基于人工蜂群改进算法的无线传感器网络定位算法

针对无线传感器网络无需测距的DV-Hop定位算法中，利用最小二乘法进行节点定位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算法中最小二乘法原理的基础上，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，改进的定位算法与最小二乘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。

Wireless Sensor Networks Node Localization Algorithm Based on Improved ABC Algorithm

An improved intelligent DV-Hop algorithm is proposed in order to solve the problem of the poor locating performance when using least squares algorithm for node localization in the DV-Hop algorithm based on range-free for Wireless Sensor Network (WSN). Firstly, the node localization problem was transformed into a global optimization problem based on analyzing the theory of least squares algorithm 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 least squares algorithm and DV-Hop algorithm based on original ABC algorithm, under the circumstances of different number of beacon ratio and different number of nodes, applying the improved DV-Hop algorithm can achieve obviously better locating performance precision and precision stability.