Underwater wireless sensor networks (UWSNs) have played an increasingly important role in the fields of ocean exploration, underwater environment monitoring, underwater navigation target tracking, terrain-assisted navigation, and so on. However, UWSNs are a dynamic network, which are unlike terrestrial wireless sensor networks, and the complexity of underwater environment poses many challenges for the positioning of sensor nodes. Aiming at the difficulty of location update, this paper proposes a UWSN positioning technology based on iterative optimization and data position correction (IO-DPC). Firstly, particle swarm optimization technology is used to perform the rough positioning stage of sensor nodes, and iterative optimization is performed for many times. Then, data position correction work is carried out, and a scheme is designed for correcting underwater sensor data position when base station receives the data packet. An underwater ocean current model is established, and IO-DPC technology is simulated in various underwater simulation environments. Experimental results show that IO-DPC technology has higher positioning accuracy than other traditional technologies.

水下无线传感器网络（UWSN）在海洋勘探，水下环境监视，水下导航目标跟踪，地形辅助导航等领域中发挥着越来越重要的作用。但是，UWSN是动态网络，与地面无线传感器网络不同，水下环境的复杂性对传感器节点的定位提出了许多挑战。针对位置更新的难点，提出一种基于迭代优化和数据位置校正（IO-DPC）的UWSN定位技术。首先，采用粒子群优化技术对传感器节点进行粗略定位，并进行了多次迭代优化。然后，进行数据位置校正工作，设计了一种方案，用于在基站接收到数据包时校正水下传感器数据位置。建立了水下洋流模型，并在各种水下模拟环境中对IO-DPC技术进行了模拟。实验结果表明，IO-DPC技术具有比其他传统技术更高的定位精度。