| The sensor array is composed of a group of sensors arranged in a specific way in space and discretely sampled the physical space.Array signal processing technology uses a sensor array to acquire data containing spatial-time/frequency domain information of the physical field and process the array signal data to extract the signal of interest or estimate the time-frequency domain parameters of the source.With the upgrading of hardware devices such as processors and sensors,as well as the advancement of signal mathematical models and algorithm theories,array signal processing technology has rapidly developed and been widely used in military and civilian fields such as radar,sonar,wireless communications,biomedicine,and voice intelligence.The parameter estimation related to the sound source position is one of the core technologies to realize spatial filtering,signal enhancement,and sound source tracing based on the microphone array.This dissertation focuses on the coupling of the microphone array and the optical sensor and studies the visual parameter estimation algorithm of the acoustic camera.However,the traditional acoustic photography methods mainly focus on a two-dimensional plane.Usually,they do not estimate the sound source location simultaneously.There are some limitations in practical use.In this dissertation,two three-dimensional acoustic photography methods are proposed,simultaneously producing sound source position estimation and visual image based on dual-mode information fusion.The two methods are verified by computer simulation and actual data experiment.The main work and contributions of this dissertation are as follows:(1)This dissertation expands the research target from the traditional two-dimensional plane to three-dimensional space,with broader applicability.An acoustic camera model in three-dimensional space is established for the dual-mode sensor array consisting of a monocular camera and multi-microphone channels.(2)Based on this acoustic camera model,two acoustic photographing methods are developed,which are combined with the steered response power(SRP)algorithm and the multiple signal classification(MUSIC)algorithm,respectively.The proposed method obtains the acoustic image by processing the array signal and fusion with the real image information captured by the camera to obtain the acoustic photographic image that can "see" the sound intensity distribution on the real image and the sound source position estimation.(3)Through computer simulation experiments,the performance of the above two acoustic photography methods in different scenarios with different array designs,different source signal frequencies,and single/multiple sound sources are discussed.The simulation results show that when using a small-size 16-channel microphone array,the two acoustic photography methods can achieve accurate acoustic imaging and sources localizing.The SRP-based acoustic photography method can be directly used for narrow/wideband signals analysis.The MUSICbased acoustic photography method has higher main lobe resolution and shorter running time.(4)An acoustic camera experiment platform is designed and built,composed of a sensor module,acoustic signal acquisition module,and computer processing module.With the platform,the indoor measured data experiment is designed and implemented.The two acoustic photography methods are verified.Experimental results show that in the laboratory environment with reverberation and multipath effect,both acoustic camera methods can realize the visual localization of single/multiple sound sources.In the visual image of the acoustic camera,the sound source area can be distinguished,and the error of source localization is controlled at the centimeter level. |
