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 information 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.
2018,40(8): 114-118 收稿日期：2017-05-01
DOI：10.3404/j.issn.1672-7649.2018.08.022
分类号：TP391
基金项目：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）
作者简介：许智勋(1990-),男,硕士研究生,研究方向为数据挖掘与信息系统
参考文献：
[1] 苑隆寅. 基于WLAN的船舶通信网络应用与仿真[J]. 舰船科学技术, 2015, (01):191-195. YUAN Long-yin. The application and simulation of shipboard communication network based on WLAN[J]. Ship Science and Technology, 2015, (01):191-195.
[2] 王玲, 张彬祥. 船舶通信导航技术及发展趋势[J]. 舰船电子工程, 2016, (03):17-21. WANG Ling, ZHANG Bin-xiang. Development trend of marine communication and navigation technology[J]. Ship Electronic Engineering, 2016, (03):17-21.
[3] 屈召贵, 刘强. 基于北斗卫星的航行数据导航方法研究[J]. 舰船科学技术, 2016, (08):145-147. QU Zhao-gui, LIU Qiang. Research on navigation data navigation method based on Beidou satellite[J]. Ship Science and Technology, 2016, (08):145-147.
[4] 马远美. 船舶导航雷达运动目标跟踪性能改进方法研究[D]. 大连:大连海事大学, 2013.
[5] 陈迅. 无线传感器网络通信协议及定位算法研究[D]. 上海:复旦大学, 2007.
[6] 钱志鸿, 孙大洋, LEUNG Victor. 无线网络定位综述[J]. 计算机学报, 2016, (06):1237-1256. QIAN Zhi-hong, SUN Da-yang, LEUNG Victor. A survey on localization model in wireless networks[J]. Chinese Journal of Computers, 2016, (06):1237-1256.
[7] 辛艳, 梁建坤, 修长虹. 无线局域网IEEE802.11ac协议的研究及应用[J]. 网络安全技术与应用, 2016, (09):80-81. XIN Yan, LIANG Jian-kun, XIU Chang-hong. Research and application of wireless LAN IEEE802.11ac protocol[J]. Network Security Technology & Application, 2016, (09):80-81.
[8] 丁根明. 基于人工智能的室内指纹定位技术研究[D]. 北京:北京交通大学, 2015.
[9] 梁峰. 大型船舶内部定位导航方法[J]. 中国科技信息, 2016, (21):60-61. LIANG Feng. Navigation method of large ship's internal location[J]. China Science and Technology Information, 2016, (21):60-61.
[10] 李言胜, 孙琳, 王亚坤. 基于ZigBee的舱内人员巡检系统的应用研究[J]. 电脑知识与技术, 2016, (26):238-239+245. LI Yan-sheng, SUN Lin, WANG Ya-kun. Application of Operator Patrol System Based on ZigBee in the Cabin[J]. Computer Knowledge and Technology, 2016, (26):238-239+245.
[11] 叶宝玉, 王钦若, 等. 基于超声波的模型船舶室内定位系统研究[J]. 计算机工程, 2012, (19):258-260+265. YE Bao-yu, WANG Qin-ruo, et al. Research on Indoor Location Systems for Ship Model Based on Ultrasonic[J]. Computer Engineering, 2012, (19):258-260+265.
[12] 谢泰, 刘晓荣, 等. 舰船人员舱内定位及生命体征监测系统研究[J]. 医疗卫生装备, 2016, (03):11-13. XIE Tai, LIU Xiao-rong, et al. Research on inboard positioning and vital signs monitoring system for ship crews[J]. Chinese Medical Equipment Journal, 2016, (03):11-13.
[13] 胡明成. WLAN中集中式的AP选择机制和节能调度方法研究[D]. 西安电子科技大学, 2015.
[14] 陈淼. 基于信号强度的WLAN室内定位跟踪系统研究[D]. 武汉:武汉大学, 2012.
[15] 徐旻捷. 可扩展的贝叶斯学习方法建模与推理[D]. 北京:清华大学, 2015.
[16] YOUSSEF M, AGRAWALA A. Handling samples correlation in the horus system[C]//IEEE InfoCom 2003. 2004(2):1023-1031.
[17] CHEN K Y, YANG Q, YIN J, et al. Power-Efficient Access-Point Selection for Indoor Location Estimation[J]. IEEE Transactions on Knowledge and Data Engineering. 2006, 18(7):877-888.
