基于自适应与轨迹预测的移动节点定位  

Mobile Node Localization Based on Adaptive Trajectory Prediction

作　　者：郭世俊[1] 吴华锋[1] 刘侠[1] 马奕葳 

机构地区：[1]上海海事大学商船学院,上海201306 [2]中国(上海)自贸区供应链研究院,上海201306

出　　处：《中国航海》2016年第2期1-5,共5页Navigation of China

基　　金：国家自然科学基金(51279099);上海市科学技术委员会基金(12ZR1412500);上海市教委科研创新基金(13ZZ124);上海市教育委员会和上海市教育发展基金会"曙光计划"基金(12SG40);交通运输部应用基础研究项目(2013329810300)

摘　　要：针对海上节点随海浪运动的情形,提出一种基于自适应与轨迹预测的移动节点定位算法(Adaptive and Trajectory Prediction Localization Algorithm,ATPLA)。首先,基于海域信标节点运动情况求得海域节点运动相关性系数,并以此建立参数自适应移动节点运动模型,预测未知节点运动轨迹;随后,提出改进型蒙特卡罗定位方法,优化采样区域和样本点权重;最后,基于未知节点与其一跳、两跳信标节点相对位置进行过滤。仿真结果表明:ATPLA在信标节点密度低、节点运动速度大等情况下具有良好的定位效能,能提高海上动态节点的定位能力,进而提高海上搜救的效率和成功率。The Adaptive and Trajectory Prediction Localization Algorithm（ATPLA） for nodes on sea surface is introduced.As the first step,the motion correlation coefficient related to the notes in an area is obtained according to the motion of beacon nodes in the area,and the parameter adaptive motion model of the nodes is established for predicting the trajectory of interested unknown nodes.The sampling area and the weights of the sampls are refined with Monte Carlo positioning algorithm afterwards.The position of an unknown note can be determined by means of filtering its one hop and two hop distances relative to beacon nodes.Simulation proves that the ATPLA performs well even if in the situation of low beacon density or high node velocity.The use of ATPLA can improve the mobile note positioning efficiency for maritime search and rescue activity.

关 键 词：交通信息工程 无线传感网 高斯马尔科夫定理 蒙特卡洛方法 动态定位 海上搜救 

分 类 号：U644.1[交通运输工程—船舶及航道工程]