Document Type : Original Article

Authors

1 Faculty of Electrical & Computer engineering, Malek Ashtar University of technology, Iran

2 Faculty of Electrical & Computer engineering, Malek Ashtar University of technology, Iran.

Abstract

This paper presents a new Modified Predictive Kalman Filter (MPKF). To solve the problem of a strap-down inertial navigation system (SINS) self-alignment process that the standard Kalman filters cannot give the optimal solution when the system model and stochastic information are unknown accurately. The proposed algorithm is applied to SINS in the initial alignment process with a large misalignment heading angle. The filter is based on the idea of an accurate predictive filter applies n-steps ahead prediction of the SINS model errors to effectively enhance the corrections of the current information residual error on the system. Firstly, the formulations of a novel predictive filter and a fine alignment algorithm for SINS are presented. Secondly, the vehicle results demonstrate the superior performance of the proposed method, in which the MPKF algorithm is less sensitive to uncertainty. It performs faster and more accurate estimation of SINS' initial orientation angles compared with the conventional EKF method.

Keywords

Main Subjects

[1]           L. Chang, F. Qin, and S. Jiang, "Strapdown inertial navigation system initial alignment based on modified process model," IEEE Sensors Journal, vol. 19, no. 15, pp. 6381-6391, 2019.
[2]           H. Han, J. Wang, and M. Du, "A fast SINS initial alignment method based on RTS forward and backward resolution," Journal of Sensors, vol. 2017, 2017.
[3]           F. O. Silva, E. M. Hemerly, and W. C. Leite Filho, "On the error state selection for stationary SINS alignment and calibration Kalman filters–part I: Estimation algorithms," Aerospace Science and Technology, vol. 61, pp. 45-56, 2017.
[4]           F. Silva, E. Hemerly, and W. Leite Filho, "On the error state selection for stationary SINS alignment and calibration Kalman filters—Part II: Observability/estimability analysis," Sensors, vol. 17, no. 3, p. 439, 2017.
[5]           Y. Zhang, L. Luo, T. Fang, N. Li, and G. Wang, "An improved coarse alignment algorithm for odometer-aided SINS based on the optimization design method," Sensors, vol. 18, no. 1, p. 195, 2018.
[6]           S. Guo, M. Wu, J. Xu, and F. Zha, "b-frame velocity aided coarse alignment method for dynamic SINS," IET Radar, Sonar & Navigation, vol. 12, no. 8, pp. 833-838, 2018.
[7]           M. Mu and L. Zhao, "A GNSS/INS-integrated system for an arbitrarily mounted land vehicle navigation device," GPS Solutions, vol. 23, no. 4, p. 112, 2019.
[8]           B. Xu, L. Wang, T. Duan, K. Jin, and J. Zhang, "A fast in-motion alignment based on inertial frame and reverse navigation," in 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS), 2020, pp. 704-713: IEEE.
[9]           G. Emel’yantsev, A. Stepanov, and B. Blazhnov, "Initial Alignment of SINS Measuring Unit and Estimation of Its Errors Using Satellite Phase Measurements," Gyroscopy and Navigation, vol. 10, no. 2, pp. 62-69, 2019.
[10]         L. Vodicheva, L. Belsky, Y. Parysheva, and E. Koksharov, "Improving the Accuracy of Initial Alignment of Strapdown INS with the Help of Gimballed INS," in 2020 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS), 2020, pp. 1-4: IEEE.
[11]         H. Jameian, B. Safarinejadian, and M. Shasadeghi, "A robust and fast self-alignment method for strapdown inertial navigation system in rough sea conditions," Ocean Engineering, vol. 187, p. 106196, 2019.
[12]         H. Xing, Z. Chen, C. Wang, M. Guo, and R. Zhang, "Quaternion-based Complementary Filter for Aiding in the Self-Alignment of the MEMS IMU," in 2019 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL), 2019, pp. 1-4: IEEE.
[13]         F. Zha, S. Guo, and F. Li, "An improved nonlinear filter based on adaptive fading factor applied in alignment of SINS," Optik, vol. 184, pp. 165-176, 2019.
[14]         S. Guo, L. Chang, Y. Li, and Y. Sun, "Robust fading cubature Kalman filter and its application in initial alignment of SINS," Optik, vol. 202, p. 163593, 2020.
[15]         T. Zhang, J. Wang, B. Jin, and Y. Li, "Application of improved fifth-degree cubature Kalman filter in the nonlinear initial alignment of strapdown inertial navigation system," Review of Scientific Instruments, vol. 90, no. 1, p. 015111, 2019.
[16]         M. Fathi, N. Ghahramani, M. A. Shahi Ashtiani, A. Mohammadi, and M. Fallah, "Incremental predictive Kalman filter for alignment of inertial navigation system," Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, p. 0954410018794324, 2018.
[17]         M.-A. Massoumnia and R. Rezaii-Far, "Stable platform initial alignment using state feedback controllers," in [Proceedings 1992] The First IEEE Conference on Control Applications, 1992, pp. 326-329: IEEE.
[18]         J. L. Crassidis and F. L. Markley, "Predictive filtering for nonlinear systems," Journal of Guidance, Control, and Dynamics, vol. 20, no. 3, pp. 566-572, 1997.
[19]         H. Odéen and D. Parker, "Dynamical model parameter adjustments in model predictive filtering MR thermometry," Journal of therapeutic ultrasound, vol. 3, no. 1, p. P31, 2015.
[20]         W. Qiuying, Z. Minghui, G. Zheng, and W. Hui, "Integrated navigation method using marine inertial navigation system and star sensor based on model predictive filtering," in 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS), 2018, pp. 850-857: IEEE.
[21]         L. Zhang, S. Qian, S. Zhang, and H. Cai, "Federated nonlinear predictive filtering for the gyroless attitude determination system," Advances in Space Research, vol. 58, no. 9, pp. 1671-1681, 2016.
[22]         A. Zenere and M. Zorzi, "Model predictive control meets robust Kalman filtering," IFAC-PapersOnLine, vol. 50, no. 1, pp. 3774-3779, 2017.
[23]         L. Cao, X. Chen, and A. K. Misra, "A novel unscented predictive filter for relative position and attitude estimation of satellite formation," Acta Astronautica, vol. 112, pp. 140-157, 2015.
[24]         L. Cao and H. Li, "Norm-constrained predictive filtering for attitude estimation," Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, vol. 230, no. 10, pp. 2000-2006, 2016.
[25]         J. Fang and X. Gong, "Predictive iterated Kalman filter for INS/GPS integration and its application to SAR motion compensation," IEEE Transactions on Instrumentation and Measurement, vol. 59, no. 4, pp. 909-915, 2009.
[26]         N. H. Ariffin, I. R. I. Zakaria, N. Arsad, A. A. A. Bakar, B. Bais, and M. S. D. Zan, "Autonomous MEMS Gyroscope and Accelerometer for North Finding System," Journal of Telecommunication, Electronic and Computer Engineering (JTEC), vol. 10, no. 1-2, pp. 13-17, 2018.
[27]         B. Johnson et al., "Tuning fork MEMS gyroscope for precision northfinding," in 2015 DGON Inertial Sensors and Systems Symposium (ISS), 2015, pp. 1-10: IEEE.
[28]         L. Iozan, M. Kirkko-Jaakkola, J. Collin, J. Takala, and C. Rusu, "Using a MEMS gyroscope to measure the Earth’s rotation for gyrocompassing applications," Measurement Science and Technology, vol. 23, no. 2, p. 025005, 2012.
[29]         E.-H. Shin and N. El-Sheimy, "Accuracy improvement of low cost INS/GPS for land applications," in Proceedings of the 2002 national technical meeting of the institute of navigation, 2002, pp. 146-157.
[30]         D. Titterton, J. L. Weston, and J. Weston, Strapdown inertial navigation technology. IET, 2004.
[31]         K. R. Britting, "Inertial navigation systems analysis," 1971.
[32]         J. Farrell, Aided navigation: GPS with high rate sensors. McGraw-Hill, Inc., 2008.