Evaluating an LKF Simulation Tool for Collaborative Navigation Systems

Nicolás García Fernández, Steffen Schön

Abstract:	Collaborative Positioning (CP) is a positioning technique in which a group of dynamic nodes (pedestrians, vehicles, etc.) equipped with different time synchronized sensors increase the quality of the Positioning, Navigation and Timing information (PNT) by exchanging navigation information as well as performing measurements between nodes or to elements of the environment such as urban furniture or buildings. The robustness of positioning is supposed to increase, describing an improvement in accuracy, integrity, continuity and availability compared to single node positioning, like e.g. standalone GNSS or tightly coupled GNSS + IMU solutions. In this paper, we describe the development of a realistic simulation tool for collaborative 3D navigation systems. Satellite navigation, inertial navigation and laser scanner techniques are combined in a Linearized Kalman Filter (LKF). Additionally, we discuss the use of available 3D building models with Level of Detail 2 (LoD2) or laser scanner point clouds as environmental models to generate the V2I measurements. We show the impact of the complex ratio between measurement precision and process noise on the estimated states and their precision.
Published in:	2018 IEEE/ION Position, Location and Navigation Symposium (PLANS) April 23 - 26, 2018 Hyatt Regency Hotel Monterey, CA
Pages:	1455 - 1464
Cite this article:	Fernández, Nicolás García, Schön, Steffen, "Evaluating an LKF Simulation Tool for Collaborative Navigation Systems," 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, April 2018, pp. 1455-1464.
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