acquisition module, video acquisition module and data processing module. The sound pressure data acquisition module is programmed by using the DAQmx API function, the video acquisition module is based on the IMAQdx function, and the data processing module uses the phase-shift sum beamforming algorithm. The design of this system can provide practical references for future applications such as noise detections.

In order to accurate the time delay estimation and orientation localization, in this paper, we are aimed at finding a high resolution algorithm to improve the deviation in the far-field source localization. Compared with the traditional method based on the cross-correlation algorithm which often corresponds with the interpolation algorithm, the method of Sliding DFT is a novel time delay estimation approach based on the Sliding DFT analysis window, which is more comprehensive and accurate. The signal is specified into a singularity frequency signal and this algorithm of Sliding DFT uses the sample number at the maximum magnitude of the spectrum as the first estimation and utilize its corresponding phase offset for compensation with the aim to estimate the time delay of the signal, which is a rather new method applied to the acoustic localization field in this paper. The simulation includes a simple acoustic source with singularity frequency using the traditional cross-correlation algorithm and the improved Sliding DFT algorithm, accompanied with the matrix transformation method to compute the position of the assumed signal. After calculating and comparing the statistic of both algorithms, the improvement of the accuracy can be easily seen.

It has been shown that driver fatalities in frontal collisions were reduced by 28% in airbag-equipped cars based on comparisons with similar cars equipped with manual lap/shoulder belts only (Zador and Ciccone, 1991). A similar finding was reported by the Department of Transportation that driver fatality rates in airbag equipped cars were reduced by 31% in purely frontal crashes (12:00 point of impact on the vehicle), and 19% in all frontal crashes (10:00 to 2:00). About 10% of drivers of vehicles with airbags involved in accidents received moderate to severe injuries. Most, if not all, of these people would have been more seriously injured or killed without the airbag. In a recent report to Congress, NHTSA estimated that airbags have saved 1,198 lives from 1987 through 1995, including 475 lives saved in 1995 alone.

The system is based on ARM as the core of the embedded platform, using STM32F103 chip, comprehensively designing adjustable gain microphone, AD7606 eight channel synchronous acquisition chip,W5300 Ethernet chip, Qt upper computer and so on to complete a multi-channel sound source localization system integrating acquisition, storage, upload, analysis and display of sound signals. The system use STM32F103 chip to control the core and source localization algorithm based on time delay estimation of arrival time difference with small computation, accurate localization and good real-time performance. Through the design and fabrication of microphone array, the acquisition and pre-processing function of sound signal is accomplished by using eight-channel synchronous acquisition module. The data is transmitted to the upper computer by using Ethernet module, and the upper computer performs algorithm processing and display. The system is simple in structure, small in size and easy to use. The test results show that the system can not only acquire complete sound data and high waveform reduction, but also display real-time sound source waveform in the upper computer. The positioning result is ideal, high accuracy, good real-time, and has certain practical value.