期刊文献+

地磁信息辅助的多维指纹室内移动轨迹映射方法 被引量:2

Multidimensional Fingerprints Method for Indoor Mobile Trajectory Mapping with Geomagnetic Information
下载PDF
导出
摘要 该文提出一种基于多维指纹地磁信息辅助的室内移动轨迹映射方法。利用Wi-Fi指纹获得初始位置,手机内置的惯性传感器指纹实时收集数据,结合室内平面图推算用户的瞬时位置;利用地磁感应器指纹实时收集行人真实位置的磁场数据,采用最小均方根算法校准移动设备的轨迹;利用规范向量和单位向量滤除预测错误的位置。实验表明,该文方法与现有的室内轨迹映射方法相比,在减小计算量的条件下提高了轨迹映射精度。 A trajectory mapping method, called MagCom, is proposed based on the geomagnetic perception of indoor mobile devices. MagCom gets the initial position by means of Wi-Fi localization technology, and then calculates the instantaneous position of users continuously leveraging data of the phone's built-in inertial sensors in real time by the floors plan. The magnetic field data of the pedestrian’s location are captured to calibrate the mapping trajectory of mobile devices with the least squares algorithm. Furthermore, the unit vector and the norm vector are applied to reduce outliers in the searching algorithm. The experimental results show that the proposed method can not only improve the trajectory mapping accuracy but reduce the computational complexity than the state of arts.
出处 《电子与信息学报》 EI CSCD 北大核心 2013年第10期2397-2402,共6页 Journal of Electronics & Information Technology
基金 国家自然科学基金(60970123 61272466) 秦皇岛市科学技术与研究发展计划(2012021A045 2012021A046)资助课题
关键词 惯性导航 轨迹映射 指纹匹配 磁场强度 移动设备 Inertial navigation Trajectory mapping Fingerprint matching Magnetic field strength Mobile devices
  • 相关文献

参考文献4

二级参考文献35

  • 1王鼎,张莉,吴瑛.基于角度信息的结构总体最小二乘无源定位算法[J].中国科学(F辑:信息科学),2009,39(6):663-672. 被引量:19
  • 2Song T L and Speyer J L. A stochastic analysis of a modified gain extended Kalman filter with application to estimation with bearings-only measurements. IEEE Trans. on Automatic Control, 1985, AC-30(10): 940-949.
  • 3Ristic B, Arulampalam S, and Gordon N. Beyond the Kalman Filter: Particle Filters for Tracking Applications. Boston, London: Artech House, 2004, Chapter 5-12.
  • 4Doucet A, de Freitas N, and Gordon N (Eds.). Sequential Monte Carlo Methods in Practice. New York: Springer, 2001, Chapter 15-26.
  • 5Doucet A and Wang X D. Monte Carlo methods for signal processing: A review in the statistical signal processing context. IEEE Signal Processing Magazine, 2005, 22(6): 152-170.
  • 6Gordon N, Salmond D, and Smith A. Novel approach to nonlinear/non-Gaussian Bayesian state estimation, lEE Proceedings on Radar and Signal Processing, 1993, 140(2): 107-113.
  • 7Zhai Y and Yeary M. A new particle filter tracking algorithm for DOA sensor system. Proc. of Instrumentation and Measurement Technology, Warsaw, 2007: 1-4.
  • 8Bolic M, Athalye A, and Djuric P M, et al. Algorithmic modification of particle filters for hardware implementation. Proc. of the European Signal Processing. Conference, Vienna,Austria, 2004: 1641-1646.
  • 9Bolic M, Djuric P M, and Hong S. Resampling algorithms for particle filters: A computational complexity perspective. EURASIP Journal of Applied Signal Processing: 2004, (15): 2267-2277.
  • 10Athalye A, Bolic M, and Hong S, et al Generic hardware architectures for sampling and resampling in particle filters. EURASIP Journal of Applied Signal Processing, 2005, (17): 2888-2902.

共引文献57

同被引文献29

  • 1秦杰,陈希,武穆清.A-GPS定位技术的研究与应用[J].数字通信世界,2007(3):53-56. 被引量:4
  • 2Want R, Hopper A, Falcao V,et al. The Active Badge LocationSystem[J]. ACM Trans on Information Systems, 1992,10(2) :91-102.
  • 3Ward A, Jones A, Hopper A. A New Location Technique for theActive Office [J]. Personal Communications, IEEE, 1997,4(5):42-47.
  • 4Woodman 0 J. An Introduction to Inertial Navigation [J]. Comput-er Laboratory, University of Cambridge, Tech Rep UCAMCL-TR-696,2007,14:15.
  • 5Iglesias H J P,Barral V,Escudero C J. Indoor Person LocalizationSystem through RSSI Bluetooth Fingerprinting [C]//Systems, Sys-tems ,Signals and Image Processing,2012 19th International Con-ference on. IEEE ,2012: 40-43.
  • 6Hong F, Zhang Y, Zhang Z, et al. WaP: Indoor Localization andTracking Using Wifi-Assisted Particle Filter [ C ]//Local ComputerNetworks (LCN),2014 IEEE 39th Conference on. IEEE, 2014.210-217.
  • 7Mahfouz M R,Fathy A E,Kuhn M J,et al. Recent Trends and Ad-vances in UWB Positioning [J]. Wireless Sensing, Local Position-ing, and RFID,2009. IMWS 2009. IEEE MTT-S International Mi-crowave Workshop on. IEEE ,2009. 1-4.
  • 8DeGregoria A. Gravity Gradiometry and Map Matching : An Aid toAircraft Inertial Navigation Systems [R]. Air Force Inst of TechWright- Patterson Afb Oh Graduate School of Engineering AndManagement,2010.
  • 9Chung J,Donahoe M,Schmandt C,et al. Indoor Location SensingUsing Geo- Magnetism [C]//Proceedings of the 9th InternationalConference on Mobile Systems,Applications, and Services,2011 :141-154.
  • 10Kim S E, Kim Y, Yoon J, et aJ. Indoor Positioning System UsingGeomagnetic Anomalies for Smartphones [C]//Indoor Positioningand Indoor Navigation, 2012 International Conference on. IEEE,2012:1-5.

引证文献2

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部