Laser range measurement filtration for PNDS purposes

• Autorzy: Zalewski P. , Tomczak A.
• Języki publikacji: EN

Abstrakty

EN

PNDS (Pilot Navigation and Docking System) [1] utilizes the range measurement between laser head and ship’s side to determine the ship’s outline presented on the screen. The noisy measurements and dynamic process noise affect the accuracy of determined parameters and propagate to ship’s heading and position. To improve the performance of PNDS system there was a need to apply the data filtering technique. In the paper the theoretical basis and algorithm of discrete Kalman filter designed for range optimal estimation in PNDS were described. The real data collected during berthing operation of motor vessel Navigator XXI were filtered and compared to row unfiltered data. The conclusions contain evaluation of filter capabilities and its potential application in PNDS system.

Słowa kluczowe

EN

Kalman filtration; state vector estimation; range measurement; laser range; docking system

• Wydawca: Wydawnictwo Naukowe Akademii Morskiej w Szczecinie
• Czasopismo: Zeszyty Naukowe / Akademia Morska w Szczecinie
• Rocznik: 2012
• Tom: nr 32 (104) z. 2
• Strony: 182--185
• Opis fizyczny: Bibliogr. 5 poz., rys.

Twórcy

autor

Zalewski P.

autor

Tomczak A.

• Maritime University of Szczecin, Institute of Marine Traffic Engineering 70-500 Szczecin, ul. Wały Chrobrego 1–2,

Bibliografia

• 1. BĄK A.: Zintegrowany system wizualizacji parametrów nawigacyjnych w PNDS. Proceedings of 14th International Scientific and Technical Conference on Marine Traffic Engineering, Edited by L. Gucma, Świnoujście, 12–14 Oct., Maritime University of Szczecin, 2011.
• 2. KALMAN R.: A New Approach to Linear Filtering and Prediction Problems. Transactions of the ASME, Journal of Basing Engineering, vol. 82, March 1960, 34–35.
• 3. SIMONS D.: Kalman Filtering with State Constraints: A Survey of Linear and Nonlinear Algorithms. Cleveland State University Department of Electrical and Computer Engineering, IET Control Theory & Applications, 2009.
• 4. WELCH G., BISHOP G.: An Introduction to the Kalman Filter. Transactions 95-041, Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599-3175, 2002.
• 5. ZALEWSKI P.: Modele z filtrem Kalmana i rozmyte w systemach dynamicznego pozycjonowania. I Międzynarodowa Konferencja Naukowo-Techniczna „Górnictwo morskie surowcową szansą przyszłych pokoleń”, AGH, Górnictwo i Geoinżynieria, rok 35, zeszyt 4/1, Kraków 2011.