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On PNT Integrity in Snapshot And Recursive Positioning Algorithms for Maritime Applications

Lanca, Luis and Romanovas, Michailas and Ziebold, Ralf (2015) On PNT Integrity in Snapshot And Recursive Positioning Algorithms for Maritime Applications. ECTRI Young Researchers Seminar 2015, 2015-06-17 - 2015-06-19, Rome, Italy.

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Resilient provision of Position Navigation and Time (PNT) data is a strategic key element of the e-Navigation strategy, developed by the International Maritime Organization (IMO). The improvement and the indication of reliability have been identified as high level user need with respect to PNT data supplied by electronics means. IMO as developed a maritime PNT system concept aiming to improve the resilience and reliability of PNT data provision during berth-to-berth navigation. The maritime PNT System comprises several structural components, where Global Navigation Satellite Systems (GNSS), have become the primary component to produce position, velocity and time information for maritime applications. For a comprehensive onboard provision of PNT data as well as to compensate the vulnerability of GNSS, further onboard sensors are needed. The PNT system is responsible for the fusion of the data provided by all the available onboard sensors and data integrity monitoring functions. A unit composed by several sensors of different classes improves the resilience of the system. DLR has developed a prototype of an onboard PNT unit and several measurement campaigns have been performed. This paper concentrates on integrity monitoring (IM) for navigation systems based on sensor fusion. IM is a mechanism that protects the user from large position and velocity errors in the presence of failures or non-scheduled events in a timely fashion. It can be seen as an instantaneous decision criterion for using or not the system and therefore constitutes a key function for the safety of navigation. The IM includes the detection and exclusion functions, they are responsible for detecting the measurements errors (faults) and exclude them from the PNT data computation algorithm. This work presents a systematic analysis of Fault Detection and Exclusion (FDE) algorithms in representative single and multi-sensor. More specifically, a pure GNSS-based snapshot weighted iterative least-square (WLS) solution is compared to a classical error-state Extended Kalman Filter (EKF) for a combined GNSS/IMU system with Euler angles for attitude parameterization. The outlier detection functionality is implemented for both pseudorange and Doppler shift observations in order to ensure the integrity of the estimated position and velocity data. The work confirms the superiority of the recursive Bayesian scheme over a snapshot algorithm in terms of the outlier detection performance. This can be explained by the recursive structure of the estimator, where the dynamical model of the system provides the additional source of information, which increases the system’s redundancy and hence improves the performance of the FDE schemes.

Item URL in elib:https://elib.dlr.de/98035/
Document Type:Conference or Workshop Item (Speech)
Title:On PNT Integrity in Snapshot And Recursive Positioning Algorithms for Maritime Applications
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Date:June 2015
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:Integrated Navigation Sensors, Kalman Filtering, Integrity Monitoring, GNSS, Inertial Sensors
Event Title:ECTRI Young Researchers Seminar 2015
Event Location:Rome, Italy
Event Type:international Conference
Event Start Date:17 June 2015
Event End Date:19 June 2015
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Automated Aids for Safe and Efficient Vessel Traffic Process (old)
Location: Neustrelitz
Institutes and Institutions:Institute of Communication and Navigation > Nautical Systems
Deposited By: Romanovas, Michailas
Deposited On:08 Sep 2015 14:03
Last Modified:24 Apr 2024 20:03

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