Target localisation is one of the key technologies and a performance metric in underwater acoustic sensor networks. A number of range-free and range-based localisation algorithms are proposed. Among them a range-based localisation algorithm: weighted centroid localisation (WCL) is widely used due to the relatively simple implementation and better localisation. The accuracy of WCL, however, is reduced when the sensor nodes are farther from the centre or inappropriate nodes are selected to perform the localisation. This study proposes a novel and an efficient node optimisation algorithm based on received signal strength and weighted centroid. The proposed algorithm consists of three stages: (a) to estimate a rough region of the target node using bearing line and azimuth; (b) to calculate the optimal localisation region by the optimal localisation region function, and then (c) compare the overlap area of the rough region of the target node and the optimal localisation region to select the optimal localisation node. Simulation experiments show that the proposed optimal localisation region function can accurately represent the optimal localisation region of the geometrical figure, composed of different nodes. The study compares the performance of our proposed algorithm with the typical WCL algorithm, and clearly shows significant improvement in the localisation accuracy.

中文翻译：

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水下接收信号强度定位中节点选择和质心算法的优化方法

目标定位是水下声传感器网络中的关键技术之一和性能指标。提出了许多无距离和基于距离的定位算法。其中一种基于范围的定位算法：加权质心定位（WCL）由于相对简单的实现和更好的定位而被广泛使用。但是，当传感器节点距离中心较远或选择了不合适的节点来执行定位时，WCL的精度会降低。本研究提出了一种基于接收信号强度和加权质心的新颖高效的节点优化算法。所提出的算法包括三个阶段：（a）使用方位线和方位角估计目标节点的粗略区域；（b）通过最佳定位区域函数计算最佳定位区域，然后（c）比较目标节点的粗糙区域与最佳定位区域的重叠区域，以选择最佳定位节点。仿真实验表明，所提出的最优定位区域函数可以准确地表示由不同节点组成的几何图形的最优定位区域。该研究将我们提出的算法与典型的WCL算法的性能进行了比较，并清楚地表明了定位精度的显着提高。仿真实验表明，提出的最优定位区域函数可以准确地表示由不同节点组成的几何图形的最优定位区域。该研究将我们提出的算法与典型的WCL算法的性能进行了比较，并清楚地表明了定位精度的显着提高。仿真实验表明，提出的最优定位区域函数可以准确地表示由不同节点组成的几何图形的最优定位区域。该研究将我们提出的算法与典型的WCL算法的性能进行了比较，并清楚地表明了定位精度的显着提高。