| Summary: | 碩士 === 國立臺北科技大學 === 電機工程系所 === 105 === Despite the emerging of various sensor for indoor positioning system (IPS), these sensors have their respective advantages and disadvantages. An innovative indoor positioning system is proposed in this research by fusing an ultra-wideband (UWB) and inertial measurement unit (IMU) sensor-based positioning solution. Given the excellent robustness of UWB and IMU sensors towards the cumulative error and external interference, respectively, the data fusion of these two sensors can lead to the robust and optimal positioning performance. The proposed sensor fusion can be accomplished by using an Extended Kalman Filter (EKF) that can estimate the IMU sensor’s systematic error and correct the positioning error simultaneously. The mechanisms of fault detection, identification and isolation are also built in the EKF design to prevent the corruption of UWB sensor measurement data and degradation of positioning performance due to the obstructions, multi-path and other potential sources of interference. The proposed sensor fusion based indoor positioning algorithm is first simulated, followed by the actual implementation for laboratory test. Extensive studies show that the positioning performance of obtained from the experimental studies are highly correlated with those of simulation results and both have demonstrated the excellent positioning performance.
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