Luo Junhai, Fan Liying
School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610073, China.
Sensors (Basel). 2017 Mar 30;17(4):726. doi: 10.3390/s17040726.
Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.
水下传感器网络（UWSN）可实现广泛的应用，如资源监测、灾害预防和导航辅助。UWSN中传感器节点的定位是一个特别相关的主题。由于水下传播问题，全球定位系统（GPS）信息不适用于UWSN。因此，一些为UWSN提出的基于传感器节点之间精确时间同步的定位算法不可行。在本文中，我们提出了一种称为两阶段无时间同步定位算法（TP - TSFLA）的定位算法。TP - TSFLA包含两个阶段，即基于距离的估计阶段和无距离评估阶段。在第一阶段，我们提出一种基于粒子群优化（PSO）算法的无时间同步定位方案，以获取未知传感器节点的坐标。在第二阶段，我们提出一种基于圆的无距离定位算法（CRFLA），用于定位那些无法通过第一阶段获得位置信息的未定位传感器节点。在第二阶段，在第一阶段已定位的传感器节点充当新的锚节点以帮助实现定位。因此，在该算法中，我们使用少量移动信标来帮助获取位置信息，而无需任何其他锚节点。此外，为了提高无距离方法的精度，通过设计坐标调整方案对CRFLA进行了扩展更新。仿真结果表明，TP - TSFLA在无时间同步的情况下可以实现相对较高的定位率。
