Navigational Error Control by Model based Filtering and Smoothing for GPS/INS Integration

International Journal of Electronics and Communication Engineering

© 2015 by SSRG - IJECE Journal

Volume 2 Issue 5

Year of Publication : 2015

Authors : Dr. S. S. Sreeja Mole

10.14445/23488549/IJECE-V2I5P114

How to Cite?

Dr. S. S. Sreeja Mole, "Navigational Error Control by Model based Filtering and Smoothing for GPS/INS Integration," SSRG International Journal of Electronics and Communication Engineering, vol. 2,  no. 5, pp. 45-56, 2015. Crossref, https://doi.org/10.14445/23488549/IJECE-V2I5P114

Abstract:

Nowadays Global Positioning System (GPS) is the widely used system for navigational aids and tracking of vehicles. However, GPS will not offer uninterrupted and consistent position values i.e. Latitude, Longitude and Altitude all the times as it likely to be blocked by buildings, mountains, etc. Inertial Navigation Systems (INS) provides continues information of position, velocity and attitude all the time. However, the performance of INS deteriorates with time due to the perfromance degradation of inertial sensors. GPS/INS integration provides reliable navigation solution. Existing GPS/INS integration using Kalman Filter (KF) can give correct results only when the system dynamic models are completely known. To estimate the state of vehicle, Extended Kalman Filter (EKF) is used. Since EKF provides the inaccurate navigation during the non linear motion of the vehicle, an Unscented Kalman Filter (UKF) has been employed. Interacting Multiple Model (IMM) filter is more efficient than the conventional single model filter in determining the adequate values of process noise covariance. In this paper, the application of Interacting Multiple Model Unscented Kalman Filter Two Filter Smoothing (IMM-UKFTFS) approach to GPS/INS integration for the maneuvering vehicle is proposed. The resulting IMM-UKFTFS strategy effectively deals with the non-linear motion and noise covariance problem of navigation. The performance of the proposed IMM-UKFTFS method is examined for a non-linear trajectory which consist of Constant Acceleration (CA) and Coordinated Turn (CT) models. The simulation results show that the proposed IMM-UKFTFS gives better estimate than the existing conventional estimators such as UKF and IMM-UKF.

Keywords:

GPS; INS; EKF; UKF; IMM-EKF; IMM-UKF; IMM-UKFTFS; TFS

References:

[1]M.S. Grewal and A.P. Andrews, Kalman Filtering Theory and Practice using Matlab, 3rd edition, John & Wiley Publications, 2008.
[2]Simon Haykin, Kalman Filtering and Neural Networks, Wiley Interscience Publications, 2001.
[3]M. S. Grewal, L.R. Weill and A.P. Andrews, Global Positioning Systems, Inertial Navigation and Integration, Wiley Interscience Publications, 2001.
[4]Modelling and Parameter Estimation of Dynamic systems by J.R.Raol,G.Girija and J.Singh.
[5]Yaakov Bar Shalom, X.Rong Li, Thiagalingam Kirubarajan, Estimations with applications to tracking and navigation, Wiley Interscience Publications, 2001.
[6]Honghui Qi, “Direct Kalman Filtering approach for GPS/INS Integration”, IEEE Transaction on Aerospace and Electronic systems, 37,pp. 687-693, 2002.
[7]X. Rong Li, Yaakov Bar-Shalom “Design of an Interacting Multiple Model Algorithm for Air Traffic Control Tracking”, IEEE Transactions on Control Systems Technology. vol.1(3), September 1993.
[8]Chien-HaoTseng and Dae-Jung Jwo “GPS navigation processing using the IMM based Extended kalman filter for integrated navigation sensor fusion”, Sensor Publications, vol.6, pp. 4-17, 2009.
[9]Ronald E.Helmik, W. Dale Blair and Scott A. Hoffman, “One-Step Fixed Lag Smoothers for Markovian Switching Systems”, IEEE Transactions on Automatic Control, vol.41(7), pp.1051-1056, 1996.
[10]Hang Liu, Sameh Nassar and Naser El-Sheimy, “Two Filter Smoothing for Accurate INS/GPS Land Vehicle Navigation in Urban Centers” IEEE Transactions on Vehicular Technology, pp. 4256-4267, vol. 59(9), November 2010.
[11]Li.X, and Bar-shalom.Y, “Performance prediction of the interacting multiple model algorithm”, IEEE Transactions on Aerospace and Electronic Systems, vol.29(3), pp. 755-771, 1993.
[12]Qian. H, An. D, Xia. Q, “IMM-UKF based land vehicle naviagion with low-cost GPS/INS”, Proceedings of the 2010 IEEE International Conferene on Information and Automation, Harbin, China, pp. 2031-2035, June 2010.
[13]X.Rong Li and Vesselin P.Jilkov “Survey of Maneuvering Target Tracking.Part.I:Dynamic Models” IEEE Transaction on Aerospace and Electronic systems, 39,No.4., 2003.
[14]Donald c. Fraser and James E. Potter," The optimum linear smoother as a combination of two optimum linear filters" IEEE Transactions on automatic control, PP 387-390, August 1969.
.