Indoor Wireless Positioning Utilizing WSN and Machine Vision

Abstract:

It is a challenging issue to develop optimal real-time target tracking methods for automobile in the small areas such as urban and indoor environments. In order to get comprehensive navigation information, a target tracking system utilizing ultrasound and machine vision is proposed. In this system, the position, velocity and the yaw in the relative coordinate are used as the state variables, the ultrasound is used to measure the distance between the reference node and the blind node, and the yaw of the automobile is measured by the machine vision. Then, the extended Kalman filter is used to fuse the information measured from local estimators in the proposed method. Simulations show that the position error of the proposed approach is about 0.2m and the velocity error of the proposed approach is about 0.1 m/s.

• Periodical: Applied Mechanics and Materials (Volumes 325-326)
• Pages: 1041-1044
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.325-326.1041
• Online since: June 2013
• Authors: Zeng Yu Wang, Yuan Xu, Qing Hua Li
• Keywords: Extended Kalman Flter (EKF), Machine Vision, Target Tracking, Wireless Sensor Network (WSN)

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