Geoacoustic characterization of a range-dependent ocean environment using towed array data

This paper examines geoacoustic inversion over a range-dependent multiple-layer seabed using a towed acoustic source and towed horizontal array. The approach is based on combining the results of a series of short-range, range-independent inversions to form a range-dependent representation of the environment. The data were collected in the Strait of Sicily during the MAPEX 2000 experiment. Issues such as the resolvability of multilayer structure and the sensitivity of various geoacoustic parameters are investigated by inversion of simulated data and by comparison of the MAPEX 2000 inversion results to a high-resolution seismic profile and to sediment core measurements. It appears that two, and in some cases possibly three, sediment layers can be resolved.     

An investigation of algorithm-induced variability in geoacoustic inversion

This paper investigates the inherent variability in the results of matched-field geoacoustic inversion algorithms. This algorithm-induced variability must be considered when interpreting inversion results in terms of environmental changes as a function of time or space. Fast simulated annealing (FSA), genetic algorithms (GA), and a hybrid algorithm (adaptive simplex simulated annealing; ASSA) are compared by performing multiple inversions of benchmark synthetic data (noise free and noisy) and acoustic data measured over both low- and high-speed sea-bed sediments in the MAPEX 2000 experiment. ASSA produced the lowest variability in inversion results for all cases, followed by GA and FSA. For the high-speed MAPEX 2000 case, the variability is essentially negligible, while for the low-speed case the variability is significant as compared with environmental variations reported in the literature.     

High-precision array element localization for vertical line arraysin the Arctic Ocean

Array element localization (AEL) surveys are often required to accurately localize acoustic instruments (transponders or sensors) in the ocean. These are typically based on transmitting or recording acoustic signals from or at a set of well-known positions. A significant limiting factor in many AEL surveys is the uncertainty inherent in these “known” positions. In this paper, an inversion algorithm is developed which properly treats both transponder and sensor positions as unknowns, subject to available a priori information in the form of position estimates and uncertainties. The algorithm essentially consists of an iterative linearized inversion of the raytracing equations employing the method of regularization. The approach is applied to independently localize transponders and vertical line array (VLA) sensors that form part of a three-dimensional sensor array in the Arctic Ocean. Confidence limits estimated via Monte Carlo simulation indicate that transponders and sensors are localized to less than 1 m in three dimensions. The VLA sensor motion, monitored over a seven-week period, appears to be predominately driven by tidal currents and is consistent with historical current measurements for the region