Sensor-Aided Personal Navigation Systems for Handheld Devices

The positioning technique is the key technique for developing geographic applications, like location based services. The Global Positioning System (GPS) is a common approach for positioning in vehicular navigations. Although GPS can provide absolute position information, the accuracy of GPS is not enough for personal navigations. What is worse, GPS does not work well indoors. Instead, Inertial Measurement Units (IMUs) can be used to track objects with high precision, but it provides relative position information. Thus, integration of GPS and IMU can do positioning indoors and outdoors. In this paper, combining our previous work, a pedestrian tracking system for handheld devices, with GPS leads to a personal navigation system for handheld devices. The position and heading information can be calculated from this system. The system also serves a platform for many applications related to the location.

[1]  David McNeil Mayhew,et al.  Multi-rate Sensor Fusion for GPS Navigation Using Kalman Filtering , 1999 .

[2]  A. El-Rabbany Introduction to GPS: The Global Positioning System , 2002 .

[3]  Bor-Chin Chang,et al.  Diversified redundancy in the measurement of Euler angles using accelerometers and magnetometers , 2007, 2007 46th IEEE Conference on Decision and Control.

[4]  Wei Chen,et al.  An integrated GPS and multi-sensor pedestrian positioning system for 3D urban navigation , 2009, 2009 Joint Urban Remote Sensing Event.

[5]  Dharma P. Agrawal,et al.  GPS: Location-Tracking Technology , 2002, Computer.

[6]  Xiaoping Yun,et al.  Self-contained Position Tracking of Human Movement Using Small Inertial/Magnetic Sensor Modules , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[7]  Angelo M. Sabatini,et al.  A step toward GPS/INS personal navigation systems: real-time assessment of gait by foot inertial sensing , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  N. Noury,et al.  A Fast Algorithm to Track Changes of Direction of a Person Using Magnetometers , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  J.W. Kim,et al.  Adaptive Step Length Estimation Algorithm Using Low-Cost MEMS Inertial Sensors , 2007, 2007 IEEE Sensors Applications Symposium.

[10]  Dan Simon,et al.  Optimal State Estimation: Kalman, H∞, and Nonlinear Approaches , 2006 .

[11]  Elliott D. Kaplan Understanding GPS : principles and applications , 1996 .