طراحی و پیاده‌سازی یک الگوریتم تعیین توجیه (AHRS) مستقل بر‌مبنای حسگرهای میکروالکترومکانیکی برای شرایط دینامیک بالا در سامانه های ناوبری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه ژئودزی دانشگاه آزاد اسلامی واحد تهران شمال

2 دانشگاه آزاد اسلامی واحد تهران شمال

چکیده

در سامانه‌های ناوبری اینرسی، تعیین زوایای توجیه سطوح دَوار با انتگرال‌گیری از مشاهدات ژیروسکوپ‌ها انجام می‌گیرد. ژیروسکوپ‌های مکانیکی که به شکل سنتی برای این منظور مورداستفاده قرار می‌گیرند، قیمت، ابعاد و وزن بسیار زیادی دارند که این موضوع، استفاده از آن‌ها را محدود می‌کند. با پیدایش حسگرهای میکروالکترومکانیکی (MEMS)، این محدودیت‌ها به شکل قابل‌توجهی کاهش یافته است، امروزه این حسگرها در اغلب تلفن‌های همراه هوشمند وجود دارد. بااین‌حال، این حسگرها دقت بسیار کمتری از انواع مکانیکی دارند. به‌خصوص ژیروسکوپ‌های MEMS خطای تجمعی بزرگی دارند که باعث می‌شود، خطای زوایای توجیه به شکل جمع‌شونده در طول زمان افزایش یابد و پس از مدتی غیرقابل استفاده شود. برای حل این مشکل، از مشاهدات شتاب‌سنج‌ها برای محاسبة زوایای تراز (رول و پیچ) و از مغناطیس‌سنج‌ها برای محاسبة زاویة آزیموت (یاو) استفاده می‌شود. اما در این روش، دقت سیستم تحت‌تأثیر شتاب‌های خارجی و اغتشاشات مغناطیسی دچار اختلال ‌می‌شود. در این پژوهش، به معرفی یک فیلتر مکمل ‌پرداخته خواهد شد که با تلفیق دو روش مزبور، یک جواب بهینه با دقت کوتاه‌مدت و بلندمدت مناسب فراهم ‌می‌کند. نتایج آزمایش‌های میدانی انجام‌شده به­وسیلة حسگرهای MEMS یک تلفن همراه هوشمند نشان می‌دهند که حتی در حرکاتی با تغییرات دینامیکی بسیار بالا و طولانی، دقت زوایای تراز حدود 2 درجه، و زاویة آزیموت حدود 4 درجه خواهد بود که نسبت به روش‌های قدیمی، بسیار بهتر و پایدارتر است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Designing and Implementing a Standalone MEMS-Based AHRS Algorithm for High-Dynamics Circumstances on navigation systems

نویسندگان [English]

  • Hanieh Elmi Aziz 1
  • Afshin Mohseni Arasteh 2
1 Islamic Azad University, North Tehran Branch
2 , Islamic Azad university., North Tehran Branch
چکیده [English]

In Inertial Navigation Systems (INS), orientation angles are computed via integrating the gyroscopes data. Traditionally, this is done using mechanical gyros of which cost, size, and weight are the limiting factors for their utilization. However, with the advent of Micro-Electro-Mechanical-Systems (MEMS), these limitations have been mitigated significantly, to a degree that most of the modern smart phones today have these sensors onboard. Nevertheless, these sensors provide far less accuracy compared to their mechanical counterparts. Particularly, MEMS gyros collect significant amounts of accumulating error over time, which makes their results unusable after a short period of time. To overcome this problem, data from accelerometers (for Roll and Pitch angles) and magnetometers (for Yaw angle) are also utilized. These external data are fused with that of the gyros in order to control the errors thereof. But the results are vulnerable to the accelerations applied to the platform in the highly dynamic movements. In this research, a new Attitude and Heading Reference System (AHRS) is introduced which uses a complementary filter to fuse the abovementioned approaches based on their characteristics. The results from the field tests (which are conducted via smartphone data) imply that even during the roughest movements, this technique yields an accuracy of about 2 degrees for Roll and Pitch, and 4 degrees for Yaw. These numbers are very promising compared to the traditional approaches that are inferior in all situations, especially under high-dynamic movements.

کلیدواژه‌ها [English]

  • Inertial Measurement Unit (IMU)
  • Micro-Electro-Mechanical System (MEMS)
  • Inertial Navigation System (INS)
  • Attitude and Heading Reference System (AHRS)
  • Complementary Filter

مراجع

  1. Hristov B. Attitude and Heading Reference System for Unmanned Aerial Vehicles. InCyber-Physical Systems for Social Applications 2019 (pp. 340-364). IGI Global.
  2. Gebre-Egziabher D, Hayward RC, Powell JD. A low-cost GPS/inertial attitude heading reference system (AHRS) for general aviation applications. InIEEE 1998 Position Location and Navigation Symposium (Cat. No. 98CH36153) 1996 Apr 20 (pp. 518-525). IEEE.
  3. Hayward RC, Gebre-Egziabher D, Schwall M, Wilson J, Powell JD. Inertially aided GPS based attitude heading reference system (AHRS) for general aviation aircraft. In :Proceedings of the 10th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 1997); 1997 Sep 19. p. 289-98.
  4. Hayward R, Marchick A, Powell JD. Single baseline GPS based attitude heading reference system (AHRS) for aircraft applications. InProceedings of the 1999 American Control Conference (Cat. No. 99CH36251) ;1999 Jun 2. IEEE;1999. Vol. 5. p. 3655-9.
  5. Wendel J, Meister O, Schlaile C, Trommer GF. An integrated GPS/MEMS-IMU navigation system for an autonomous helicopter. Aerospace science and technology. 2006 Sep 1;10(6):527-33.
  6. Sabet MT, Daniali HM, Fathi A, Alizadeh E. A low-cost dead reckoning navigation system for an AUV using a robust AHRS: Design and experimental analysis. IEEE Journal of Oceanic Engineering. 2017 Dec 4;43(4):927-39.
  7. Armstrong B, Wolbrecht E, Edwards DB. AUV navigation in the presence of a magnetic disturbance with an extended Kalman filter. InOCEANS'10 IEEE SYDNEY 2010 May 24 (pp. 1-6). IEEE.
  8. Guoqing Z, Tao L. Bio-inspired autonomous navigation system for logistics mobile robots with inertial AHRS. In2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference (ITOEC) 2017 Oct 3 (pp. 971-975). IEEE.
  9. Wang K, Liu YH, Li L. A simple and parallel algorithm for real-time robot localization by fusing monocular vision and odometry/AHRS sensors. IEEE/ASME Transactions On Mechatronics. 2014 Jan 23;19(4):1447-57.
  10. Markov A. Autonomous Strapdown Attitude and Heading Reference System for a Small Agile UAV. In2020 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS) 2020 May 25 (pp. 1-3). IEEE.
  11. Euston M, Coote P, Mahony R, Kim J, Hamel T. A complementary filter for attitude estimation of a fixed-wing UAV. In2008 IEEE/RSJ international conference on intelligent robots and systems 2008 Sep 22 (pp. 340-345). IEEE.
  12. Oh AS. A Study on MTL Device Design and Motion Tracking in Virtual Reality Environments. Journal of information and communication convergence engineering. 2019;17(3):205-12.
  13. Abbate N, Basile A, Brigante C, Faulisi A. Development of a MEMS based wearable motion capture system. In2009 2nd Conference on Human System Interactions 2009 May 21 (pp. 255-259). IEEE.
  14. Naeemabadi M, Dinesen B, Najafi S, Thøgersen M, Hansen J. Feasibility of employing AHRS algorithms in the real-time estimation of sensor orientation using low-cost and low sampling rate wearable sensors in IoT application. In2018 IEEE 8th International Conference on Consumer Electronics-Berlin (ICCE-Berlin) 2018 Sep 2 (pp. 1-6). IEEE.
  15. Li Y, Efatmaneshnik M, Dempster AG. Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications. GPS solutions. 2012 Jan 1;16(1):41-52.
  16. Da R. Investigation of a low-cost and high-accuracy GPS/IMU system. InProceedings of the 1997 National Technical Meeting of The Institute of Navigation 1997 Jan 16 (pp. 955-963).
  17. Cohen CE, Parkinson BW, McNally BD. Flight tests of attitude determination using GPS compared against an inertial navigation unit. Navigation. 1994 Mar;41(1):83-97.
  18. Lee B, Lee YJ, Sung S. Attitude Determination Algorithm based on Relative Quaternion Geometry of Velocity Incremental Vectors for Cost Efficient AHRS Design. International Journal of Aeronautical and Space Sciences. 2018 Jun;19(2):459-69.
  19. Geiger W, Bartholomeyczik J, Breng U, Gutmann W, Hafen M, Handrich E, Huber M, Jackle A, Kempfer U, Kopmann H, Kunz J. MEMS IMU for ahrs applications. InProceedings of IEEE/ION PLANS 2008 2008 May 8 (pp. 225-231).
  20. Herberth U, Rende J, Lutz H. Development of Inertial Sensors for AHRS considering DO-254. In2018 DGON Inertial Sensors and Systems (ISS) 2018 Sep 11 (pp. 1-19). IEEE.
  21. Yadav N, Bleakley C. Accurate orientation estimation using AHRS under conditions of magnetic distortion. Sensors. 2014 Nov;14(11):20008-24.
  22. Farrell J. Aided navigation: GPS with high rate sensors. McGraw-Hill, Inc.; 2008 Mar 25.
  23. Yang YC, inventor. Method and apparatus for adaptive filter based attitude updating. United States patent application US 11/107,085. 2005 Oct 27.
  24. Maliňák P, Soták M, Kaňa Z, Baránek R, Duník J. Pure-inertial AHRS with adaptive elimination of non-gravitational vehicle acceleration. In2018 IEEE/ION Position, Location and Navigation Symposium (PLANS) 2018 Apr 23 (pp. 696-707). IEEE.
  25. Finlay CC, Maus S, Beggan CD, Bondar TN, Chambodut A, Chernova TA, Chulliat A, Golovkov VP, Hamilton B, Hamoudi M, Holme R. International geomagnetic reference field: the eleventh generation. Geophysical Journal International. 2010 Dec 1;183(3):1216-30.
  26. Jekeli C. Inertial navigation systems with geodetic applications. Walter de Gruyter; 2012 Oct 25.
  27. Collinson RP. Introduction to avionics. Springer Science & Business Media; 2012 Dec 6.
  28. Lai YC, Jan SS, Hsiao FB. Development of a low-cost attitude and heading reference system using a three-axis rotating platform. Sensors. 2010 Apr;10(4):2472-91.
  29. Kok M, Hol JD, Schön TB. Using inertial sensors for position and orientation estimation. arXiv preprint arXiv:1704.06053. 2017 Apr 20.
  30. Kok M, Schön TB. A fast and robust algorithm for orientation estimation using inertial sensors. IEEE Signal Processing Letters. 2019 Sep 26;26(11):1673-7.
  31. Islam T, Islam MS, Shajid-Ul-Mahmud M, Hossam-E-Haider M. Comparison of complementary and Kalman filter based data fusion for attitude heading reference system. In: AIP Conference Proceedings 2017 Dec 28 (Vol. 1919, No. 1, p. 020002). AIP Publishing LLC.
  32. Amiri-Simkooei AR, Teunissen PJ, Tiberius CC. Application of least-squares variance component estimation to GPS observables. Journal of Surveying Engineering. 2009 Nov;135(4):149-60.
  33. https://play.google.com/store/apps/details?id=com.sensorange.sensorange

فایل ها

هم رسانی

ارجاع به این مقاله

آمار