摘要
无线传感器网络定位问题是一个基于不同距离或路径测量值的优化问题。由于传统的节点定位算法采用最小二乘法求解非线性方程组时很容易受到测距误差的影响,为了提高节点的定位精度,将粒子群优化算法引入到传感器网络定位中,提出了一种传感器网络的粒子群优化定位算法。该算法利用未知节点接收到的锚节点的距离信息,通过迭代方法搜索未知节点位置。仿真结果表明,该算法有效地抑制了测距误差累积对定位精度的影响,提高了节点的定位精度。
The localization of wireless sensor networks（WSN）is an optimization problem of measurement based on different distance or path.Due to the fact that the adoption of least square method in the traditional node localization for solving nonlinear equations are vulnerable to the impact of ranging error,and by introduction of the POS idea into the location of WSN,an algorithm named Particle Swarm Optimization（PSO） Localization Algorithm for Wireless Sensor Networks is proposed,thus to improve the accuracy of node localization.The algorithm uses the information received by the unknown nodes from the anchor nodes,and by means of the iterative method,searches the location of unknown nodes.The simulation results show that this algorithm could effectively suppress the impact of ranging-error accumulation on the positioning accuracy,and improve the positioning accuracy of the node.
出处
《通信技术》
2011年第1期102-103,108,共3页
Communications Technology
基金
中央高校基本科研业务费专项资金资助(No.DUT10ZD110)
