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2 2011

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Assisting personal positioning in indoor environments using map matching

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Attia M. , Moussa A. , Zhao X. , El-Sheimy N.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

2011

tom Vol. 22

39--49

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.

Particle swarm optimization algorithm based low cost magnetometer calibration

100%

Ali A. , Siddharth S. , Syed Z. , El-Sheimy N.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

2011

tom Vol. 22

9--23

Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a microprocessor provide inertial digital data from which position and orientation is obtained by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the absolute user heading based on Earth’s magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are corrupted by several errors including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO) based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometer. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. The estimated bias and scale factor errors from the proposed algorithm improve the heading accuracy and the results are also statistically significant. Also, it can help in the development of the Pedestrian Navigation Devices (PNDs) when combined with the INS and GPS/Wi-Fi especially in the indoor environments.