Since localization now has been an essential step in underwater work. The traditional localization algorithm, like time different of arrival (TDoA) has been proposed for its efficiency in terrestrial while it cannot perform perfect because of the unstable propagation in the harsh underwater environment. And autonomous underwater vehicle (AUV) has been used in many circumstances to meet the needs of underwater works. Hence, an enhanced AUV-aided TDoA localization algorithm (EATLA) for underwater acoustic sensor networks (UASNs) is proposed. The AUV dives into the predefined depth from the water surface after acquiring its position coordinates through the GPS, and periodically transmits data packets around the unknown node. After the unknown node receives the data packets and calculates its position, the conditions for the unique result and evaluate the reliability are quantified. Then, to save the energy consumption, a time-delay system is proposed. Compared with traditional localization algorithms, this paper evaluates the performance of EATLA with localization accuracy, coverage and time used in simulations. The obtained results indicate this algorithm achieves relatively higher accuracy with relatively smaller calculations and overcomes some traditional localization drawbacks.

自从本地化以来，这已成为水下工作的重要步骤。传统的定位算法，如到达时间差（TDoA），由于其在陆地上的效率而被提出，但由于在恶劣的水下环境中不稳定的传播而无法完美执行。自主水下航行器（AUV）已在许多情况下用于满足水下工程的需求。因此，增强的AUV辅助TDOA定位算法（EATLA）的水声传感器网络（UASNs）被提议。AUV通过GPS获取其位置坐标后，便从水面潜入预定深度，并在未知节点周围定期发送数据包。在未知节点接收到数据包并计算其位置之后，将量化唯一结果的条件并评估可靠性。然后，为了节省能耗，提出了一种时延系统。与传统的定位算法相比，本文通过仿真中的定位精度，覆盖范围和时间来评估EATLA的性能。获得的结果表明该算法以相对较小的计算实现了较高的精度，并克服了一些传统的定位缺陷。