Research And Implementation Of Indoor Positioning System Based On Phase-of-Arrival Ranging

With the rapid development of modern wireless network technology and people’s living standard, people’s demand for locating and navigating increases day by day, especially in the interior space where the global positioning system cannot cover. Therefore, how to locate certain persons and objects’ positions is becoming the key issue of location-based service.For the deficiencies of the prior indoor positioning technology, such as high price, low accuracy, difficulty in monitor, etc., the thesis researches and implements the RTLS (Real Time Location System) based on POA (Phase Of Arrival) which is a kind of great technology with the merits such as low price, low power consumption, high accuracy and ability to support the antenna diversity. Overall, implemented system has outstanding application potential. The thesis conducts deep research about the principle and hardware of POA, designs and implements a system with three parts including bottom layer, PC software and server as well, improves the algorithms of ranging and positioning, and tests the performance of the system.The paper’s main jobs are as follows:(1) Design and implementation of the RTLS based on POA including the bottom layer, PC software and server:The bottom layer uses Atmel’s AT86RF233 to realize basic ranging by phase shift measurements. The nodes management as well as multipoint cycle ranging software are designed to realize the ranging between mobile node and anchors. The PC layer of the system implements data parsing, calculation of positioning coordinates, real-time coordinates display, log record written by C# on Visual Studio. Among them, calculation of positioning coordinates adopts the improved trilateral localization algorithm based on centroid localization method. Remote monitoring server uses HTTP to communicate and utilizes B/S architecture which includes Bootstrap and ThinkPHP to realize data reception of PC software and real-time monitoring on browsers.(2) Optimization of ranging results and improvement of positioning algorithms:The fulfillment of ranging optimization is through the adaptive amplitude-limiting and weighted filter whose functions include weighting the results by DQF (Distance Quality Factor) and adding adaptive amplitude-limiting rules to limit the large fluctuations. Note that, localization algorithm is improved by applying WMMSE (Weighted Minimum Mean Square Error) method which can increase the adaptability.(3) Performance tests of the system under different circumstances:The positioning accuracy, ranging range, anti-multipath ability, and real-time performance of the positioning system are tested separately. Among those, the outdoor long distance ranging experiment tests the accuracy and range of the system; indoor and outdoor fixed-point ranging experiments test the anti-multipath ability of the system; walking ranging experiment in indoor long straight footpath tests the tracking ability of the system; fixed-point positioning experiments in the small underground parking lot test the accuracy and stability of the system; mobile positioning experiment in the small underground parking lot tests the real-time locating ability of the system.