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SINS/GPS/PDR室内外无缝导航定位算法
时间: 2021-05-10 次数:

张鹏, 王树森, 李孟委.SINS/GPS/PDR室内外无缝导航定位算法[J].河南理工大学学报(自然科学版),2021,40(3):113-119.

ZHANG P, WANG S S, LI M W.SINS/GPS/PDR indoor and outdoor seamless navigation and positioning algorithm[J].Journal of Henan Polytechnic University(Natural Science) ,2021,40(3):113-119.

SINS/GPS/PDR室内外无缝导航定位算法

张鹏1,2, 王树森1,2, 李孟委1,2

1.中北大学 电子测试技术国家重点实验室,山西 太原  030051;2.中北大学 南通智能光机电研究院,江苏 南通 226000

摘要:针对城市高楼、隧道、室内外等多种复杂环境下单源导航定位系统的定位精度低、可靠性差和不连续等问题,提出一种基于GPSMIMU、表面肌电信号(SEMG)传感器、三维电子罗盘的SINS/GPS/PDR室内外无缝导航定位算法。利用SEMG传感器配合三维电子罗盘进行行人航位推算,同时以捷联惯导为主,多传感器辅助的方式建立多源信息融合模型,设计自适应联邦卡尔曼滤波算法。行走测试结果表明,该方法能够实现室内外无缝导航定位,多源融合的精度水平优于1.5 m(室外)/2 m(室内),显著改善了定位精度与连续性。

关键词:室内外无缝导航定位;行人航迹推算;多源信息融合;自适应联邦卡尔曼滤波器

doi:10.16186/j.cnki.1673-9787.2020040018

基金项目:军委装备发展部装备预研基金资助项目(41403010305 );装备预研兵器工业联合基金资助项目(6141B012907

收稿日期:2020/04/06

修回日期:2020/05/14

出版日期:2021/05/15

SINS/GPS/PDR indoor and outdoor seamless navigation and positioning algorithm

ZHANG Peng1,2, WANG Shusen1,2, LI Mengwei1,2

1.Science and Technology on Electronic Test & Measurement Laboratory North University of China Taiyuan  030051 Shanxi China;2.Nantong Institute of Intelligent Opto-mechatronics North University of China Nantong  226000 Jiangsu China

Abstract:In order to solve the problems of low positioning accuracy poor reliability and discontinuity of the single-source navigation and positioning system in various complex environments such as urban high-rise buildings tunnels indoors and outdoors a SINS/GPS/PDR indoor and outdoor seamless navigation and positioning algorithm based on GPS MIMU surface electromyographic SEMG signal sensor and three-dimensional electronic compass was proposed. By using the SEMG sensor and the three-dimensional electronic compass for pedestrian dead reckoning while by using strapdown inertial navigation as the main method a multi-source information fusion model was established based on a multi-sensor assisted method and an adaptive federated Kalman filter algorithm was designed. The walking test results showed that the method could achieve seamless indoor and outdoor navigation and positioning and the accuracy level of multi-source fusion was better than 1.5 m outdoor /2 m indoor which significantly improved the positioning accuracy and continuity. 

Key words:indoor and outdoor seamless positioning;pedestrian dead reckoning;multi-source information fusion;adaptive federal Kalman filter

 SINS_GPS_PDR室内外无缝导航定位算法_张鹏.pdf

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