融合测距修正和哈里斯鹰优化的DV-Hop定位算法

针对传统DV-Hop定位算法在无线传感器网络节点定位时精度偏低的问题，本文提出了一种基于测距修正和哈里斯鹰优化算法的DV Hop改进算法。该算法采用多通信半径调整网络节点最小跳数，利用最小均方差和权重因子优化网络节点平均跳距，采用改进的哈里斯鹰算法替代最小二乘法进行位置计算，引入Tent混沌映射、精英群体制度和正余弦优化策略以避免算法过早陷入局部优化，通过最优解求解得到网络节点近似坐标值。仿真结果表明，在不同条件下，改进算法与传统DV-Hop算法和ABCDV-Hop算法相比能够具有更好的定位能力，节点定位误差平均下降20.13%和7.74%，定位精度较高。

DV-Hop localization algorithm combining ranging correction and Harris hawks optimization

Aiming at the low accuracy of traditional DV-Hop positioning algorithm in wireless sensor network node positioning, this paper proposes an improved DV-Hop algorithm based on ranging correction and Harris hawks optimization algorithm. The algorithm uses multi-communication radius to adjust the minimum hop number of network nodes, optimizes the average hop distance of network nodes by using the minimum mean square error and weight factor, uses the improved Harris hawks algorithm to replace the least square method for position calculation, and introduces Tent chaotic mapping and elite group system. And the sine and cosine optimization strategy is used to avoid the algorithm falling into local optimization prematurely, and the approximate coordinate value of the network node is obtained by solving the optimal solution. The simulation results show that under different conditions, the improved algorithm can have better positioning ability compared with the traditional DV-Hop algorithm and ABCDV-Hop algorithm, the node positioning error is reduced by 20.13% and 7.74% on average, and the positioning accuracy is higher.