The Automatic Identification System (AIS) is widely used for reporting vessel movements and broadcasting additional information related to the current voyage or constant parameters like the IMO number or the overall dimension of the hull. Since dynamic AIS data is shared mostly without human interaction, and is not flawless, the static AIS content edited manually is vulnerable to human error. This work introduces a simple vessel motion pattern approach that determines the probable foredeck/afterdeck location of the GNSS reference used by the AIS transponder, and compares it to the hull parameters obtained from the static AIS data, to find observable errors in the static AIS configuration of the mount point of the GNSS reference antenna.

In this paper, we analyze the added value of maritime radar image data for tracking and classification of target vessels. The current automatic radar plotting aid (ARPA) only provides a single point of the acquired radar target. A radar image on the other hand contains two dimensional information on the whole surrounding area as well as the 2D projection of the target itself. The paper starts with a theoretical discussion of possible additional values of using radar image data instead of ARPA based distance and bearing information. In addition, an astrophysical tool is used to extract targets and estimate their minor and major semi-axes of the best fitting ellipse. Finally, we analyze the stability of the ellipsoidal parameters during the tracking of targets. This is done using the Automatic Identification System (AIS) as the primary source of target vessel positioning. With the AIS data it is possible to choose the closest ellipse on the radar image. Repeating this procedure until the AIS target leaves the radar range makes the stability analysis possible.

Abstract Since its deployment in 2004, the Automatic Identification System (AIS) has been considered a significant improvement of watchkeeping duties at sea. According to current regulations, AIS has not been recognised as an approved anticollision instrument yet. However, it would be difficult to rule out a possibility that AIS, being an essential part of the onboard SOLAS — compliant configuration, is unaidedly used for collision avoidance tasks. Recent research activities of DLR's Department of Nautical Systems have shown that AIS transmissions may contain a lot of incomplete data and the system does not have any dependable information on its data integrity. For that reason, the computation of the closest point of approach (CPA) and the time to the CPA (TCPA) are analysed based on AIS data involving multiple vessels, in order to compare the predictions with factual approaches between vessels and to evaluate the usability of AIS data, in its present form, for the appraisal of the traffic situation around each vessel.

This paper introduces the basic concept of the Position Navigation and Timing (PNT) Module as future part of a ship side Integrated Navigation System (INS). Core of the PNT Module is a sensor fusion based processing system (PNT Unit). The paper will focus on important aspects and first results of the initial practical realization of such a PNT Unit, including a realization of a Consistent Common Reference System (CCRS), GNSS/IMU tightly coupled positioning results as well as contingency performance of the inertial sensors.

The standard for interfacing marine electronic devices (NMEA – National Marine Electronics Association), does not provide unambiguous information regarding the reliability of data and its timing. In this paper, time delays in navigational data are investigated. For this purpose AIS and navigational data collected offshore and onshore are used. The investigations are concentrated on lags among various NMEA sentences recorded in a relational database during the survey voyage. The analysis is based on standard elements of descriptive statistics.

This paper studies the performance of pattern matching algorithms with the goal of the detection and tracking of vessel targets in maritime radar images. We compare different methods using a database which consists of radar images from two different manufactures. The data covers a timespan of roughly 4 hours with a one second time resolution. The performance of 3 template matching and 5 feature detector algorithms is tested and the most suitable algorithm is chosen for further optimizations. These optimizations are based on the properties of the radar images and the properties of the radar target.

Abstract Since its introduction the Automatic Identification System (AIS) has played an important part in improving safety at sea, making bridge watchkeeping duties more comfortable and enhancing vessel traffic management ashore. However the analysis of a AIS data set describing the vessel traffic of the Baltic Sea came to conclusion, that specific parameters with relevance to navigation seemed to be defective or implausible. Essentially, it concerned the true heading (THDG) and the rate of turn (ROT) parameters. With the paper we are trying to clarify, which parameters of the AIS position report and to what extent, are affected. The detailed data analysis gives answers on how reliable the AIS data in different traffic areas is.

Starting from the goal developing deterministic realtime applications for high-rate GNSS data this paper shows a number of possible program structures depending on the chosen algorithm complexity using a DLR own software framework. Single-threaded and multi-threaded applications will be compared using a simple example and a real project.

Since its introduction the Automatic Identification System (AIS) has played an important part in improving safety at sea, making bridge watchkeeping duties more comfortable and enhancing vessel traffic management ashore. However the analysis of a AIS data set describing the vessel traffic of the Baltic Sea came to conclusion, that specific parameters with relevance to navigation seemed to be defective or implausible. Essentially, it concerned the true heading (THDG) and the rate of turn (ROT) parameters. With the paper we are trying to clarify, which parameters of the AIS position report and to what extent, are affected. The detailed data analysis gives answers on how reliable the AIS data in different traffic areas is.