基于改进布谷鸟算法的WSN节点定位

有效的定位算法在无线传感器网络（WSN）的应用中起着重要的作用。针对DV-Hop算法在求解未知节点位置过程中定位精度低的问题进行了研究，提出了改进的无线传感器网络节点定位算法（SACSDV-Hop)。首先引入布谷鸟搜索（CS）算法，然后动态调整CS算法的发现概率 及影响步长大小的参数 以提高CS算法的收敛速度和局部搜索能力。SACSDV-Hop算法用改进的布谷鸟算法（SACS）代替DV-Hop算法在估算未知节点的位置坐标阶段所使用的最小二乘法，把节点定位问题转变为智能寻优问题，降低跳距估计误差对其的影响。仿真实验结果表明，所提算法比CSDV-Hop算法及传统的DV-Hop算法具有更高定位精度，并且不需要增加硬件开销。

WSN Node Localization Based On Improved Cuckoo Search Algorithm

Efficient localization algorithm plays an important role in the application of wireless sensor network (WSN). During the process of estimating unknown node position, the accuracy of DV-Hop algorithm is not that perfect. So this is about this paper. In terms of the improvement of accuracy, here puts forward a SACSDV-Hop algorithm. Firstly, introduced the cuckoo search (CS) algorithm; Secondly, dynamic adjustment of the discovery probability and impact of the step size parameter to improve the convergence speed and local search ability of CS algorithm. SACSDV-Hop algorithm use SACS algorithm instead of DV-Hop algorithm to estimate the coordinate position of the unknown node stage, which uses the least square method. The node localization problem is transformed into intelligent optimization. Simulation results show that the SACSDV-Hop algorithm is better than the CSDV-Hop algorithm and DV-Hop algorithm, which has a higher positioning accuracy and does not need to increase the hardware cost.