期刊名称：Archiwum Fotogrametrii, Kartografii i Teledetekcji
印刷版ISSN：2083-2214
出版年度：2011
卷号：22
语种：English
出版社：Main Board of Association of Polish Surveyors
摘要：Personal positioning is facing a huge challenge to maintain a reliable accuracy through all applications. Although in outdoor applications,several mobile navigation devices can provide acceptable positioning accuracy,the situation in indoor environment is not the same. Mobile navigation devices mainly contain a global positioning system (GPS) receiver and an inertial measurement unit (IMU). The main drawback in indoor navigation applications is the unavailability of the GNSS signals,which decreases the possibility of obtaining an accurate absolute position solution,as the inertial system (INS) solution will drift with time in the absence of external updates. Several alternatives were presented lately to update the inertial solution such as using Wi-Fi,UWB, RFID,several self-contained sensors,imaging aiding and spatial information aiding. In order to achieve accurate position solution,with low-cost and usable technique,an integrated mobile navigation system integrating GPS/IMU/Wi-Fi and map-matching was developed. The developed system uses the prior knowledge of the indoor geometrical and topological information,as a threshold for the navigation solution,forcing the provided solution to be mostly on the right track. The geometrical and topological information for the building was used to build the geospatial data model. The use of this model was performed by developing a map matching algorithm which uses the geometrical and topological characteristics of the building to locate the user position on the building map. This algorithm was developed based on the geospatial information of the Engineering building, University of Calgary,where the field test occurred. The map-matching algorithm was evaluated by processing and comparing two separate navigation solutions through the study area,one using only the GPS/IMU/Wi-Fi system,and second solution was assisted with the map-matching algorithm which shows significant enhancement in the position solution for the indoor trajectory.
