Concepedia

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underwater sensing

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Shallow-Water Model-Based Inversion

1991 - 1997

In this period, the dominant paradigm centers on model-based acoustic field representations, notably matched-field inversions and normal-mode localization, used to characterize the shallow-water environment and localize targets while jointly estimating bottom properties and sensor geometry from measured data. A broad spectrum of hardware-focused investigations addresses transducer performance, self-noise, and measurement platforms—from flow-induced hydrophone noise to drifting sensors and surface acoustic wave-based sensing—complementing sea-bottom and acoustic field studies. Bioacoustic work examines cetacean perception, deterrent devices to reduce bycatch, and marine mammal hearing and ice tracking, highlighting ecological and management implications, while active sonar and robotics research emphasizes obstacle localization and autonomous sensing and navigation.

Model-based acoustic field representations (matched-field inversions, normal-mode localization) enable environment characterization and target localization in shallow-water oceans, with simultaneous estimation of bottom properties and sensor geometry from measured data [4], [10], [11], [8].

A range of hardware-oriented studies address sensing transducers, self-noise, and measurement platforms for underwater acoustics, from flow-induced hydrophone noise, to drifting infrasonic/pressure sensors, to SAW-based humidity sensing, to transducer technology [6], [9], [12], [15].

Bioacoustic studies examine cetacean perception and bycatch dynamics, including net reflectivity, deterrent devices to reduce cetacean mortality, and marine mammal hearing/ice tracking, highlighting ecological and management implications [2], [3], [5], [13], [18].

Active sonar and robotics-oriented research focus on obstacle localization and integrated vehicle-manipulator control, including bat-like wide-beam sonar systems and adaptive tracking, illustrating advances in autonomous sensing and navigation [17], [19], [7].

Underwater Vision and Sensing

1998 - 2024