Volume 13, Issue 1 (Journal of Control, V.13, N.1 Spring 2019)                   JoC 2019, 13(1): 47-56 | Back to browse issues page

XML Persian Abstract Print

1- Maleke Ashtar university of technology
Abstract:   (2733 Views)
This paper aims is to design an integrated navigation system constituted by low-cost inertial sensors to estimate the orientation of an Autonomous Underwater Vehicle (AUV) during all phases of under water and surface missions. The proposed approach relied on global positioning system, inertial measurement unit (accelerometer & rate gyro), magnetometer and complementary filter technique. Complementary filter operates based on low pass filter and high pass filter to remove noise and bias error of measurement data in the integrated navigation structure, respectively. Consequently, a relatively accurate orientation estimation is provided for guidance/control system. The most important feature of the proposed approach is the ability of switching between GPS and magnetometer sensor consistent with phase-change in the AUV motion. This brings about more accurate estimation of heading angle in both the surface and underwater phase compared to gyro-based navigation. The performance of the proposed algorithm is assessed in a field test executed on a research AUV and in comparison, with Kalman filter.
Full-Text [PDF 713 kb]   (1202 Downloads)    
Type of Article: Review paper | Subject: Special
Received: 2017/08/7 | Accepted: 2018/05/30 | Published: 2019/07/15

1. [1] Robert Mahony, Tarek Hamel, Jean-Michel P.flimlin "Complementary filter design on the special orthogonal group SO(3)" Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, Seville, Spain, December 12-15, 2005.
2. [2] Antonio Vasilijevic, Bruno Borovic, Zoran Vukic "Underwater Vehicle Localization with Complementary Filter: Performance Analysis in the Shallow Water Environment" J Intell Robot Syst (2012) 68:373-386. [DOI:10.1007/s10846-012-9766-6]
3. [3] Pedro Batista, Carlos Silvestre, and Paulo Oliveira "Sensor-based Complementary Globally Asymptotically Stable Filters for Attitude Estimation" Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference Shanghai, P.R. China, December 16-18, 2009. [DOI:10.1109/CDC.2009.5399810]
4. [4] G. Perez Paina, D. Gaydou, J. Redolfi, C. Paz, and L. Canali "Experimental comparison of Kalman and complementary filter for attitude estimation" Research Centre in Informatics for Engineering (CIII) National Technological University, Cordoba Regional Faculty (UTN-FRC), 09, August, 2016.
5. [5] Chan Gook Park, Chang Ho Kang, Sanghyun Hwang and Chul Joo Chung "An Adaptive Complementary Filter for Gyroscope/ Vision Integrated Attitude Estimation" Int'l J. of Aeronautical & Space Sci. 17(2), 214-221 (2016). [DOI:10.5139/IJASS.2016.17.2.214]
6. [6] Dongwon Jung and Panagiotis Tsiotras "Inertial Attitude and Position Reference System Development for a Small UAV" Georgia Institute of Technology, Atlanta, GA, 30332-0150, 2013.
7. [7] Robert Smith a, b Andy Frostb, Penny Probert "Gyroscopic Data Fusion via a Quaternion Based Complementary Filter" university of Oxford, England. bSilsoe Research Institute, England, 2015.
8. [8] Mark Euston, Paul Coote, Robert Mahony, Jonghyuk Kim and Tarek Hamel "A Complementary Filter for Attitude Estimation of a Fixed-Wing UAV" Intelligent Robots and System, IROS 2008, IEEE/RSJ International Conference. [DOI:10.1109/IROS.2008.4650766]
9. [9] Tae Suk Yoo, Sung Kyung Hong, Hyok Min Yoon and Sungsu Park "Gain-Scheduled Complementary Filter Design for a MEMS Based Attitude and Heading Reference System" Sensors 2011, 11, 3816-3830, 29 March 2011. [DOI:10.3390/s110403816]
10. [10]Walter T.Higgins, JR "A Comparison of Complementary and Kalman Filtering" IEEE Tranactions on Aerospace and Electronic Systems Vol. AES-1 1, NO. 3 MAY 1975. [DOI:10.1109/TAES.1975.308081]
11. [11] Roberto G. Valenti, Ivan Dryanovski and Jizhong Xiao "Keeping a Good Attitude: A Quaternion-Based Orientation Filter for IMUs and MARGs" Sensors 2015, 15, 19302-19330. [DOI:10.3390/s150819302]
12. [12] El Hadri and A. Benallegue "Attitude estimation with gyros-bias compensation using low-cost sensors" Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference Shanghai, P.R. China, December 16-18, 2009. [DOI:10.1109/CDC.2009.5400357]
13. [13] Dung Duong Quoc, Jinwei Sun, Van Nhu Le and Nguyen Ngoc Tan "Sensor Fusion based on Complementary Algorithms using MEMS IMU" International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 8, No. 2 (2015), pp. 313-324. [DOI:10.14257/ijsip.2015.8.2.30]
14. [14] Roberts, Ricky L "Analysis, experimental evaluation, and software upgrade for attitude estimation by the Shallow-Water AUV Navigation System (SANS)" Naval Postgraduate School Monterey, California, March 1997.
15. [15] Val erie Renaudin, Muhammad Haris Afzal, and G' erard Lachapelle "Complete Tri-axis Magnetometer Calibration in the Magnetic Domain" Hindawi Publishing Corporation Journal of Sensors, Volume 2010, Article ID 967245, 10 pages. [DOI:10.1155/2010/967245]
16. [16] li xing, yijum hang, zhi xiong, jianye liu and zhong wan, "accurate attitude estimation using ARS under conditions of vehicle movement based on disturbance acceleration adaptive estimation and correction" sensors 2016. [DOI:10.3390/s16101716]

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.