基于人行为地图的室内PIR定位方法

doi:10.12068/j.issn.1005-3026.2018.06.004

东北大学学报:自然科学版 ›› 2018, Vol. 39 ›› Issue (6): 776-780.DOI: 10.12068/j.issn.1005-3026.2018.06.004

基于人行为地图的室内PIR定位方法

杨丹，徐彬

(东北大学信息科学与工程学院，辽宁沈阳110819)

收稿日期:2017-02-27 修回日期:2017-02-27 出版日期:2018-06-15 发布日期:2018-06-22
通讯作者: 杨丹
作者简介:杨丹(1979-)，女，辽宁营口人，东北大学副教授，博士.冯明杰(1971-)，男，河南禹州人，东北大学副教授; 王恩刚(1962-)，男，辽宁沈阳人，东北大学教授，博士生导师.
基金资助:
国家自然科学基金资助项目(51607029)国家自然科学基金资助项目(51171041)..

PIR-based Indoor Localization Method Combined with Human Behavior-based Map

YANG Dan， XU Bin

School of Information Science & Engineering， Northeastern University， Shenyang 110819， China.

Received:2017-02-27 Revised:2017-02-27 Online:2018-06-15 Published:2018-06-22
Contact: XU Bin
About author:-
Supported by:
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摘要/Abstract

摘要： 针对老人家庭看护中的室内定位问题，提出了一种基于人行为地图的室内热红外释电传感器(pyroelectric infrared sensor， PIR)定位方法.首先采集PIR传感器检测身体运动信号来确定人在室内的初步位置信息;利用惯性测量单元(inertial measurement unit， IMU)检测3D加速度信号识别人在室内的基本日常行为——躺、坐、站、走;利用IMU的3D加速度信号估计人的室内移动速度和方向;通过行为习惯观察，建立相应的躺、坐、站、走的行为地图;通过粒子滤波方法融合上述传感器信息，实现定位.实验结果表明，提出的方法在定位时，既保护人的隐私，也提高基于PIR传感器定位的精度及稳定性.

关键词: 室内定位, 行为地图, 热红外释电传感器, 惯性测量单元, 粒子滤波

Abstract: Aiming to human localization method for elder people assisting in smart home， a method was proposed to realize the indoor localization by pyroelectric infrared sensor (PIR) combined with human behavior-based map. PIRs were used for collecting body motion signal to localize the subject’s raw position in the room. One inertial measurement unit (IMU) was used to collect 3D motion data for human daily body activity recognition such as lying， sitting， and standing. The other IMU was used for velocity and direction estimation. The related behavior-based maps were built by human habits observation. Particle filters method was presented to fuse the data from PIR and IMU，and took into account these prior behavior-based maps to get more accurate localization. Experimental results showed that the proposed approach has the advantage of protecting the privacy while maintaining high accuracy and stability of indoor localization.

Key words: indoor localization, behavior-based map, pyroelectric infrared sensor(PIR), inertial measurement unit(IMU), particle filters

中图分类号:

TN98

杨丹，徐彬. 基于人行为地图的室内PIR定位方法[J]. 东北大学学报:自然科学版, 2018, 39(6): 776-780.

YANG Dan， XU Bin. PIR-based Indoor Localization Method Combined with Human Behavior-based Map[J]. Journal of Northeastern University Natural Science, 2018, 39(6): 776-780.

参考文献

[1]黄毅，佟晓光.中国人口老龄化现状分析［J］.中国老年学杂志，2012，32 (21):4853-4855.(Huang Yi，Tong Xiao-guang.Analysis of the current situation of China’s population aging［J］.Chinese Journal of Gerontology，2012，32 (21):4853-4855.)
[2]Skubic M，Alexander G，Popescu M.A smart home application to eldercare:Current status and lessons learned［J］.Technology and Health Care，2009，3:183-201.
[3]Bahadori S，Iocchi L，Leone G R，et al.Towards ambient intelligence for the domestic care of the elderly［J］.Applied Intelligence:The International Journal of Artificial Intelligence，Neural Networks，and Complex Problem-Solving Technologies，2007，26(2):83-97.
[4]Takuya M，Tetsushi I，Hiroshi I.Human tracking using floor sensors based on the Markov chain Monte Carlo method［C］//Proceedings of International Conference on Pattern Recognition.Cambridge，2004:917-920.
[5]Shen B H，Wang G L.Distributed target localization and tracking with wireless pyroelectric sensor networks［J］.International Journal on Smart Sensing and Intelligent Systems，2013，6(4):1400-1418.
[6]Hsiao R S，Chung C H，Cheng S C，et al.Indoor target detection and localization in pyroelectric infrared sensor networks［C］//Proceedings of the 8th Asia Pacific Wireless Communications Symposium.Singapore，2011:115-119.
[7]Luo R C，Chen O.Indoor human dynamic localization and tracking based on sensory data fusion techniques［C］//The International Conference on Intelligent Robots and Systems.St.Louis，2009:860-865.
[8]Al-Naimi I，Wong C B，Moore P.Advanced approach for indoor identification and tracking using smart floor and pyroelectric infrared sensors［C］//The 5th International Conference on Information and Communication Systems(ICICS).Jordan，2014:1-6.
[9]Kim H H，Ha K N.Resident location-recognition algorithm using a Bayesian classifier in the PIR sensor-based indoor location-aware system［J］.IEEE Transactions on Systems，Man and Cybernetics Part C:Applications and Reviews，2009，39(2):240-245.
[10]Arulampalam M S，Maskell S，Gordon N J，et al.A tuturial on particle filters for online nonlinear/non-Gaussian Bayesian tracking［J］.IEEE Transactions on Signal Processing，2002，50(2):174-188.

基于人行为地图的室内PIR定位方法

PIR-based Indoor Localization Method Combined with Human Behavior-based Map

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