基于测距修正及改进灰狼优化器的DV-Hop定位算法研究

Research on DV-Hop location algorithm based on range correction and improved gray wolf optimizer

节点定位是无线传感器网络中的一个重要问题,基于测距的定位算法虽然定位误差较小,但在应用于室外三维环境时具有较多的局限性。因此,以原始的距离向量(DV-Hop,distance vector-hop)算法为研究基础,分别引入接收信号强度指示(RSSI,received signal strength indication)算法和最小均方误差(MMSE,minimum mean squared error)准则对算法的测距过程进行修正,同时采用改进的灰狼优化器对确定未知节点坐标的过程进行优化处理。仿真结果表明,相较于原始DV-Hop算法和IPDV-Hop算法,IGDV-Hop算法在初始参数下的平均定位误差率分别降低了28%和17%,定位效果得到明显改善。

Node location is an important problem in wireless sensor network.Although the location algorithm based on distance measurement has small positioning error,it has many limitations when applied to outdoor environments.Therefore,based on the original distance vector-hop(DV-Hop)algorithm,received signal strength indication(RSSI)technology and the minimum mean square error(MMSE)criterion to modify the algorithm’s ranging process were introduced,and the improved gray wolf optimizer was used to optimize the process of determining the coordinates of unknown nodes.Simulation results show that,compared with the original DV-Hop algorithm and IPDV-Hop algorithm,the average location error rate of the IGDV-Hop algorithm under the initial parameters was reduced by 28%and 17%respectively,and the location effect was significantly improved.