Scientific paper ID 1886 : 2019/3

Emil Iontchev, Rosen Miletiev, Lachezar Hristov

MEMS sensors are low price products which determines their widespread use in mobile phones, virtual reality, unmanned vehicle, robots and etc. In the same time theirs output signals have a lot of noise components and are unstable over time. One way to make their characteristics better is to combine data from two or more sensors that are mutually complementary. This is usually done using a complementary filter or Kalman filter. The object of this article are algorithms of complementary filters used to determine the angle of rotation of a child seat in a car. The two algorithms are with different complexity. One of them is with a simpler structure and is suitable for embedding in systems realized by microcontrollers.On the other hand the second one has a more complex structure and describes better the physical processes. Our interest is stopped only on the angle of rotation relative to the longitudinal axis of the vehicle, which can be determined using data from only two sensors - an accelerometer and a gyroscope. These two sensors have complementary frequency characteristics - the accelerometer will determine the change of the angle for a long period of time, while the gyro-data will determine its instantaneous value. The filters are implemented in the Matlab environment and their operation is verified with data obtained from static and dynamic real measurements of the deviation of a child seat, mounted in a car.

комплементарен филтър филтър на Калман инерциални сензори Ойлерови ъгли.complementary filter Kalman filter inertial sensors Euler anglesEmil Iontchev Rosen Miletiev Lachezar Hristov


[1] Hofmann-Wellenhof Bernhard, Herbert Lichtenegger, Elmar Wasle, GNSS – Global Navigation Satellite Systems GPS, GLONASS, Galileo, and more, SpringerWienNewYork, , 2008, ISBN 978-3-211-73012-6

[2] Stephen Statler, Beacon Technologies: The Hitchhiker’s Guide to the Beacosystem, Apress, 2016, ISBN-13 (pbk): 978-1-4842-1888-4

[3] David Munoz, Frantz Bouchereau, Cesar Vargas, Rogerio Enriquez, Position Location Techniques and Applications, Elsevier Inc., 2009, ISBN 13: 978-0-12-374353-4

[4] Welch Greg, Gary Bishop, An Introduction to the Kalman Filter, University of North Carolina at Chapel Hill, Department of Computer Science, NC 27599-3175,{welch, gb}

[5] R. Mahony, Tarek Hamel, Jean-Michel Pflimlin. Nonlinear Complementary Filters on the Special Orthogonal Group. IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, 2008, 53 (5), pp.1203-1217. ff10.1109/TAC.2008.923738ff. ffhal-00488376ff

[6] A. Jouybaria, A. A. Ardalana, M-H. Rezvan, Experimental comparison between mahoney and complementary sensor fusion algorithm for attitude determination by raw sensor data of xsens imu on buoy, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-4/W4, 2017 Tehran`s Joint ISPRS Conferences of GI Research, SMPR and EOEC 2017, 7–10 October 2017, Tehran, Iran

[7] Kenneth W. Eure, Cuong Chi Quach, and Sixto L. Vazquez, An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System, NASA/TM–2013-218144, 2019-04-26T09:08:59 00:00Z

[8] Fakhri Alam, Zhou ZhaiHe, Hu JiaJia, A Comparative Analysis of Orientation Estimation Filters using MEMS based IMU, 2nd International Conference on Research in Science, Engineering and Technology (ICRSET’2014), March 21-22, 2014 Dubai (UAE)

[9] Kim Phil, Kalman Filter for Beginners with Matlab Examples, A-JIN Publishing company, 2011, ISBN-13: 978-1463648350

[10] N. L. Pavlov, E. E. Sokolov, M. H. Peychev and D. I. Dacova ,Numerical simulation of free and forced oscillations for pendulum type child travel seat, International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 03, March 2019, pp. 172–177, Article ID: IJMET_10_03_017 Available online at ISSN Print: 0976-6340 and ISSN Online: 0976-6359

[11] Nikolay Pavlov, Evgeni Sokolov, Mihail Peychev, Diana Dacova, Design and test of a tilting seat for improving children’s comfort during traveling, Second International Scientific Conference ITEMA 2018 – Conference Proceedings, ISBN 978-86-80194-13-4, pp 305-312

[12] Iontchev Emil, Rosen Miletiev, Petar Kapanakov, Lachezar Hristov, Sensor data fusion for determine object position, 54th International Scientific Conference on Information, Communication and Energy Systems and Technologies, Ohrid, Macedonia 2019, 26-29 June 2019




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