摘要
船舶人员室内位置的锁定,受到定位算法的影响,导致平均定位误差较高。因此,提出Wi-Fi信号指纹在船舶室内定位中的应用。引入K-mean分类算法,依托于信号强度建立Wi-Fi信号指纹库。针对船舶室内定位空间,建立室内栅格地图。基于实时采集Wi-Fi信号的RSS向量,设计Wi-Fi指纹定位算法。最后,通过计算信息增益值优化AP选取方案,实现定位精度提升。实验结果显示:Wi-Fi信号指纹技术在室内定位中应用后,使得平均定位误差降低了54%,58%。
the indoor position locking of ship personnel is affected by the positioning algorithm,resulting in high average positioning error.Therefore,the application of Wi-Fi signal fingerprint in ship indoor positioning is proposed.K-mean classification algorithm is introduced to establish Wi-Fi signal fingerprint database based on signal strength.Aiming at the indoor positioning space of ships,an indoor grid map is established.Based on the RSS vector of Wi-Fi signal collected in real time,a Wi-Fi fingerprint location algorithm is designed.Finally,the AP selection scheme is optimized by calculating the information gain value to improve the positioning accuracy.The experimental results show that after the application of Wi-Fi signal fingerprint technology in indoor positioning,the average positioning error is reduced by 54%and 58%.
作者
黄婷婷
HUANG Ting-ting(Sino German Institute of Engineering,Shanghai Technical Institute of Electronics and Information,Shanghai 201411,China)
出处
《舰船科学技术》
北大核心
2021年第24期139-141,共3页
Ship Science and Technology
基金
上海市教育科学研究项目(C2021078)
作者简介
黄婷婷(1981-),女,硕士,讲师,研究方向为控制理论与控制工程等。
