Abstract
Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especially true for applications dealing with highly automatic or even autonomous driving. Subsequently, multi-sensor platforms including laser scanners and cameras, as well as map data are used to enhance the navigation performance, namely in accuracy, integrity, continuity and availability. Although well-established procedures for integrity monitoring exist for aircraft navigation, for sensors and fusion algorithms used in automotive navigation, these concepts are still lacking. The research training group i.c.sens, integrity and collaboration in dynamic sensor networks, aims to fill this gap and to contribute to relevant topics. This includes the definition of alternative integrity concepts for space and time based on set theory and interval mathematics, establishing new types of maps that report on the trustworthiness of the represented information, as well as taking advantage of collaboration by improved filters incorporating person and object tracking. In this paper, we describe our approach and summarize the preliminary results.
Highlights
The requirements for the navigational information described in terms of accuracy, integrity, continuity and availability have grown considerably in recent years in Sensors 2018, 18, 2400; doi:10.3390/s18072400 www.mdpi.com/journal/sensorsSensors 2018, 18, 2400 order to ensure safe navigation
Within the research training group, in total, nine individual PhD projects are carried out focusing on aspects of integrity and collaboration in dynamic sensor networks
Interval-based approaches and set theory are alternatives to derive integrity measures that do not suffer from assumptions about probability distributions and that intrinsically have an error propagation different from quadratic variance propagation [55]
Summary
The requirements for the navigational information (position, velocity, attitude and time) described in terms of accuracy, integrity, continuity and availability have grown considerably in recent years in Sensors 2018, 18, 2400; doi:10.3390/s18072400 www.mdpi.com/journal/sensorsSensors 2018, 18, 2400 order to ensure safe navigation. The requirements for the navigational information (position, velocity, attitude and time) described in terms of accuracy, integrity, continuity and availability have grown considerably in recent years in Sensors 2018, 18, 2400; doi:10.3390/s18072400 www.mdpi.com/journal/sensors. One of the key features for future autonomous systems is a guarantee of integrity, i.e., to warn the user in a timely manner when a predefined threshold (alert limit) is transgressed [1]. Integrity concepts have been developed and used primarily in aviation for GPS-based navigation [2,3]); an overview of studies for integrity in urban areas is given in [4]. One established solution to evaluate the integrity risk is Receiver Autonomous Integrity Monitoring (RAIM); cf [5,6]. Diversified observation configurations or sensor systems are considered, which independently enable a state estimation. Another partially independent source of information can be used to increase integrity [9,10], but generally, the map itself has nowadays no dedicated integrity information
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