ResearchResearch Projects
Optimale kollaborative Positionierung (GRK 2159, Thema 4)

Optimal Collaborative Positioning (GRK 2159, Topic 4)

Leaders:  Prof. Dr.-Ing. Steffen Schön
Email:  garcia@ife.uni-hannover.de
Team:  M.Sc. Nicolas Garcia Fernandez
Year:  2016
Sponsors:  DFG
More Link https://www.icsens.uni-hannover.de/en/research/phd-projects

Collaborative Positioning (CP) is a promising technique in which a group of dynamic nodes (pedestrians, vehicles, etc.) equipped with different (time synchronized) sensors can increase the quality of the Positioning, Navigation and Timing (PNT) information by exchanging navigation information as well as performing measurements between nodes or to elements of the environment (urban furniture, buildings, etc.).

The robustness of positioning increases, describing an improvement in the accuracy, integrity, continuity and availability terms compared to single node positioning, like e.g. standalone GNSS or tightly coupled GNSS + IMU solutions. Hence, the navigation system can be considered as a geodetic network in which some of the nodes are changing their position and in which the links between nodes are defined by measurements carried out with additional sensors (V2X measurements). In order to get insights into the behavior of such networks and to evaluate the benefits of CP with respect to single vehicle approaches, a realistic simulation tool for collaborative navigation systems was developed.

We combine satellite navigation, inertial navigation, laser scanner, photogrammetry and odometry in order to get an algorithm which serves us to fulfill the purposes of fusing multi-sensor data as well as evaluating the correlations and dependencies of the estimated parameters and observations. The simulation tool allows us to grade the advantages and disadvantages of the different sensor measurement fusion algorithms capable of executing CP techniques. The validation of the simulation tool with real data guarantees that the conclusions taken from the analysis lead unequivocally to an improvement in the robustness of the estimation which can be translated into safe and precise navigation.