【摘要】 近年来优化算法在无线传感器网络定位算法中得到了广泛应用。在对差分进化算法研究的基础上提出一种二阶段定位算法,第一阶段在Euclidean定位算法的基础上,加入了距离路由思想,通过与未知节点距离两跳之内的两个锚节点和距离两跳之外的任一锚节点利用Euclidean算法来计算估计位置。第二阶段利用差分进化算法进行迭代寻优,提出的新算法称之为DE-Euclidean定位算法。仿真结果表明,DE-Euclidean算法明显提高了定位精度。更多还原

【Abstract】 In recent years the optimisation algorithm has been widely used in wireless sensor network localisation algorithms.Based on an in-depth study on differential evolution algorithm,the authors propose a two-stage localisation algorithm.In the first phase,based on the Euclidean localisation algorithm,they added the idea of distance routing,which is to work with two anchor nodes within two-hop of the unknown node and with any one anchor node which locates two-hop away from the unknown node to calculate the estimated location.In the second phase,they used differential evolution algorithm to perform the iterative optimisation.The proposed algorithm is called the DE-Euclidean localisation algorithm. Simulation results show that,the DE-Euclidean algorithm significantly improves the precision of localisation.更多还原