DocumentCode
67482
Title
Inertial Sensor Based Indoor Localization and Monitoring System for Emergency Responders
Author
Rui Zhang ; Hoflinger, F. ; Reindl, Leonhard
Author_Institution
Dept. of Microsyst. Eng., Univ. of Freiburg, Freiburg, Germany
Volume
13
Issue
2
fYear
2013
fDate
Feb. 2013
Firstpage
838
Lastpage
848
Abstract
This paper presents a novel indoor localization and monitoring system based on inertial sensors for emergency responders. The system utilizes acceleration, angular rate and magnetic field sensors and consists of three parts. The first part is a modified Kalman filtering which implements the sensor data fusion and meanwhile detects and minimizes the magnetic field disturbances, so as to provide a long term stable orientation solution. The second part is zero velocity updating which resets the velocity within still phase to deliver accurate position information. The last part of the system is body movement monitoring, which is achieved by calculating the relative position of each body segment based on the transformation of coordinate frame of each body segment. The experimental result shows that the system is able to track person indoors in both walking and running cases, and to monitor the body movement during whole period of experiment.
Keywords
Kalman filters; acceleration measurement; angular velocity measurement; body sensor networks; emergency services; magnetic field measurement; magnetic sensors; monitoring; position measurement; sensor fusion; acceleration sensor; angular rate sensor; body movement monitoring; body segmentation; coordinate frame transformation; emergency responder; indoor localization; inertial sensor; magnetic field disturbance; magnetic field sensor; modified Kalman filtering; person indoor tracking; position information; relative position calculation; sensor data fusion; zero velocity; Acceleration; Earth; Kalman filters; Magnetic separation; Magnetometers; Monitoring; Vectors; Indoor localization; Kalam filter; inertial measurement unit (IMU); magnetic field disturbances; orientation; sensor data fusion; zero velocity update (ZUPT);
fLanguage
English
Journal_Title
Sensors Journal, IEEE
Publisher
ieee
ISSN
1530-437X
Type
jour
DOI
10.1109/JSEN.2012.2227593
Filename
6353495
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