无线传感器网络局部协同定位算法

针对无线传感器网络中距离定位算法精度和覆盖率低的问题，提出了局部协同定位算法(LCLA)。该算法通过对节点路径损耗指数的局部计算，将通信中受到环境或者障碍物影响的锚节点判定为无效锚节点；同时引入协同定位思想，将满足误差要求的已定位节点升级为锚节点，并参与其他未知节点的定位，以提高定位的覆盖率。节点定位时，若收到多个锚节点信号，优先选取初始的有效锚节点对其进行定位；当有效锚节点个数不足以定位时，再选取升级后的锚节点，以减少累积误差，提高定位精度。仿真结果表明，局部协同定位算法在定位覆盖率和精度方面优于改进的接收信号强度指示(RSSI)定位算法、多维尺度分析(MDS-MAP)算法和协作定位算法。

Local cooperative localization algorithm for wireless sensor networks

In order to overcome the low accuracy and coverage rate of localization algorithm based on distance in wireless sensor networks, a Local Cooperative Localization Algorithm (LCLA) was proposed. The algorithm judged anchor nodes by calculating their local path loss indexes and determined those influenced by communication environment or obstacles to be invalid. At the same time, the idea of cooperative localization was introduced and the nodes that met certain requirements of localization error would be upgraded to anchor nodes to take part in localization of other nodes and improved coverage rate of localization. When nodes received multiple signals from anchor nodes, they first selected the initial valid anchor nodes to calculate their positions in priority. If the number of the initial valid anchor nodes was not sufficient, nodes would then select from the upgraded ones to reduce the cumulative error and improve localization accuracy. The simulation results indicate that LCLA performs better in localization accuracy and coverage rate compared with the algorithm of improved Received Signal Strength Indicator (RSSI) localization, MDS-MAP (MultiDimensional Scaling MAP) and cooperating localization.