Adaptive rapid environmental assessment simulation framework

Abstract

The coastal environment is characterized by variability on small spatial scales and short temporal scales. These environmental uncertainties translate—in a highly non-linear fashion—into uncertain acoustic propagation properties, often severely affecting the sonar performance prediction capabilities. Conventional oceanographic measurement systems cannot capture these environmental uncertainties due to their limited predictability and the lack of mobility of the traditional measurement platforms. Taking advantage of the mobility of modern autonomous underwater vehicle technology, the Adaptive Rapid Environmental Assessment (AREA) concept has been developed to optimally use the available resources to capture the acoustic uncertainty by adaptive and rapid in situ measurement of the environmental properties most significant to the actual sonar system. The ocean area of interest is usually fairly large, and the in situ measurement resources are limited, and the adaptive sampling strategy in AREA can therefore make a significant difference in capturing and mitigating the sonar performance uncertainties. To determine an optimal or sub-optimal sampling strategy and test the optimization effect before doing costly on-site experiments, an Adaptive Rapid Environmental Assessment Simulation Framework (AREASF) has been developed, based on state-of-the-art forecasting frameworks and acoustic propagation models. The simulation framework has been applied to investigate the performance of AREA under different environmental conditions, and based on these results, the feasibility of performing real-time adaptive environmental assesment using AREA under realistic ocean conditions will be discussed. [Work supported by ONR.]