Fluid field estimation and source localization by dynamic positioning of autonomous underwater sensor nodes

在本研究提案范围内，应通过移动的传感器识别具有不确定源、边界和初始条件的流体场。因此，流场的模拟将与来自移动的传感器节点的测量同化并被预测。对不确定流场的预测将用于规划移动的传感器的轨迹，这些传感器返回最佳测量值以提高流场估计的准确性。这样的系统可以用于定位主要未知流体域中的热和污染源，而且还可以验证流体动力学计算。通常，河流、港口、河口和海洋中的水流和污染物由多个固定传感器测量，并由载人船只的测量结果提供支持。在集中控制的移动的自主传感器网络中，通过传感器节点的优化定位可以获得更高的动态分辨率。实时的全球数据同化是必不可少的，以发现在哪些领域需要更多的测量，并不断产生路径和测量位置的移动的sensors.A边界条件估计，源识别和当前测量的自动化过程，确保了高度的灵活性和快速部署的自组织水下航行器。完全未知的流场可以分析，只要所有的位置在感兴趣的领域，由于当前的条件下，船舶可以达到。在力学和海洋工程研究所进行了几个初步研究的理论，源识别和定位，成功地实施了模拟。此外，控制系统已被开发，计算每个移动的传感器的最佳轨迹，并确保网络的有效协调。此外，我们将与美国和巴西的合作伙伴机构在该项目的理论和实践部分合作。特别需要进一步的研究在源定位和边界条件估计，但也是整个系统的动态。由于完整的系统包含许多不确定性和部分，这是无法建模，一个实际的实施是本研究项目的一部分，这一概念的验证将通过一个实验装置，其中移动的水下航行器配备温度传感器应识别和定位在水箱中的泵驱动流场的热源，并自动检测边界条件。估计的流场和它的不确定性被用来产生最佳的轨迹的车辆。理论和模拟应通过在受控环境中进行的实验进行验证，并且在进行海上试验之前必须分析技术问题和可能性

In the scope of this research proposal fluid fields with uncertain sources, boundary and initial conditions shall be identified by mobile sensors. A simulation of the fluid field will therefore be assimilated with measurements from the mobile sensor nodes and predicted. The prediction of the uncertain fluid field will then be used to plan trajectories for the mobile sensors which return optimal measurements to improve the accuracy of the fluid field estimation.A system like that can be used to localize heat and pollution sources in primarily unknown fluid domains, but also to verify fluid dynamic calculations. Usually, currents and pollutants in rivers, harbors, estuaries, and oceans are measured by multiple stationary sensors, supported by measurements from manned vessels. With a centrally controlled mobile autonomous sensor network we can achieve a much higher dynamic resolution through optimal positioning of the sensor nodes. Global data assimilation in real-time is indispensable to discover in which areas more measurements are needed and to continuously generate paths and measurement locations for the mobile sensors.An automated process of boundary condition estimation, source identification, and current measurement assures a high flexibility and a fast deployment of the self-organizing underwater vehicles. Completely unknown fluid fields can be analyzed as long as all positions in the domain of interest can be reached by the vessels due to current conditions.At the Institute of Mechanics and Ocean Engineering several preliminary studies have been conducted about the theory of source identification and localization which were implemented successfully in simulations. Additionally, a control system has been developed which calculates the optimal trajectories for each mobile sensor and ensures an efficient coordination of the network. Furthermore, we will collaborate with partner institutions in the USA and Brazil in theoretical and practical parts of this project. Further research is especially needed in source localization and boundary condition estimation, but also the dynamic of the complete system. Because the complete system contains many uncertainties and parts, which cannot be modeled, a practical implementation is part of this research project.The verification of this concept will be done by an experimental setup, in which mobile underwater vehicles equipped with temperature sensors shall identify and localize a heat source in a pump driven flow field in a water tank and automatically detect boundary conditions. The estimated flow fields and its uncertainties are used to generate optimal trajectories for the vehicles. The theory and simulations shall be verified through this experiment in a controlled environment and technical issues and possibilities have to be analyzed before sea trials are conducted