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一种基于手机端的室内外场景识别方法及其初步实验 被引量:4

A Method of Indoor and Outdoor Scene Recognition Based on Mobile Phone and Its Preliminary Experiment
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摘要 场景识别是室内外无缝定位技术的研究重点,场景识别的好坏决定了位置服务用户体验的优劣,已有室内外场景识别研究方法存在数据冗余和计算复杂度高的问题。鉴于此,该文提出一种基于手机端的室内外场景识别方法,利用智能手机获取GPS卫星高度角、信噪比和卫星数目,通过分析上述实验数据的相互作用影响,得到基于截止高度角、信噪比阈值和GPS卫星数目阈值的室外到室内场景识别判定依据,实验证明,该判定依据可有效区分室外、室外到室内过渡区域和室内场景。为得到普适的室内外场景识别方法,该判定依据需在其他场景进一步验证。 Scene recognition is the key research of indoor and outdo or seamless positioning technology.The scene recognitiontechnology usually determines t heuser experience of Location-Based Services(LBS).Researcher scarried out the indoor andoutdoor scene recognition with the problems of data redundancy and high computational complexity.Therefere,in oder toquickly and accurately recognize scenes from outdoor to indoor,a novel method of indo or and outdoor scene recognition based ona mobile phone is proposed.GPS elevat ion ang le,Sig nal Noise Ratio(SNR),and GPS satellitesc number can be received on thesmar tpho ne.By analyzing the inter action of the above exper imental data comprehensively,the obtaining judgment basis of scenerecog nition from outdoor to indoor is based on GPS elevation mask angle,SNR threshold,and GPS satellitesc number.In the experimental test environment,the judgment basis can be used to disting uish the outdoor scenes,outdoor to the indo or transitionareas,and the indoor scenes.But in order to obtain univ ersal indoor and outdoor scene recognition methods,the judgment basisshould be further v erified inot her scenarios.
作者 毕京学 汪云甲 甄杰 BI Jing-xue;WANG Yun-jia;ZHEN Jie(School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou 221116;Chinese Academy of Surveying and Mapping,Beijing 100830,China)
出处 《地理与地理信息科学》 CSCD 北大核心 2017年第3期48-51,共4页 Geography and Geo-Information Science
基金 国家重点专项"室内混合智能定位技术"(2016YFB0502102) 江苏省普通高校学术学位研究生创新计划项目(KYLX16_0544)
关键词 室内外无缝定位 场景识别 GPS 高度角 信噪比 卫星数目 indoor and outdoor seamless positioning scene recognition GPS elevation angle SNR the number of satellites
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