There are 361 ports of interest to the US Coast Guard regarding homeland security issues. Speed and accuracy of inspections there for "foreign objects" is critical to maintaining the flow of commerce through these ports. A fusion of acoustic and optical imaging technologies has been implemented to rapidly locate anomalies acoustically and inspect them optically. Results of field tests are presented. Effective deployment of AUV-or ROV-mounted optical sensors to inspect ship hulls and port facilities will depend on accurate, real-time prediction of the sub-surface optical environment and upon accurate sensor models parameterized for the time and place of inspection. For bi-static laser-line scanner sensors such as the Real-time Ocean Bottom Optical Topographer (ROBOT), ambient light decreases the range to the inspection object (e.g. hull) for which laser-line contrast is adequate for ranging and imaging in 3-D. Reduced range implies narrower swaths and longer inspection times. A 2-D and 3-D hybrid marine optical model (HyMOM) of the environment beneath ships or adjacent to sea walls and pilings has been developed, applied and validated in eutrophic and mesotrophic settings, and a Monte Carlo sensor model of ROBOT has been developed. Both are discussed and combined to evaluate sensor performance in different environments. To provide the inherent optical properties needed to run such models, data from the Autonomous Marine Optical System (AMOS) were collected and transmitted back to the laboratory. Examples of AMOS results and model outputs are presented.
The ability to automatically generate internal models from sensed data will be of critical importance in the development of flexible, adaptive and useful unmanned underwater vehicles. The subsequent recognition of objects based on these a-priori models, which may be incomplete or partial, will also be an essential component in the success of UUV missions. This paper describes and presents experimental results obtained with our calibrated computer controlled frequency modulated (FM) subbottom penetrating sonar. We present a topographic model of the sea-floor surface and a sequence of sonar "images", obtained with the same FM sonar. This latter sequence shows a vertical section through the sea-bed itself. Despite the absence of surface features the variations in stratigraphy of this vertical section and the automation of the interpretation of these features opens the possibiliity of using these data to navigate when resurfacing is either not an option or desirable, for example, during under ice missions or from full ocean depth.
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