基于进化算法的多通信半径DV-Hop改进定位算法

定位是无线传感器网络中最重要的问题之一。针对DV-Hop算法定位精度低问题,提出基于进化算法的多通信半径DV-Hop改进定位算法。该方法在多通信半径定位算法基础上,使用蛙跳算法对锚节点跳距进行优化,并对其适应值函数进行改进,让跳距值更接近真实值,然后在DV-Hop算法最后阶段利用遗传算法求解未知节点坐标。实验仿真结果表明,改进算法在不增加额外硬件情况下,大大降低了定位误差,相比于传统DV-Hop算法,定位精度提高了大约69%,相比其他文献,定位精度提高了大约21%。

Improved Localization Algorithm of Multiple Communication Radius DV-Hop Based on Evolutionary Algorithm

Localization is one of the most important problems in Wireless Sensor Networks（WSN）. Aiming at the problem of low localization accuracy of DV-Hop algorithm, an improved multi-communication radius of DV-Hop localization algorithm based on an evolutionary algorithm is proposed. A leapfrog algorithm is applied to optimize a jump distance of anchor nodes and an adaptive function is modified in order to render the jump distance closer to a ture value. Then, in the last phase of DV-Hop algorithm, a genetic algorithm is used to solve a coordinates of unknown nodes. Experimental simulation results have shown that the improved approach greatly reduces a localization error without adding an additional hardware resource. Compared to a traditional DV-Hop algorithm, the positioning accuracy is improved by about 69%. The localization accuracy is increased by 21% comparing to other literature.