CAJ | 학술논문

该文提出一种高精度的移动传感器网络中实现定位跟踪的方法，该方法利用未知节点在运动过程中网络拓扑结构变化的信息提高锚节点利用率，并改善样本采集效率。在无拓扑结构变化的情况下采用牛顿插值方法对节点当前位置进行预测，当拓扑结构有变化时，采用拓扑结构变化构建适应值函数，并用粒子群算法优化样本点的质量。仿真实验结果表明，该文算法与传统算法相比加快了收敛速度，提高了定位精度，改善了在低锚节点密度时的性能。
해문제출일충고정도적이동전감기망락중실현정위근종적방법，해방법이용미지절점재운동과정중망락탁복결구변화적신식제고묘절점이용솔，병개선양본채집효솔。재무탁복결구변화적정황하채용우돈삽치방법대절점당전위치진행예측，당탁복결구유변화시，채용탁복결구변화구건괄응치함수，병용입자군산법우화양본점적질량。방진실험결과표명，해문산법여전통산법상비가쾌료수렴속도，제고료정위정도，개선료재저묘절점밀도시적성능。
The paper presents a high precision of localization algorithm in mobile sensor networks. The algorithm uti-lizes topological change of unknown nodes during the process of node motion to improve utilization of anchor node and the efficiency of sampling. In the case of no topological change,Newton interpolation will be adopted to calcu-late the current position of the node and when the topology changes, the fitness function will be created with the changes,then the particle swarm optimization will be applied to optimize the sample quality. Simulation result show that the algorithm outperforms the tranditional algorithm in convergence speed,localiization accuracy,and require-ment of node density.