scholarly journals Automatic Identification System (AIS) Dynamic Data Integrity Monitoring and Trajectory Tracking Based on the Simultaneous Localization and Mapping (SLAM) Process Model

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8430
Author(s):  
Krzysztof Jaskólski ◽  
Łukasz Marchel ◽  
Andrzej Felski ◽  
Marcin Jaskólski ◽  
Mariusz Specht
Keyword(s):  
Process Model ◽  
Dead Reckoning ◽  
Simultaneous Localization And Mapping ◽  
Process Models ◽  
Automatic Identification ◽  
Identification System ◽  
Dynamic Data ◽  
Integrity Monitoring ◽  
Automatic Identification System ◽  
Localization And Mapping

To enhance the safety of marine navigation, one needs to consider the involvement of the automatic identification system (AIS), an existing system designed for ship-to-ship and ship-to-shore communication. Previous research on the quality of AIS parameters revealed problems that the system experiences with sensor data exchange. In coastal areas, littoral AIS does not meet the expectations of operational continuity and system availability, and there are areas not covered by the system. Therefore, in this study, process models were designed to simulate the tracking of vessel trajectories, enabling system failure detection based on integrity monitoring. Three methods for system integrity monitoring, through hypotheses testing with regard to differences between model output and actual simulated vessel positions, were implemented, i.e., a Global Positioning System (GPS) ship position model, Dead Reckoning and RADAR Extended Kalman Filter (EKF)—Simultaneous localization and mapping (SLAM) based on distance and bearing to navigational aid. The designed process models were validated on simulated AIS dynamic data, i.e., in a simulated experiment in the area of Gdańsk Bay. The integrity of AIS information was determined using stochastic methods based on Markov chains. The research outcomes confirmed the usefulness of the proposed methods. The results of the research prove the high level (~99%) of integrity of the dynamic information of the AIS system for Dead Reckoning and the GPS process model, while the level of accuracy and integrity of the position varied depending on the distance to the navigation aid for the RADAR EKF-SLAM process model.

scholarly journals Information unfitness as a factor constraining Automatic Identification System (AIS) application to anti-collision manoeuvring

2012 ◽  
Vol 19 (3) ◽  
pp. 60-64 ◽  
Author(s):  
Andrzej Felski ◽  
Krzysztof Jaskólski
Keyword(s):  
Decision Making ◽  
Collision Avoidance ◽  
Significant Role ◽  
Technical Specification ◽  
Supplementary Information ◽  
Automatic Identification ◽  
Identification System ◽  
Radar Measurement ◽  
Dynamic Data ◽  
Automatic Identification System

ABSTRACT Common use of shipboard AIS creates conditions for the use of a new kind of dynamic data in the situation of the risk of collision. AIS position report is a source of supplementary information derived from error leveraged radar measurement. However, in view of the results of the studies there are opinions with regard to inconsistent AIS dynamic data in the process of decision-making by the officer of the watch. By taking into consideration the recordings of the studies and technical specification of AIS it can be concluded that the results of inconsistent data have significant role in collision avoidance manoeuvring.

scholarly journals Automatic Identification System (AIS) dynamic data estimation based on discrete Kalman Filter (KF) algorithm

2017 ◽  
pp. 1-1 ◽  
Author(s):  
Krzysztof Jaskólski
Keyword(s):  
Kalman Filter ◽  
Motion Tracking ◽  
Data Availability ◽  
Automatic Identification ◽  
Identification System ◽  
Data Link ◽  
Dynamic Data ◽  
Automatic Identification System ◽  
Safety Reason ◽  
Limit Probability

Due to the safety reason, the ship movement on the littoral area should be monitored, tracked, recorded and stored. Automatic Identification System (AIS) is the perfect tool to ensure this requirement. The limit probability for the AIS dynamic data availability can be limited by the lack of Global Position System (GPS) signal, heading (HDG) and rate of turn (ROT) data in position report. Availability of data link is an additional limitation. For this purpose, it is possible to attach the Discrete Kalman filter (KF) for the position, and course estimation. Coordinate estimation in the absence of a transmission link can improve the quality of AIS service at Vessel Traffic Service (VTS) stations. This article presents Kalman filtering algorithm to improve the possibilities of ship motion tracking and monitoring in the TSS (Traffic Separation Scheme) and fairways area. Only 39 iterations were presented to familiarize how the Kalman filter algorithm works. The archival data from 2006 were used deliberately. During that time, there were problems with the AIS availability service. With the use of measurements series from those years, it is easier to observe the effectiveness of Kalman filter in absence of AIS data.

Automatic Identification System Receiver for Small Fishing Vessels

2020 ◽  
Author(s):  
Febus Reidj G. Cruz ◽  
Jeremiah A. Ordiales ◽  
Malvin Angelo C. Reyes ◽  
Pinky T. Salvanera
Keyword(s):  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Fishing Vessels

Automatic identification system data-driven model for analysis of ship domain near bridge-waters

2021 ◽  
pp. 1-22
Author(s):  
Lei Jinyu ◽  
Liu Lei ◽  
Chu Xiumin ◽  
He Wei ◽  
Liu Xinglong ◽  
...  
Keyword(s):  
Least Squares Method ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Automatic Identification System ◽  
Domain Models ◽  
System Data ◽  
Quantification Model ◽  
Highly Correlated

Abstract The ship safety domain plays a significant role in collision risk assessment. However, few studies take the practical considerations of implementing this method in the vicinity of bridge-waters into account. Therefore, historical automatic identification system data is utilised to construct and analyse ship domains considering ship–ship and ship–bridge collisions. A method for determining the closest boundary is proposed, and the boundary of the ship domain is fitted by the least squares method. The ship domains near bridge-waters are constructed as ellipse models, the characteristics of which are discussed. Novel fuzzy quaternion ship domain models are established respectively for inland ships and bridge piers, which would assist in the construction of a risk quantification model and the calculation of a grid ship collision index. A case study is carried out on the multi-bridge waterway of the Yangtze River in Wuhan, China. The results show that the size of the ship domain is highly correlated with the ship's speed and length, and analysis of collision risk can reflect the real situation near bridge-waters, which is helpful to demonstrate the application of the ship domain in quantifying the collision risk and to characterise the collision risk distribution near bridge-waters.

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