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

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.

[1]  A. Wojtkiewicz,et al.  The simple method for analysis of nonlinear frequency distortions in FMCW radar , 2000, 13th International Conference on Microwaves, Radar and Wireless Communications. MIKON - 2000. Conference Proceedings (IEEE Cat. No.00EX428).

[2]  W. Kazimierski,et al.  A comparison of the target tracking in marine navigational radars by means of GRNN filter and numerical filter , 2008, 2008 IEEE Radar Conference.

[3]  C. J. Harris,et al.  Comparison of two measurement fusion methods for Kalman-filter-based multisensor data fusion , 2001 .

[4]  J. Lubczonek Application of GIS techniques in VTS radar stations planning , 2008, 2008 International Radar Symposium.

[5]  Krzysztof Kulpa Novel method of decreasing influence of phase noise on FMCW radar , 2001, 2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559).

[6]  Piotr Borkowski,et al.  Ship Course-Keeping Algorithm Based On Knowledge Base , 2011, Intell. Autom. Soft Comput..

[7]  Xinping Yan,et al.  A spatial–temporal forensic analysis for inland–water ship collisions using AIS data , 2013 .

[8]  Andrzej Stateczny,et al.  Aspects of spatial planning of radar sensor network for inland waterways surveillance , 2009, 2009 European Radar Conference (EuRAD).

[9]  A. Wojtkiewicz,et al.  Phase noise in two-dimensional spectrum of video signal in FMCW homodyne radar , 2000, 13th International Conference on Microwaves, Radar and Wireless Communications. MIKON - 2000. Conference Proceedings (IEEE Cat. No.00EX428).

[10]  P. Silveira,et al.  Use of AIS Data to Characterise Marine Traffic Patterns and Ship Collision Risk off the Coast of Portugal , 2013, Journal of Navigation.

[11]  H. Ligteringen,et al.  Study on collision avoidance in busy waterways by using AIS data , 2010 .

[12]  W. Kazimierski,et al.  Determining manoeuvre detection threshold of GRNN filter in the process of tracking in marine navigational radars , 2008, 2008 International Radar Symposium.

[13]  Vyacheslav Tuzlukov Signal Processing in Radar Systems , 2012 .

[14]  Andrzej Stateczny,et al.  Multisensor Tracking of Marine Targets - Decentralized Fusion of Kalman and Neural Filters , 2011 .

[15]  V. Vaidehi,et al.  IMM-UKF-TFS Model-based Approach for Intelligent Navigation , 2013 .

[16]  Phil F. Culverhouse,et al.  Interval Kalman filtering in navigation system design for an uninhabited surface vehicle , 2013 .

[17]  Natalia Wawrzyniak,et al.  Exchange of Navigational Information between VTS and RIS for Inland Shipping User Needs , 2014, TST.

[18]  Natalia Wawrzyniak,et al.  Managing Depth Information Uncertainty in Inland Mobile Navigation Systems , 2014, RSEISP.

[19]  Li Li,et al.  XNAV/CNS Integrated Navigation Based on Improved Kinematic and Static Filter , 2013, Journal of Navigation.

[20]  Krzysztof Kulpa,et al.  Focusing range image in VCO based FMCW radar , 2003, 2003 Proceedings of the International Conference on Radar (IEEE Cat. No.03EX695).

[21]  Piotr Borkowski,et al.  Data fusion in a navigational decision support system on a sea-going vessel , 2012 .

[22]  Marta Wlodarczyk-Sielicka,et al.  Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process , 2014, RSEISP.

[23]  Witold Kazimierski,et al.  Optimization of multiple model neural tracking filter for marine targets , 2012, 2012 13th International Radar Symposium.

[24]  James Llinas,et al.  Handbook of Multisensor Data Fusion : Theory and Practice, Second Edition , 2008 .

[25]  Andrzej Stateczny Neural Manoeuvre Detection of the Tracked Target in ARPA Systems , 2001 .

[26]  Toke Koldborg Jensen,et al.  Empirical Ship Domain based on AIS Data , 2013, Journal of Navigation.

[27]  Huanxin Zou,et al.  Ship Surveillance by Integration of Space-borne SAR and AIS – Further Research , 2013, Journal of Navigation.

[28]  John B. Hooper,et al.  The AIS-Assisted Collision Avoidance , 2009, Journal of Navigation.

[29]  Andrzej Stateczny,et al.  Radar sensors implementation in river information services in Poland , 2014, 2014 15th International Radar Symposium (IRS).

[30]  Witold Kazimierski Problems of data fusion of tracking radar and AIS for the needs of integrated navigation systems at sea , 2013, 2013 14th International Radar Symposium (IRS).

[31]  Andrzej Stateczny,et al.  Sensor data fusion in inland navigation , 2013, 2013 14th International Radar Symposium (IRS).

[32]  Lars Linsen,et al.  Comprehensive Analysis of Automatic Identification System (AIS) Data in Regard to Vessel Movement Prediction , 2014 .

[33]  W. Kazimierski,et al.  Verification of multiple model neural tracking filter with ship's radar , 2012, 2012 13th International Radar Symposium.

[34]  Hao Wei,et al.  Error Analysis of Multi-Sensor Data Fusion System for Target Detection on The Ocean Surface , 2006, 2006 IEEE International Conference on Information Acquisition.

[35]  Witold Kazimierski,et al.  Analysis of the Possibility of Using Radar Tracking Method Based on GRNN for Processing Sonar Spatial Data , 2014, RSEISP.

[36]  Stephan Matzka,et al.  A comparison of track-to-track fusion algorithms for automotive sensor fusion , 2008, 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.