基于质点弹簧模型的无线传感器网络非测距定位算法

在无线传感器网络定位中,非测距定位因功耗低、成本低而备受关注,但其较低的定位精度限制了其应用范围。提出了一种精度较高的基于质点弹簧模型的非测距定位算法L-MSM( Localization based on Mass Spring Model)。该算法首先使用复杂度低、通信开销小的质心算法进行粗定位,然后利用改进的质点弹簧模型进行优化,使质心算法定位后成簇聚集的节点分散开来并趋近实际位置,从而实现精确定位。仿真结果表明,在通信半径较小时,L-MSM算法的定位精度相对于质心算法有显著的提高。

Range-Free Localization Algorithm Based on Mass Spring Model for Wireless Sensor Networks

The range-free localization algorithm has attracted much attention in wireless sensor networks due to its low power consumption and low cost,but its low positioning accuracy has limited its application. This paper proposes a high-accuracy range-free localization algorithm L-MSM( Localization based on Mass Spring Model) . The algorithm first uses the centroid algorithm which has low complexity and little communication overhead for coarse positioning, then adopts modified mass spring model for iterative refinement,which makes the nodes in clusters because of the drawback of centroid algorithm spread out and approach the actual position. The simulation results indicate that the L-MSM algorithm can significantly improve the positioning accuracy compared to the centroid algorithm when the communication radius is small.