Autonomous Noise Mitigation for Underwater Acoustic Networks

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Ocean monitoring is receiving increased interest for environmental, scientific, commercial and military applications. It is particularly important to monitor seaports, estuaries and in-land bodies of water because of the high level of activity in these areas. To monitor the ocean, remote sensor nodes are being deployed for extended periods of time and are often meant to detect specific signatures, such as marine mammals, ships and platforms, or even communication signals. To extend the monitoring range, a network of sensor nodes that share information is deployed. The problem is that underwater acoustic sensors incur highly variable noise conditions, due to changes in the environmental conditions. The reliability of detection at each node is thwarted when the noise power overwhelms the signal of interest. In this work, the objective is to develop an autonomous underwater system that monitors and analyzes ambient noise and that autonomously re-configures its settings to the varying noise conditions. To achieve this, a sensor will be developed to monitor the underwater noise and to characterize its properties. Different noise mitigation techniques will be studied to maintain the operation of the network. To develop the noise mitigation algorithms, the underwater propagation environment will be modeled using simulation tools. Further, promising algorithms will be implemented on hardware prototypes, and tested in realistic underwater conditions.