RESUMO
The received sound intensity of bottom-mounted line array varies as the submerged sound source moves in the direct arrival region, which resulting from interference between the direct and surface-reflected propagation paths, modulates with the target depth. In this work, the Fourier integral method from McCargar and Zurk [J. Acoust. Soc. Am. 133, EL320-EL325 (2013)] has been improved for depth estimation with a horizontal line array, and the matched sound intensity structure method from Zheng, Yang, Ma, and Du [J. Acoust. Soc. Am. 148, 347-358 (2020)] is introduced as a comparison. The two methods are verified in a deep ocean experiment.
RESUMO
Ocean acoustic tomography can be used based on measurements of two-way travel-time differences between the nodes deployed on the perimeter of the surveying area to invert/map the ocean current inside the area. Data at different times can be related using a Kalman filter, and given an ocean circulation model, one can in principle now cast and even forecast current distribution given an initial distribution and/or the travel-time difference data on the boundary. However, an ocean circulation model requires many inputs (many of them often not available) and is unpractical for estimation of the current field. A simplified form of the discretized Navier-Stokes equation is used to show that the future velocity state is just a weighted spatial average of the current state. These weights could be obtained from an ocean circulation model, but here in a data driven approach, auto-regressive methods are used to obtain the time and space dependent weights from the data. It is shown, based on simulated data, that the current field tracked using a Kalman filter (with an arbitrary initial condition) is more accurate than that estimated by the standard methods where data at different times are treated independently. Real data are also examined.
