Radar and Automatic Identification System Track Fusion in an Electronic Chart Display and Information System

Abstract

This paper presents the results of research on the fusion of tracking radar and an Automatic Identification System (AIS) in an Electronic Chart Display and Information System (ECDIS). First, the concept of these systems according to the International Maritime Organization (IMO) is described, then a set of theoretical information on radar tracking and the fusion method itself is given and finally numerical results with real data are presented. Two methods of fusion, together with their parameters, are examined. A proposal for calculating the covariance matrix for radar and AIS data is also given, and the paper ends with conclusions.

MSIS Image Postioning in Port Areas with the Aid of Comparative Navigation Methods

“…The comparative navigation methods have been mainly used, so far, for positioning with the aid of a radar and electronic navigation maps [18][19][20], although in recent years the comparison methods are becoming more and more frequently used in underwater positioning [21][22][23][24][25][26]. The research direction which has recently been very popular in this area refers to mobile navigation [27][28][29].…”

Technology of Spatial Data Geometrical Simplification in Maritime Mobile Information System for Coastal Waters

“…The issue common for all conventional and non-conventional systems is the requirement of real-time presentation of dynamical data, which requires separate algorithms for data quality control and uncertainty management [15,16].…”

Validation of Radar Image Tracking Algorithms with Simulated Data

“…The matter of AIS and radar fusion was mainly addressed for anomaly detection, e.g., based on multi hypothesis tests in Guerriero, Willett, Coraluppi, and Carthel (2008) or by exploiting historical traffic route knowledge for SAR/AIS fusion in Mazzarella and Vespe (2015). In Kazimierski and Stateczny (2015) an overview was given for different AIS/radar fusion techniques incorporating online covariance estimation. In and Siegert, Banyś, Hoth, and Heymann (2017), implementations of IMM-MSPDA and IMM-JPDA…”