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Title: Ambient Noise Imaging in Warm Shallow Water
Keywords: Ambient noise imaging, acoustic imaging, underwater imaging, snapping shrimp noise, shallow water imaging, source localization
Issue Date: 18-Aug-2011
Citation: SUBASH KUSELAN (2011-08-18). Ambient Noise Imaging in Warm Shallow Water. ScholarBank@NUS Repository.
Abstract: Underwater Ambient Noise Imaging (ANI) is a concept that has been proposed for creating images of objects in the ocean from the insonification provided by the incident ambient noise field, quite different from active and passive systems. With an active system, an object is illuminated by a pulse of sound and its presence inferred from the echo it produces, whereas the passive approach involves simply listening for the sound that the object itself emits. ANI uses sound in the ocean, which is neither passive nor active. It relies on the naturally occurring, incoherent ambient noise field in the ocean which can be thought of as 'acoustic daylight? as the sole source of acoustic illumination. An underwater acoustic camera receives the reflected sound waves from the object and produces digital images. A real-time underwater ambient noise imaging camera and its processing platform present a complex design challenge with the technology available today. The design challenge is to simultaneously sample 508 acoustic transducers at 196 kSa/s, transmit this massive data (1.6 Gbps) to the surface and process it in real-time to form images. The recent advances in multichannel data acquisition systems, embedded single board computers along with Gigabit Ethernet technology and general purpose GPUs made it possible to realize an underwater imaging system. This thesis describes the complete design and development of underwater imaging system. Underwater Ambient Noise Imaging (ANI) systems rely on the acoustic illumination produced by natural noise sources to image an object of interest. Snapping shrimp are a dominant natural source of illumination in tropical waters and their snaps occur randomly. Hence incoherent energy detection methods, which require no knowledge of the source locations, are usually employed to form images of the objects. This approach, although simple, only produces images when the anisotropy in ambient noise is conducive. This thesis describes a different approach. Snap detection & localization algorithms to estimate the locations of the noise sources on the sea-bottom and then uses the sound from these sources to passively range and form image of the objects. 3D visualization of underwater objects using snapping shrimp noise also described. This dissertation is unique; the contents are a blend of engineering and research. End-to-end ambient noise imaging camera design and a unique image processing technique using snapping shrimp noise are presented.
Appears in Collections:Master's Theses (Open)

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