MSIS image postioning in port areas with the aid of comparative navigation methods

• Autorzy: Wawrzyniak N. , Stateczny A.
• Języki publikacji: EN

Abstrakty

EN

The article presents a method to determine the position of mechanically scanned sonar images by comparing them with the database of simulated synthetic images. The synthetic images are generated from high-density bathymetric data coming from the same fragment of water region, using the ray tracing method. The article discusses the issues related to the choice of the probability function as the method of image comparing which allows to find the correct georeference of the real image. For the correlation method and the logical conjunction method, which are believed to give the best results, detailed studies were performed, including boundary cases. The obtained results of matching are presented in tabular and graphic form.

Słowa kluczowe

EN

sonar imaging; MSIS sonar; image comparison methods; image simulation

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2017
• Tom: nr 1
• Strony: 32--41
• Opis fizyczny: Bibliogr. 42 poz., rys., tab.

Twórcy

autor

Wawrzyniak N.

• Maritime University Szczecin, Poland

autor

Stateczny A.

• Maritime University Szczecin, Poland

Bibliografia

• 1. Wawrzyniak N., Zaniewicz G., Detecting small moving underwater objects using scanning sonar in waterside surveillance and complex security solutions. Proceedings of the 17th International Radar Symposium (IRS),Krakow, Poland,(2016)
• 2. Ribas D., Ridao P., Neira J.et al. Line extraction from mechanically scanned imaging sonar, 3rd Iberian Conference on Pattern Recognition and Image Analysis. Book Series: Lecture Notes in Computer Science, vol.4477, pp. 322-329, (2007).
• 3. Kazimierski, W., Zaniewicz, G., Analysis of the Possibility of Using Radar Tracking Method Based on GRNN for Processing Sonar Spatial Data, Proceedings of the Joint Rough Set Symposium, Spain, Kryszkiewicz et al. (Eds), Lecture Notes in Artificial Intelligence, 8537, pp. 319-326. Granada and Madrid, (2014).
• 4. Zhang, J., Han, Y., Zheng, C. et al., Underwater target localization using long baseline positioning system. Applied Acoustics, vol. 111, pp. 129-134, (2016).
• 5. Reis, J., Morgado, M., Batista, P. et al., Design and Experimental Validation of a USBL Underwater Acoustic Positioning System. Sensors, vol. 16, issue 9, article number 1491, (2016).
• 6. Naus, K., Nowak, A., The Positioning Accuracy of BAUV Using Fusion of Data from USBL System and Movement Parameters Measurements. Sensors, vol. 16, issue 8, article number 1279, (2016).
• 7. Bell, J. M., Linnett L. M., Simulation and Analysis of Synthetic Sidescan Sonar Images. IEEE Proceedings - Radar, Sonar and Navigation, 144(4), (1997).
• 8. Palczynski, M., Method for generating synthetic sonar images for the purpose of comparative navigation, (Ph. D. thesis), Szczecin University of Technology, (2008).
• 9. Stateczny, A., The neural method of sea bottom shape modelling for the spatial maritime information system. Book Editor(s): Brebbia, CA., Olivella, J. Maritime Engineering and Ports II. Book Series: Water Studies Series vol. 9, pp. 251-259, Barcelona (2000).
• 10. Lubczonek, J., Stateczny, A., Concept of neural model of the sea bottom surface. Book Editor(s): Rutkowski, L., Kacprzyk, J. Neural Networks and Soft Computing, Book Series: Advances in Soft Computing, pp. 861-866, Zakopane (2003).
• 11. Lubczonek, J., Hybrid neural model of the sea bottom surface, Edited by: Rutkowski, L., Siekmann, J., Tadeusiewicz, R. et al., 7th International Conference on Artificial Intelligence and Soft Computing, Lecture Notes in Artificial Intelligence, vol. 3070, pp. 1154-1160, Zakopane, Poland (2004).
• 12. Maleika, W., Moving Average Optimization in Digital Terrain Model Generation Based on Test Multibeam Echosounder Data, Geo-Marine Letters, 35, 61-68, (2015).
• 13. Maleika, W., The Influence of the Grid Resolution on the Accuracy of the Digital Terrain Model Used in Seabed Modelling. Marine Geophysical Research, 36, 35-44, (2015).
• 14. Maleika, W, Palczynski, M., Frejlichowski, D., Effect of Density of Measurement Points Collected from a Multibeam Echosounder on the Accuracy of a Digital Terrain Model, 4th International Scientific Asian Conference on Intelligent Information and Database Systems (ACIIDS), Edited by: Pan, JS., Chen, SM., Nguyen, NT., Book Series: Lecture Notes in Artificial Intelligence, vol. 7198, pp. 456-465, Kaohsiung, Taiwan, (2012).
• 15. Maleika, W., The influence of track configuration and multibeam echosounder parameters on the accuracy of seabed DTMs obtained in shallow water, Earth Science Informatics, vol. 6, issue 2, pp. 47-69, (2013).
• 16. Wawrzyniak, N., Hyla, T., Managing Depth Information Uncertainty in Inland Mobile Navigation Systems. Joint Rough Set Symposium, Granada and Madrid, Spain, Kryszkiewicz et al. (Eds), Lecture Notes in Artificial Intelligence, 8537, pp. 343–350, 2014.
• 17. Ratuszniak, N., Palczynski, M., Method of visualization for scanning sonar image, Measurement Automation and Monitoring vol.56 no 12/2010.
• 18. Stateczny, A., Methods of comparative plotting of the ship’s position. Book Editor(s): Brebbia, CA., Sciutto, G. Maritime Engineering & Ports III. Book Series: Water Studies Series vol. 12, pp. 61-68, Rhodes (2002)
• 19. Stateczny, A., Artificial neural networks for comparative navigation. Book Editor(s): Rutkowski, L., Siekmann, J., Tadeusiewicz, R., et al. Artificial Intelligence and Soft Computing - ICAISC 2004. Book Series: Lecture Notes in Artificial Intelligence, vol. 3070, pp. 1187-1192, Zakopane (2004).
• 20. Kazimierski, W., Stateczny, A., Radar and Automatic Identification System track fusion in an Electronic Chart Display and Information System. Journal of Navigation, vol. 68, pp 1141-1154, 2015.
• 21. Wang, L., Yu, L., Zhu, Y., Construction Method of the Topographical Features Model for Underwater Terrain Navigation. Polish Maritime Research, vol. 22, special issue 1, pp. 121-125, (2015).
• 22. Zhou, L., Cheng, X., Zhu, Y.,Terrain aided navigation for autonomous underwater vehicles with coarse maps. Measurement Science and Technology, vol. 27, issue 9, article number 095002, (2016).
• 23. Miller, P., A., Farrell, J., A., Zhao, Y. et al. Autonomous Underwater Vehicle Navigation, IEEE Journal of Oceanic Engineering, vol. 35, issue 3, special issue, pp. 663-678, (2010).
• 24. Nygren, I., Jansson, M., Terrain navigation for underwater vehicles using the correlator method. IEEE Journal of Oceanic Engineering vol. 29, issue 3, pp. 906-915, (2004).
• 25. Zhou, L., Cheng, X., Zhu, Y. et al. Terrain Aided Navigation for Long-Range AUVs Using a New Bathymetric Contour Matching Method. IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Busan, South Korea, pp. 249-254, (2015).
• 26. Ramesh, R., Jyothi, V., Vedachalam, N. et al. Development and Performance Validation of a Navigation System for an Underwater Vehicle. Journal of Navigation, vol. 69, issue 5, pp. 1097-1113, (2016).
• 27. Hyla, T., Kazimierski, W., Wawrzyniak, N,. Analysis of Radar Integration Possibilities in Inland Mobile Navigation. Proceedings of 16th International Radar Symposium (IRS), International Radar Symposium Proceedings, H. Rohling (Ed.), pp. 864-869, Dresden, Germany (2015).
• 28. Hyla, T., Wawrzyniak, N., Kazimierski, W., Model of Collaborative Data Exchange for Inland Mobile Navigation, Proceedings of Soft Computing in Computer and Information Science Conference, Advances in Intelligent Systems and Computing, vol. 342, pp. 435-444, Miedzyzdroje, (2015)
• 29. Gotlib, D., A Cartographic Presentation Model for Navigation and Location-Based Applications. Joint Symposium of ISPRS Commission IV / AutoCarto Annual Conference. Book Series: International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, vol. 38, part 4, Orlando, (2010).
• 30. Wlodarczyk-Sielicka, M., Stateczny, A., Selection of SOM Parameters for the Needs of Clusterisation of Data Obtained by Interferometric Methods. Proceedings of 16th International Radar Symposium (IRS), International Radar Symposium Proceedings, H. Rohling (Ed.), pp. 1129-1134, Dresden, Germany (2015).
• 31. Wlodarczyk-Sielicka M., Lubczonek J., Stateczny A., Comparison of Selected Clustering Algorithms of Raw Data Obtained by Interferometric Methods Using Artificial Neural Networks. Proceedings of 16th International Radar Symposium (IRS), International Radar Symposium, Krakow, Poland (2016).
• 32. Wlodarczyk-Sielicka M., Stateczny A., Comparison of selected reduction methods of bathymetric data obtained by multibeam echosounder. Proceedings of Baltic Geodesy Congress, Gdansk, Poland (2016).
• 33. Dziubich, T., Szymanski, J., Brzeski, A. et al.Depth Images Filtering in Distributed Streaming. Polish Maritime Research, vol. 23, issue: 2, pp. 91-98, (2016).
• 34. Wlodarczyk-Sielicka, M., Stateczny, A., Clustering Bathymetric Data for Electronic Navigational Charts. The Journal of Navigation vol. 69, issue 5, pp 1143-1153 (2016).
• 35. Hejmanowska B., Kamiński W., Przyborski M., Pyrchla J., Modern remote sensing and the challenges facing education systems in terms of its teaching, 7th International Confrence on Education and New Learning Technologies EDULEARN 15 Barcelona, Spain, Book Series: EDULEARN Proceedings, pp. 6549-6558,(2015).
• 36. Kazimierski, W., Wlodarczyk-Sielicka, M., Technology of Spatial Data Geometrical Simplification in Maritime Mobile Information System for Coastal Waters. Polish Maritime Research,Vol. 23, Issue:3, pp. 3-12, (2016).
• 37. Moszynski, M., Chybicki, A., Kulawiak, M. et al. A novel method for archiving multibeam sonar data with emphasis on efficient record size reduction and storage. Polish Maritime Research, vol. 20, issue 1, pp. 77-86, (2013).
• 38. Stateczny, A., Bodus-Olkowska I., Hierarchical Hydrographic Data Fusion or Precise Port Electronic Navigational Chart Production. in Mikulsk J.(ed.) Telematics in the Transport Environment, Book Series: Communications in Computer and Information Science 471, pp. 359-368, Ustron, Poland (2014).
• 39. Stateczny, A., Bodus-Olkowska, I., Sensor Data Fusion Techniques for Environment Modelling. Proceedings of 16th International Radar Symposium (IRS), International Radar Symposium Proceedings, H. Rohling (Ed.), pp. 11231128, Dresden, Germany (2015).
• 40. Pokonieczny, K., Bielecka, E., Kaminski, P., Analysis of Spatial Distribution of Geodetic Control Points and Land Cover. 14th International Multidisciplinary Scientific Geoconference (SGEM) Geoconference on Informatics, Geoinformatics and Remote Sensing, vol. II, pp. 49-56, Albena, Bulgaria, (2014).
• 41. Burdziakowski, P., Janowski A., Kholodkow A. et al., Maritime Laser Scanning as the Source For Spatial Data, Polish Maritime Research, vol. 22, issue 4, pp. 9-14, (2015).
• 42. Stateczny, A., Wawrzyniak, N., Method for determining stationary position of scanning sonar, involves determining head position based on sonar search for actual sonar image with set of synthetic images generated by performing ray tracing process based on model of bottom. Patent Number: PL406523-A1. Patent Assignee: Marine Technology Sp. z o.o. (2015).

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)