Dynamic fine-grained localization in Ad-Hoc networks of sensors
Proceedings of the 7th annual international conference on Mobile computing and networking
An Experimental Study of a Cooperative Positioning System
Autonomous Robots
GPS: Location-Tracking Technology
Computer
Optimal Estimation of Three-Dimensional Rotation and Reliability Evaluation
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
A relative positioning system for co-located mobile devices
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Vehicular Ad Hoc Networks: A New Challenge for Localization-Based Systems
Computer Communications
A survey on localization for mobile wireless sensor networks
MELT'09 Proceedings of the 2nd international conference on Mobile entity localization and tracking in GPS-less environments
Fundamental limits of wideband localization: part I: a general framework
IEEE Transactions on Information Theory
Fundamental limits of wideband localization: part II: cooperative networks
IEEE Transactions on Information Theory
Cramér-Rao bound for hybrid GNSS-terrestrial cooperative positioning
IEEE Communications Letters
Markov-Based Lane Positioning Using Intervehicle Communication
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Mobile Computing
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Nowadays, unmanned aerial vehicles (UAVs) have become very popular for civil as well as military purposes, ranging from small quadcopters up to plane sized drones. UAVs are usually controlled manually or autonomously, both ways often heavily relying on the use of a global positioning system such as GPS. However, especially the wide spread GPS suffers form large positioning errors of 10-30 m on average. In this paper it is shown how UAVs can improve the accuracy of their position estimates by cooperating with each other. By using ranging hardware, UAVs can create a local positioning frame of reference, and use this to reduce the average positioning error of the global positions. This is done by finding an optimal 3D-rotation between the local and global coordinates. By using simulation, we demonstrate the feasibility of our approach, as well as the influence of parameters like vehicle speed and area size on the average positioning error.