基于跳距修正与差分进化优化的改进DV-Hop定位算法

为了提高传统DV-Hop(distance vector-hop)算法的定位精度，提出一种基于跳距修正和差分进化优化的改进DV-Hop(differential evolution distance vector-hop,DEDV-Hop)算法。由DV-Hop的算法原理可知，锚节点间的距离测量误差是算法定位误差的主要来源，由此根据锚节点间的不同跳数引入权重因子，从而减小平均每跳距离误差，并且利用差分进化算法对最小二乘法计算出的节点坐标进行二次优化，最终提高系统的整体定位精度。为了验证算法的有效性，在相同实验条件下，通过设置不同的定位参数将提出的算法与同类的经典算法进行实验对比。实验结果表明，DEDV-Hop算法可以有效减少节点平均定位误差，其定位精度明显优于其他几种算法。

Improved DV-Hop location algorithm based on hop correction and differential evolution algorithm

To improve the location accuracy of the classical distance vector-hop (DV-hop) algorithm, an improved differential evolution distance vector-hop (DEDV-Hop) algorithm based on hop distance correction and differential evolution optimization is proposed. By analyzing the algorithm principle of DV-hop, the distance measurement error between anchor nodes is the main source of the algorithm location error. Therefore, in accordance with the different hops between anchor nodes, the weight factor is introduced to reduce the average distance error per hop. In addition, differential evolution algorithm is used to optimize the coordinates of the nodes calculated by the least square method to improve the global location accuracy of the system. To verify the effectiveness of the algorithm, different localization parameters were set under the same experimental conditions to compare the proposed algorithm with the same classical algorithm. The experimental results show that the DEDV-Hop algorithm can effectively reduce the average location error of nodes, and its location accuracy is obviously superior to other algorithms.