Attitude and Heading Reference System for Aerospace Application
Keywords:
ArdiunoUno, Accelerometer, Gyroscope, MagnetometerAbstract
Many experiments have been conducted for attitude estimation with low cost micro electro-mechanical system (MEMS), even though it was of low cost and less weight it causes certain noise and errors over time. The main objective of the paper is to introduce accelerometer portion of basic attitude and heading reference system for aerospace application using Internet of Things (IoT) which can be used to find the optimal weight value such error of the Attitude and Heading Reference (AHRS) is minimised. The proposed system also assures the body rate by using 2 axis gyro and it provides distance rate measurement and angular rotation. This system consumes low power and easy to handle
References
[1] M. Wang, Y. C. Yang, R. R. Hatch, Y. H. Zhang, Adaptive filter for a miniature MEMS based attitude and heading reference system. In Proceedings of IEEE Position Location and Navigation Symposium, Monterey, CA, USA, April 26-29, 2004.
[2] R. Zhu, D. Sun, Z. Y. Zhou, D. Q. Wang, A linear fusion algorithm for attitude determination using low cost MEMS-based sensors. Measurement, 40, 322-328, 2007.
[3] E. Mu˜noz, A. R. Jim´enez, F. de Ponte, F. Zampella, Evaluation of AHRS Algorithms for Inertial Personal Localization in Industrial Environments, Proceedings of the 2015 IEEE International Conference on Industrial Technology (ICIT), pp. 3412 - 3417 Seville, Spain, March 17-19, 2015.
[4] A. E. Eiben, and J. E. Smith, Introduction to Evolutionary Computing, Springer, Natural Computing Series, 1st edition, 2003.
[5] Foot Mounted IMU data sets for the evaluation of PDR algorithms, LOPSI Research group, Spain, http://lopsi.weebly.com/downloads.html, 2017.
[6] A. G. Cutti, A. Giovanardi, L. Rocchi, A. Davalli, R. Sacchetti, Ambulatory measurement of shoulder and elbow kinematics through inertial and magnetic sensors. Med. Boil. Eng. Comput., 46, 169-178, 2008.
[7] W. M. Chung, S. Yeung, W. W. Chan, R. Lee, Validity of VICON Motion Analysis System for Upper Limb Kinematic Measurement AComparisonStudy with Inertial Tracking Xsens System. Hong Kong Physiother. J.2011.
[8] D. Hamacher, D. Bertram, C. Folsch, L. Schega, Evaluation of a visual feedback system in gait retraining: A pilot study. Gait Posture, 36, 182- 186, 2012.
[9] K. Saber-Sheikh, E. C. Bryant, C. Glazzard, A. Hamel, R. Y. Lee,Feasibility of using inertial sensors to assess human movement. Man.Ther., 15, 122-125, 2010.
[10] Foot Mounted IMU data sets for the evaluation of PDR algorithms, LOPSI Research group, Spain, http: //lopsi.weebly.com/downloads.html, 2017.
[11] A. G. Cutti, A. Giovanardi, L. Rocchi, A. Davalli, R. Sacchetti, Ambulatory measurement of shoulder and elbow kinematics through inertial and magnetic sensors. Med. Boil. Eng. Comput., 46, 169-178, 2008.
[12] W. M. Chung, S. Yeung, W. W. Chan, R. Lee, Validity of VICON Motion Analysis System for Upper Limb Kinematic Measurement A Comparison Study with Inertial Tracking Xsens System. Hong Kong Physiother. J. 2011.
[13] D. Hamacher, D. Bertram, C. Folsch, L. Schega, Evaluation of a visual feedback system in gait retraining: A pilot study. Gait Posture, 36, 182-186, 2012.
[14] K. Saber-Sheikh, E. C. Bryant, C. Glazzard, A. Hamel, R. Y. Lee, Feasibility of using inertial sensors to assess human movement. Man. Ther., 15, 122-125, 2010.
[15] T.H.Cox,C. J.Nagy,M. A. Skoog, and I.A. Somers, “Civil UAV capabil it y assessment,” The National Aeronautics and Space Administration, pp. 1–10, 2014
[16] Z. Wachter, “A cost effective motion platform for performance testing of MEMS-based attitude and heading reference systems,” Journal of Intelligent & Robotic Systems, vol. 70, no. 411, pp. 1–9, 2013.
[17] S. J. Zaloga, D. Rockwell, and P. Finnegan, World Unmanned Aerial Vehicle Systems Market Profile and Forecast, Teal GroupCorporation, 2014
[18] R. Schneiderman, “Unmanned drones are flying high in the military/aerospace sector,” IEEE Signal Processing Magazine, vol. 29, no. 1, pp. 8–11, 2014
[19] Qiang Zhu, Shaokang Li, Zhen Xu, Study of Solving Nonlinear Least Squares Under Large Residual Based on Levenberg-Marquardt Algorithm, China Measurement and Testing Technology, 42(03): 12–16, 2016.
[20] Xu Yang, XingLong Wang, Discussion on the Method of Eliminating Abnormal Data in Measurement Test,Technology Wind, (15): 136, 2016.
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
