Autonomous Noise Mitigation for Underwater Acoustic Networks

海洋监测越来越受到环境、科学、商业和军事领域的关注 申请。监测海港、河口和内陆水体尤为重要，因为 这些地区的高水平活动。为了监测海洋，正在部署远程传感器节点用于 延长的时间段，通常用于检测特定的特征，如海洋哺乳动物、船只和 平台，甚至是通信信号。为了扩大监测范围，传感器节点网络 已部署共享信息。问题是，水声传感器会产生高度可变的噪声 条件，由于环境条件的变化。在每个节点处检测的可靠性受到阻碍 当噪声功率压倒感兴趣的信号时。 在这项工作中，目标是开发一种自主的水下环境监测和分析系统 并自主地重新配置其设置以适应变化的噪声条件。为了实现这一点，一个传感器 将被开发来监测水下噪声并表征其特性。不同的噪声抑制 将研究维持网络运行的技术。发展降噪技术 算法，将使用仿真工具对水下传播环境进行建模。此外， 有希望的算法将在硬件原型上实现，并在真实的水下进行测试 条件。

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.