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Concept of AHRS algorithm designed for platform independent IMU attitude alignment

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Nowadays, along with the advancement of technology one can notice the rapid development of various types of navigation systems. So far the most popular satellite navigation, is now supported by positioning results calculated with use of other measurement system. The method and manner of integration will depend directly on the destination of system being developed. To increase the frequency of readings and improve the operation of outdoor navigation systems, one will support satellite navigation systems (GPS, GLONASS ect.) with inertial navigation. Such method of navigation consists of several steps. The first stage is the determination of initial orientation of inertial measurement unit, called INS alignment. During this process, on the basis of acceleration and the angular velocity readings, values of Euler angles (pitch, roll, yaw) are calculated allowing for unambiguous orientation of the sensor coordinate system relative to external coordinate system. The following study presents the concept of AHRS (Attitude and heading reference system) algorithm, allowing to define the Euler angles.The study were conducted with the use of readings from low-cost MEMS cell phone sensors. Subsequently the results of the study were analyzed to determine the accuracy of featured algorithm. On the basis of performed experiments the legitimacy of developed algorithm was stated.
Rocznik
Tom
Strony
33--47
Opis fizyczny
Bibliogr. 22 poz., rys., wykr.
Twórcy
  • Institute of Geodesy, The Faculty of Geodesy, Geospatial and Civil Engineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego St. 1, 10-719, Olsztyn, Poland
autor
  • Institute of Geodesy, The Faculty of Geodesy, Geospatial and Civil Engineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego St. 1, 10-719, Olsztyn, Poland
  • Institute of Geoinformation and Cartography, The Faculty of Geodesy, Geospatial and Civil Engineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego St. 1, 10-719, Olsztyn, Poland
Bibliografia
  • [1] Cui, X., Mei, C., Qin, Y., Yan, G., & Fu, Q. (2017). In-motion alignment for low-cost SINS/GPS under random misalignment angles. Journal of Navigation, 1–17. doi:10.1017/S037346331700039X
  • [2] Emami, M., & Taban, M. R. (2017). A customized H-infinity algorithm for underwater navigation system: With experimental evaluation. Ocean Engineering, 130(Supplement C), 611-619. Retrieved from http://www.sciencedirect.com/science/article/pii/S0029801816305996 doi: https://doi.org/10.1016/j.oceaneng.2016.12.011
  • [3] Farrel, J. A. (2008). Aided navigation GPS with high rate sensors. Mc Graw Hill.
  • [4] Farrell Jay A., J. W. (2017). GNSS/INS Integration. springer handbook of global navigation satellite systems (S. I. Publishing, Ed.). Springer International Publishing.
  • [5] Foxlin, E. (2005). Pedestrian tracking with shoe-mounted inertial sensors. IEEE Comput. Graph. Appl(25(6)), 38-46.
  • [6] Freescale. (2012). Implementing a tilt-compensated eCompass using accelerometer and magnetometer sensors. Freescale Semiconductor Application Note.
  • [7] Groves, D. (2008). Principles of GNSS, inertial, and multisensory integrated navigation systems. Artech House.
  • [8] Henriksson, M. (2013). Estimation of heading using magnetometer and GPS.
  • [9] Li, Z., Wang, J., & Gao, J. (2016). An enhanced GPS/INS integrated navigation system with GPS observation expansion. Journal of Navigation, 69(5), 1041–1060. doi:10.1017/S0373463315001083
  • [10] Nakath David, J. C., & Rachuy, C. (2017). Rigid body attitude control based on a manifold representation of direction cosine matrices. Journal of Physics: Conference Series, 783(1).
  • [11] Noureldin, A., Karamat, T., & J.Georgy. (2013). Fundamentals of inertial navigation, satellitebased positioning and their integration. Springer.
  • [12] Ozyagcilar, T. (2012). Calibrating an ecompass in the presence of hard and soft-iron interference. Freescale Semiconductor.
  • [13] Sabet, M., Daniali, H. M., Fathi, A., & Alizadeh, E. (2017). Experimental analysis of a low-cost dead reckoning navigation system for a land vehicle using a robust AHRS. Robotics and Autonomous Systems, 95(Supplement C), 37-51. Retrieved from http://www.sciencedirect.com/science/article/pii/S0921889016307497 doi: https://doi.org/10.1016/j.robot.2017.05.010
  • [14] Sasani, J. A.-S. A. R., S.and Asgari. (2016, Jan 01). Improving MEMS-IMU/GPS integrated systems for land vehicle navigation applications. GPS Solutions, 20(1), 89–100. Retrieved from https://doi.org/10.1007/s10291-015-0471-3 doi: 10.1007/s10291-015-0471-3
  • [15] Simončič, S., Klobčar, D., & Podržaj, P. (2015). Kalman filter based initial guess estimation for digital image correlation. Optics and Lasers in Engineering, 73(Supplement C), 80 - 88. Retrieved from http://www.sciencedirect.com/science/article/pii/S0143816615000330 doi: https://doi.org/10.1016/j.optlaseng.2015.03.001
  • [16] Tang Daquan, J. C. G., Yongkang Jiao. (2016). On automatic landing system for carrier plane based on integration of INS, GPS and vision. In Navigation and control conference (cgncc).
  • [17] Tomaszewski, D., Rapiński, J., & Śmieja, M. (2015). Projekt oraz pierwsze testy zitegrowanej platformy ewaluacyjnej GPS/INS. Logistyka(3), 46-49.
  • [18] Tomaszewski, D., Rapiński, J., & Śmieja, M. (2015). Analysis of the noise parameters and attitude alignment accuracy of INS conducted with the use of MEMS – based integrated navigation system. Acta Geodynamica et Geomaterialia, 2(12), 197-208.
  • [19] Wang, L., Zhang, Z., & Sun, P. (2015). Sun quaternion-based kalman filter for AHRS using an adaptive-step gradient descent algorithm. International Journal of Advanced Robotic Systems (12).
  • [20] Woodman, O. (2007). An introduction to inertial navigation (Tech. Rep. No. 696). Cambridge.
  • [21] Yadav, N., & Bleakley, C. (2014). Accurate orientation estimation using AHRS under conditions of magnetic distortion. Sensors(14), 20008-20024.
  • [22] Yang Ling, e. a. (2016). Seamless pedestrian navigation augmented by walk status detection and context features. In Ubiquitous positioning, indoor navigation and location based services (upinlbs).
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f797e6d1-501a-4a6b-8761-600f8f68eefd
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