【摘要】 针对无线传感器网络无需测距DV-Hop定位算法中,利用多边测量法计算未知节点坐标时存在较大误差的问题,提出了一种改进的DV-Hop智能定位算法。首先在详细分析DV-Hop算法中多边测量法的基础上,将定位问题转化成全局最优化问题;其次根据人工蜂群算法计算最优化问题的优势,结合定位具体问题,提出了一种自适应人工蜂群算法;最后将改进的人工蜂群算法运用到DV-Hop算法未知节点的坐标估计阶段实现定位。仿真实验表明,改进的定位算法与多边测量法及基于传统人工蜂群算法的DV-Hop算法相比,在不同锚节点比例和不同节点数的情况下,定位精度和精度稳定性都有明显提高。更多还原

【Abstract】 An improved intelligent DV-Hop algorithm is proposed in order to solve the problem of the poor locating performance when using multilateral measurement method for computing the coordinates of unknown nodes in the range-free DV-Hop algorithm for Wireless Sensor Network(WSN).Firstly,the node localization problem was transformed into a global optimization problem based on analyzing the theory of multilateral measurement method with DV-Hop algorithm.Then according to the superiority on solving the optimization problem,Adaptive Artificial Bee Colony(AABC)algorithm was proposed by considering the specific localization problem.Finally,the improved ABC algorithm was used at the stage of location in DV-Hop algorithm so as to accomplish the localization.The results from simulation show that compared with multilateral measurement method and DV-Hop algorithm based on original ABC algorithm,and under the circumstances of different number of beacon ratio and different number of nodes,applying the improved DV-Hop algorithm,better locating performance precision and precision stability can be achieved obviously.更多还原