摘要
大型船舶内部结构复杂,传统导航定位技术无法穿透船舱实现舱体内的人员定位需求。本文设计了基于WLAN的舱体内RSS指纹定位方法,在离线阶段,采集并训练RSS位置指纹;在在线定位阶段,将实时采集的数据与离线指纹库中数据进行比对,估算出定位结果。针对船舶舱体结构复杂、封闭空间多的特点,文章在定位的在线阶段和离线阶段,分别提出了贝叶斯分簇定位算法和基于信息增益的AP选择改进算法,并与传统算法进行仿真实验对比。结果表明,本文所提算法能够符合舱体内定位的精度需求,且与原有算法相比,进一步提升了定位精度。
Large internal structure of the ship is complex, Traditional navigation and positioning technology can not penetrate the cabin to achieve staff positioning. This paper designs the RSS fingerprint positioning method based on WLAN. In the offline phase, collect and train RSS location fingerprints. In the online positioning phase, the data collected in real time is compared with the offline fingerprint library to estimate the positioning result. Aiming at the characteristics of complex and closed space of the ship＇s cabin, the Bayesian clustering algorithm and the algorithm of AP selection based on informa-tion gain are proposed in the online and offline stages of positioning, and the simulation experiment is carried out with the traditional algorithm Compared. The results show that the proposed algorithm can meet the accuracy requirements of positioning in the cabin, and further improve the positioning accuracy compared with the original algorithm.
作者
许智勋
高尚
XU Zhi-xun;GAO Shang(School of Computer Science and Engineering,Jiangsu University of Science and Technology,Zhenjian 212003,China)
出处
《舰船科学技术》
北大核心
2018年第8期114-118,共5页
Ship Science and Technology
基金
国家自然科学基金资助项目(61572242)
人工智能四川重点实验室开放课题资助项目(2016RYJ03)
关键词
舱体内定位
位置指纹
定位算法
AP选择算法
cabin positioning
location fingerprint
positioning algorithm
AP selection algorithm
