Non-Range Based Cooperative Localization for VANETs in Urban Environments

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Authors

Mahmoud, Anas

Date

2015-08-19

Type

thesis

Language

eng

Keyword

Urban Environments , Localization , Ranging , INS/GPS integration , Cooperative Positioning , Cooperative Navigation , VANETs

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Abstract

Location-Based Services (LBS) and Intelligent Transportation Systems (ITS) demand positioning accuracy and availability requirements. In urban canyons, Global Navi- gation Satellite Systems (GNSS) su er from signal blockage, severe multipath, and low Carrier-to-Noise (C/No) ratio which degrade positioning accuracy and availabil- ity. Therefore, applications solely relying on GNSS have limited performance. In this thesis, we present a novel uni ed Cooperative Positioning (CP) solution which en- hances positioning accuracy and availability in urban canyons. The proposed system exploits the fact that vehicles have di erent positioning resources and is based on Angle Approximation (AA). AA requires no infrastructure or other aiding sensors, AA is distributed and addresses two core challenges (limited positioning accuracy and availability) in a uni ed solution. AA arti cially generates the hindered pseudorange by sharing pseudoranges between vehicles using Dedicated Short Range Communi- cation (DSRC). To enhance the performance of the AA technique, we propose the Absolute Sum of Double Di erencing (ASODD) method which increases the probabil- ity of selecting the most accurate generated pseudorange. We also propose a vehicle selection method called Absolute Sum of Single Di erencing (ASOSD). As the dis- tance between vehicles decrease, the accuracy of the proposed system increases and hence ASOSD is utilized to increase the probability of selecting the nearest assistingvehicle to the target vehicle. We have developed an Orbit Simulator to evaluate the performance of our system. In addition, we employ the proposed cooperative system to assist the loose integration between the Inertial Navigation System (INS) and the GPS system (using Extended Kalman Filter) during partial GPS outages. Using raw data from inertial sensors and GPS receivers in real road trajectories, we implement the cooperative INS/GPS loose integration and show that our cooperative integrated system outperforms the non-cooperative integrated system. The performance metrics used are the 2D posi- tioning Root-Mean-Square (RMS) error, the maximum 2D positioning error and the Positioning Accuracy Gain (PAG). Speci cally, the PAG gain is around 88%, 80% and 60% when the number of blocked satellites is one, two and three respectively.

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Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2015-08-18 15:33:57.429

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