Inertial sensors applications in underwater measurements

• Autorzy: Bikonis K. , Demkowicz J.
• Języki publikacji: EN

Abstrakty

EN

Over the past decades microelectromechanical systems (MEMS) researchers have demonstrated a number of microsensors for almost every possible sensing modality, including attitudes. Current MEMS inertial measurement units (IMU) come in many shapes, sizes, and costs — depending on the application, and performance required. MEMS sensors have proved and demonstrated performance exceeding those of their macroscale counterpart sensors. In the paper chosen IMU applications in underwater measurements are presented. First, for reduction of instability of the underwater sensor during measurements, like multibeam echosounder system (MBES), where the MEMS parameters’ quality are crucial for further MBES record-processing. Second, in underwater navigation systems, for determining the position of underwater vehicles, like Remotely Operated Vehicles (ROV) and, more recently, Autonomous Underwater Vehicle (AUV) or to improve other positioning methods.

Słowa kluczowe

EN

inertial measurements unit (IMU); inertial navigation system (INS); underwater navigation system

• Wydawca: Polskie Towarzystwo Akustyczne. Oddział Gdański
• Czasopismo: Hydroacoustics
• Rocznik: 2017
• Tom: Vol. 20
• Strony: 13--18
• Opis fizyczny: Bibliogr. 9 poz., rys.

Twórcy

autor

Bikonis K.

• Gdansk University of Technology Gdansk, Narutowicza str. 11/12, Poland

autor

Demkowicz J.

• Gdansk University of Technology Gdansk, Narutowicza str. 11/12, Poland

Bibliografia

• [1] R. Feliz, E. Zalama, J. G. Garcia-Bermejo, Pedestrian cracking using inertial sensors. Journal of Physical Agents, Vol. 3 (No. 1), 2009.
• [2] J. Demkowicz, K. Bikonis, MEMS technology quality requirements as applied to multibeam echosounder, Hydroacoustics, Vol. 19, 75-82, 2016.
• [3] K. Bikonis, J. Demkowicz, Data Integration from GPS and Inertial Navigation Systems for Pedestrians in Urban Area, International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 7 (No. 3), 401-406, 2013.
• [4] K. Bikonis, J. Demkowicz, A. Stepnowski, Integration of inertial sensors and GPS system data for underwater navigation, Hydroacoustics vol. 15, 21-26, 2012.
• [5] Ch. Ling, H. Housheng,IMU/GPS Based Pedestrian Localization. 2012 4th Computer Science and Electronic Engineering Conference (CEEC). University of Essex, 2012.
• [6] S. Leutenegger, R. Y. Siegwart, A Low-Cost and Fail-Safe Inertial Navigation System for Airplanes. 2012 IEEE Conference on Robotics and Automation, 2012.
• [7] J. Kedzierski, Filtr Kalmana - zastosowania w prostych ukladach sensorycznych, Wroclaw, Koło Naukowe Robotykow KoNaR, Politechnika Wroclawska, 2007.
• [8] G. Pengfei, T. Liqiong, M Subhas, MEMS Based IMU for Tilting Measurement: Comparison of Complementary and Kalman Filter Based Data Fusion, 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA), 2015.
• [9] F. Aghili, CH. Y. Su, Robust Relative Navigation by Integration of ICP and Adaptive Kalman Filter Using Laser Scanner and IMU, IEEE/ASME Transactions on Mechatronics vol. 21 (No. 4), 2016.

Uwagi

PL

Opracowanie w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).