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定位技术是无线传感器网络中关键的支撑技术之一。现有的无线传感器网络定位算法大多是针对静态场景的,不能直接应用于移动无线传感器网络。针对移动无线传感器网络的特点,在深入分析现有蒙特卡洛算法的基础上,提出一种改进机制,即采样区域自调整的蒙特卡洛节点定位(SA_MCL)算法。该算法通过对节点历史位置信息插值模拟获得节点的运动速度和方向,目的是为了自动调整采样区域,从而提高定位精度。仿真结果表明,采用SA_MCL算法,节点的定位精度有较大提高。
Positioning technology is one of the key support technologies in wireless sensor networks. Most existing wireless sensor network location algorithms are for static scenes and can not be directly applied to mobile wireless sensor networks. Aiming at the characteristics of mobile wireless sensor networks, an improved mechanism is proposed based on the deep analysis of the existing Monte Carlo algorithms, namely the Monte Carlo Node Location (SA_MCL) algorithm of self-adjusting sampling region. The algorithm obtains the velocity and direction of the node by interpolating the historical position information of the node, in order to adjust the sampling area automatically so as to improve the positioning accuracy. The simulation results show that using SA_MCL algorithm, the positioning accuracy of the node is greatly improved.