Ambient Noise Imaging through joint source localization

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. Even in anisotropic noise, some sources `illuminate´ the target while others obscure it. In this paper we describe a different approach. We use a snap detection algorithm to estimate the locations of the noise sources on the sea-bottom and then use the sound from these sources to passively range and form images of the objects. By using only the noise from sources that provide us good illumination and rejecting undesirable sources, we improve the image quality. The feasibility of this approach has been experimentally demonstrated with the data collected during a recent deployment of ROMANIS, an ANI camera developed in Singapore.