Wireless sensor network (WSN) is a research hot spot of scholars in recent years, in which node localization technology is one of the key technologies in the field of wireless sensor network. At present, there are more researches on static node localization, but relatively few on mobile node localization. The Monte Carlo mobile node localization algorithm utilizes the mobility of nodes to overcome the impact of node velocity on positioning accuracy. However, there are still several problems: first, the demand for anchor nodes is large, which makes the positioning cost too high; second, the sampling efficiency is low, and it is easy to fall into the infinite loop of sampling and filtering; and third, the positioning accuracy and positioning coverage are not high. In order to solve the above three problems, this paper proposes a Monte Carlo node location algorithm based on improved QUasi-Affine TRansformation Evolutionary (QUATRE) optimization. The algorithm firstly selects the high-quality common nodes in the range of one hop of unknown nodes as temporary anchor nodes, and takes the temporary anchor nodes and anchor nodes as the reference nodes for positioning, so as to construct a more accurate sampling area; then, the improved QUATRE optimization algorithm is used to obtain the estimated location of unknown nodes in the sampling area. Simulation experiments show that the Monte Carlo node positioning algorithm based on the improved QUATRE optimization has higher positioning accuracy and positioning coverage, especially when the number of anchor nodes is relatively small.

中文翻译：

---

基于改进的QUARTE优化的蒙特卡洛节点定位

无线传感器网络（WSN）是近年来学者们的研究热点，其中节点定位技术是无线传感器网络领域的关键技术之一。目前，关于静态节点定位的研究较多，而关于移动节点定位的研究则相对较少。蒙特卡洛移动节点定位算法利用节点的移动性来克服节点速度对定位精度的影响。但是，仍然存在一些问题：第一，对锚节点的需求很大，这使得定位成本过高。其次，采样效率低，容易陷入采样滤波的无限循环。第三，定位精度和定位覆盖率不高。为了解决以上三个问题，提出了一种基于改进的拟仿射变换演化（QUATRE）优化的蒙特卡洛节点定位算法。该算法首先选择未知节点一跳范围内的高质量公共节点作为临时锚节点，并以临时锚节点和锚节点作为参考节点进行定位，以构造更准确的采样区域。然后，使用改进的QUATRE优化算法获得采样区域中未知节点的估计位置。仿真实验表明，基于改进的QUATRE优化的蒙特卡洛节点定位算法具有较高的定位精度和定位覆盖率，特别是在锚点数量较少的情况下。