Non-line-of-sight localization in an indoor multipath environment

Indoor and outdoor localization has generated enough attention in recent years. Global Positioning System (GPS), the most commonly used localization scheme, uses several Line of Sight (LOS) signal paths to serve the purpose of localization by setting up enough number of independent equations. But th...

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Bibliographic Details
Main Author: Wen, Kai.
Other Authors: Tan Soon Yim
Format: Final Year Project (FYP)
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/46103
Description
Summary:Indoor and outdoor localization has generated enough attention in recent years. Global Positioning System (GPS), the most commonly used localization scheme, uses several Line of Sight (LOS) signal paths to serve the purpose of localization by setting up enough number of independent equations. But this method fails if there are no sufficient LOS paths and it can’t be used in the indoor environment, where many obstacles and reflectors are existed. Current state of the art localization scheme is capable of estimating Mobile Device (MD) location using both Line of Sight (LOS) and Non Line of Sight (NLOS) paths and bidirectional Time of Arrival (TOA) and Angle of Arrival (AOA) information at both Reference Device (RD) and MD ends in two and even three dimensions. However, information that have been collected, like coordinates of estimated MD location, TOA and AOA can be further used for other important purposes. In this paper, based on previous people’s work, a method is proposed to reconstruct the 2-dimentional environment by using estimated MD location, TOA and AOA information. Single bound reflection and second bound reflection paths are utilized to find the reflection points, from which the environment can be reconstructed. Meanwhile, the algorithm to distinguish LOS, single bound reflection and second bound reflection paths is also proposed. Furthermore, Gaussian noise is added onto both TOA and AOA. The effects of noise on the performance of proposed method are also studied in this paper. Last but not least, a set of grids and weighting factor are designed, which will be beneficial to see the effects of noise and it may be helpful in future work to increase accuracy of reconstructed environment.