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http://dx.doi.org/10.11003/JPNT.2019.8.3.107

Extended Kalman Filter Based GF-INS Angular Velocity Estimation Algorithm  

Kim, Heyone (Department of Electronics Engineering, Chungnam National University)
Lee, Junhak (Research & Development Division, Korea Aerospace Industries Ltd)
Oh, Sang Heon (Navcours Co. Ltd)
Hwang, Dong-Hwan (Department of Electronics Engineering, Chungnam National University)
Lee, Sang Jeong (Department of Electronics Engineering, Chungnam National University)
Publication Information
Journal of Positioning, Navigation, and Timing / v.8, no.3, 2019 , pp. 107-117 More about this Journal
Abstract
When a vehicle moves with a high rotation rate, it is not easy to measure the angular velocity using an off-the-shelf gyroscope. If the angular velocity is estimated using the extended Kalman filter in the gyro-free inertial navigation system, the effect of the accelerometer error and initial angular velocity error can be reduced. In this paper, in order to improve the navigation performance of the gyro-free inertial navigation system, an angular velocity estimation method is proposed based on an extended Kalman filter with an accelerometer random bias error model. In order to show the validity of the proposed estimation method, angular velocities and navigation outputs of a vehicle with 3 rev/s rotation rate are estimated. The results are compared with estimates by other methods such as the integration and an extended Kalman filter without an accelerometer random bias error model. The proposed method gives better estimation results than other methods.
Keywords
accelerometer bias; Extended Kalman Filter; gyro-free INS; MEMS; spinning vehicle;
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1 Algrain, M. C. & Saniie, J. 1991, Estimation of 3-D Angular Motion Using Gyroscopes and Linear Accelerometers, IEEE Transactions on aerospace and electronic systems, 27, 910-920. https://doi.org/10.1109/7.104259   DOI
2 Brown, R. G. & Hwang, P. Y. C. 1997, Introduction to Random Signals and Applied Kalman Filtering, 3rd ed. (New York: John Wiley & Sons)
3 Chatterjee, G., Latorre, L., Mailly, F., Nouet, P., Hachelf, N., et al. 2017, Smart-MEMS based inertial measurement units: gyro-free approach to improve the grade, Microsystem Technologies, 23, 3969-3978   DOI
4 Chen, J.-H., Lee, S.-C., & DeBra, D. B. 1994, Gyroscope Free Strapdown Inertial Measurement Unit by Six Linear Accelerometers, Journal of Guidance, Control, and Dynamics, 17, 286-290. https://doi.org/10.2514/3.21195   DOI
5 Costello, M. & Webb, C. 2003, Angular Rate Esimtation Using an Array of Fixed and Vibrating Triaxial Acceleration Measurements, in AIAA Atmospheric Flight Mechanics Conference and Exhibit, Texas, U.S., 11-14 Aug 2003. https://doi.org/10.2514/6.2003-5623
6 Cucci, D. A., Crespillo, O. G., & Khaghani, M. 2016, An analysis of a gyro-free inertial system for INS/GNSS navigation, in 2016 European Navigation Conference, Helsinki, Finland, 30 May-2 Jun 2016
7 Edwan, E., Knedlik, S., & Loffeld, O. 2011, Constrained Angular Motion Estimation in a Gyro-Free IMU, IEEE Transactions on Aerospace and Electronic systems, 47, 596-610. https://doi.org/10.1109/TAES.2011.5705694   DOI
8 Hanson, R. 2005, Using Multiple MEMS IMUs to Form a Distributed Inertial Measurement Unit, Master's Thesis, Air Force Air University
9 Hanson, R. & Pachter, M. 2005, Optimal Gyro-Free IMU Geometry, in AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco, CA, 15-18 Aug 2005
10 Mickelson, W. A. 2000, Navigation system for spinning projectiles, U.S. Patent No. 6,163,021. 19
11 Nilsson, J-O. & Skog, I. 2016, Inertial Sensor Arrays - A Literature Review, in 2016 European Navigation Conference, Helsinki, Finland, 30 May-2 Jun 2016
12 Pachter, M., Welker, T. C., & Huffman, R. E. 2013, Gyro-Free INS Theory, Navigation: Journal of the Institute of Navigation, 60, 2, 85-96. https://doi.org/10.1002/navi.32
13 Padgaonkar, A. J., Krieger, K. W., & King, A. I. 1975, Measurement of Angular Acceleration of a Rigid Body Using Linear Accelerometers, Journal of Applied Mechanics, 42, 552-556. https ://doi.org/10.1115/1.3423640   DOI
14 Park, S., Tan, C.-W., & Park, J. 2005, A Scheme for Improving the Performance of a Gyroscope-Free Inertial Measurement Unit, Sensors and Actuactors A: Physical, 121, 6151-6159. https://doi.org/10.1016/j.sna.2005.03.060
15 Santiago, A. A. 1992, Extended Kalman Filtering Applied to a Full Accelerometer Strapdown Inertial Measurement Unit, Ph.D Thesis, Massachusetts Institute of Technology
16 Schuler, A. R., Grammatikos, A., & Fegley, K. A. 1967, Measuring Rotational Motion with Linear Accelerometers, IEEE Transactions on Aerospace and Electronic Systems, 3, 465-472. https://doi.org/10.1109/TAES.1967.5408811
17 Rubinstein, R. Y. 1981, Simulation and the Monte Carlo method (New York: John Wiley & Sons)