RSS and IMU Indoor Navigation Information Fusion System in ZigBee Wireless Sensor Networks

• Main Authors: Sung-Ling Wang, 王菘麟
• Other Authors: Shau-Shiun Jan
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/54938477950734418381

碩士 === 國立成功大學 === 航空太空工程學系碩博士班 === 94 === This thesis investigates a new fused indoor position determination technique. The fused position determination technique takes the advantages of position information from measurements of Inertial Measurement Unit (IMU) and the distance prediction based positioning algorithm in a wireless sensor network. The goal of this thesis is to obtain an accurate, drift-free positioning method indoors by utilizing the technique mentioned above. In this thesis, the distance prediction based positioning algorithm uses degradation of received signal strength (RSS) in the user end as an indication of distance between beacons and the user in a wireless sensor network. Four sensors in the network act as beacons. A signal propagation model must be utilized to transfer the RSS information into distance. As a consequence, no matter what kind of signal propagation model is chosen, one must determine the parameters of signal propagation model before utilizing it. This thesis uses a simple, straightforward but effective self-parameter-determination technique to determine the parameters of the signal propagation model at different environments in a wireless sensor network. This thesis tries to fuse the position information obtained from the distance prediction based positioning algorithm and IMU using Kalman filter for static case and Iterated Least Squares (ILS) filter for dynamic case. The experimental results by utilizing position information obtained from distance prediction based positioning algorithm, measurements of IMU and the fused method will be shown. The position information obtained from IMU is relatively accurate in comparison with which obtained from the distance prediction based positioning algorithm. However, only distance prediction based positioning algorithm can determine the absolute position of a user in a wireless sensor network. By fusing the two methods, the accuracy of the fused positioning system is about 1m RMS error.