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dc.contributor.advisor汤碧玉
dc.contributor.advisor郑灵翔
dc.contributor.author翁少林
dc.date.accessioned2018-12-05T01:48:15Z
dc.date.available2018-12-05T01:48:15Z
dc.date.issued2017-12-28
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/170661
dc.description.abstract基于惯性导航的室内定位系统不需要依赖外部源便可定位,且使用方便,成本低廉,具有很强的适应性。随着智能手机的普及,基于惯性传感设备安装在人体上半身的室内定位系统(也称手持式室内定位系统)成为了研究热点。到目前为止,由于人类步态的多样性,在手持式室内定位系统中,对于不同场景下的步长估计缺乏一个高精度、通用的算法。本文拟设计一种自适应的步长估计算法,实现对手持式室内定位系统中步长的准确估计。 本文通过对手持式室内定位系统中人员行进时腰部的运动特性进行研究分析,设计了基于“线性倒立摆”模型的步长估计算法,并对模型中回归系数的影响因素以及算法对步长估计的误差进行分析。引入BP神经网络,实现了模型回归系...
dc.description.abstractIndoor positioning system based on inertial navigation has many advantages, such as low cost, easy to use, working without external sources, so it has a strong adaptability. With the popularity of smart phones, the positioning system based on inertial sensing equipment installed in the upper body (also known as the handheld indoor positioning system) has become a research hotspot. Due to the diver...
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=58585&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=60105
dc.subject步长估计
dc.subject神经网络
dc.subject自适应模型
dc.subjectstep length estimation
dc.subjectneural network
dc.subjectadaptive model
dc.title基于惯性传感器的室内定位系统步长估计算法研究
dc.title.alternativeResearch on Step Length Estimation Algorithm in Indoor Positioning System Based on Inertial Sensor
dc.typethesis
dc.date.replied2017-05-18
dc.description.note学位:工程硕士
dc.description.note院系专业:信息科学与技术学院_工程硕士(电子与通信工程)
dc.description.note学号:23320141153268


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