Novel WiFi/MEMS Integrated Indoor Navigation System Based on Two-Stage EKF

Abstract

Indoor navigation has been developing rapidly over the last few years. However, it still faces a number of challenges and practical issues. This paper proposes a novel WiFi/MEMS integration structure for indoor navigation. The two-stage structure uses the extended Kalman filter (EKF) to fuse the information from WiFi/MEMS sensors and contains attitude-determination EKF and position-tracking EKF. In the WiFi part, a partition solution called “moving partition” is originally proposed in this paper. This solution significantly reduces the computation time and enhances the performance of the traditional Weighted K-Nearest Neighbors (WKNN) method. Furthermore, the direction measurement is generated utilizing WiFi positioning results, and a “turn detection” is implemented to guarantee the effectiveness. The navigation performance of the presented integration structure has been verified through indoor experiments. The test results indicate that the proposed WiFi/MEMS solution works well. The root mean square (RMS) position error of WiFi/MEMS is 0.7926 m, which is an improvement of 20.59% and 36.60% when compared to MEMS and WiFi alone. Besides, the proposed algorithm still performs well with very few access points (AP) available and its stability has been proven.

Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

“…Wi-Fi systems are prone to noise and require complex processing algorithms. The accuracy of this kind of system is not enough to handle an accurate trajectory estimation in NLOS industrial indoor environments in our case [26,27]. UWB is interesting thanks to its wide bandwidth which makes it more accurate in industrial warehouses.…”

A New Dataset of People Flow in an Industrial Site with UWB and Motion Capture Systems

“…This system is expensive to use in a large area due to deployment of tags. RFID systems cannot do trajectory tracking because most of them rely on proximity detection of permanently mounted tags to locate mobile readers [13,14]. UWB will be more interesting because it needs fewer tags and it uses higher bandwidth (above 3.5 GHz), which leads to a better accuracy.…”

Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

“…Wifi systems are prone to noise and requires complex processing algorithms. The accuracy of this kind of systems is not enough to handle an accurate trajectory estimation in NLOS industrial indoor in our case [25,26]. UWB is interesting thanks to its large bandwidth make it more accurate in industrial warehouses.…”