Abstract
The uncertainty behavior of an enhanced three-dimensional (3D) localization scheme for pulsed sources based on relative travel times at a large-aperture three-hydrophone array is studied. The localization scheme is an extension of a two-hydrophone localization approach based on time differences between direct and surface-reflected arrivals, an approach with significant advantages, but also drawbacks, such as left-right ambiguity, high range/depth uncertainties for broadside sources, and high bearing uncertainties for endfire sources. These drawbacks can be removed by adding a third hydrophone. The 3D localization problem is separated into two, a range/depth estimation problem, for which only the hydrophone depths are needed, and a bearing estimation problem, if the hydrophone geometry in the horizontal is known as well. The refraction of acoustic paths is taken into account using ray theory. The condition for existence of surface-reflected arrivals can be relaxed by considering arrivals with an upper turning point, allowing for localization at longer ranges. A Bayesian framework is adopted, allowing for the estimation of localization uncertainties. Uncertainty estimates are obtained through analytic predictions and simulations and they are compared against two-hydrophone localization uncertainties as well as against two-dimensional localization that is based on direct arrivals.
Highlights
Underwater pulsed-source localization is of importance for a broad range of marine operations, from the monitoring of underwater vehicles [1], search and rescue operations [2], to wildlife monitoring [3,4], and spatial audio applications [5]
Direct arrivals are followed by arrivals that are associated with acoustic paths reflected off the sea surface and/or the sea bottom
Various 3D localization approaches exploiting direct and surface-reflected arrivals at two hydrophones have been proposed for homogeneous environments [10,11,12], as well as for refractive environments [13,14,15,16]
Summary
Underwater pulsed-source localization is of importance for a broad range of marine operations, from the monitoring of underwater vehicles [1], search and rescue operations [2], to wildlife monitoring [3,4], and spatial audio applications [5]. In [16], the two-hydrophone localization problem was embedded in a Bayesian framework, enabling the estimation of localization uncertainties that are caused by errors in the TDOAs and hydrophone locations, as well as by uncertainties in the sound-speed profile characterizing a refractive environment. This approach was applied to a series of controlled localization
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