R. Munguía
Departamento de Ciencias Computacionales, Universidad de Guadalajara Guadalajara, Jalisco, México. *rodrigo.munguia@upc.edu
ABSTRACT
This work presents a practical method for estimating the full kinematic state of a vehicle, along with sensor error parameters, through the integration of inertial and GPS measurements. This kind of system for determining attitude and position of vehicles and craft (either manned or unmanned) is essential for real time, guidance and navigation tasks, as well as for mobile robot applications.
The architecture of the system is based in an Extended Kalman filtering approach in direct configuration. In this case, the filter is explicitly derived from the kinematic model, as well as from the models of sensors error. The architecture has been designed in a manner that it permits to be easily modified, in order to be applied to vehicles with diverse dynamical behaviors.
]]> The estimated variables and parameters are: i) Attitude and bias-compensated rotational speed of the vehicle, ii) Position, velocity and bias-compensated acceleration of the vehicle and iii) bias of gyroscopes and accelerometers. Experimental results with real data show that the proposed method is enough robust for its use along with low-cost sensors.Keywords: Inertial Navigation, Sensor Fusion, State Estimation.
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References
[1] S. Sukkarieh et al., "Achieving integrity in an INS/GPS navigation loop for autonomous land vehicle applications," IEEE International Conference on Robotics and Automation, 1998. [ Links ]
[2] Q. Honghui and J.B. Moore, "Direct Kalman filtering approach for GPS/INS integration," IEEE Transactions on Aerospace and Electronic Systems, vol. 38, no.2, pp. 687-693, Apr 2002. [ Links ]
]]>[3] Y. Yunchun and J.A. Farrell, "Magnetometer and differential carrier phase GPS-aided INS for advanced vehicle control," IEEE Transactions on Robotics and Automation , vol. 19, no.2, pp. 269- 282, Apr 2003. [ Links ]
[4] S. Godha and M.E. Cannon, "Integration of DGPS with a Low Cost MEMS-Based Inertial Measurement Unit (IMU) for Land Vehicle Navigation Application," Proceedings of the ION GNSS 2005. [ Links ]
[5] I. Skog and P. Händel, "A low-cost GPS aided inertial navigation system for vehicle applications," in Proc. EUSIPCO 2005. [ Links ]
[6] W. Wang, et al., "Quadratic extended Kalman filter approach for GPS/INS integration, Aerospace Science and Technology," Volume 10, Issue 8, December 2006. [ Links ]
[7] P. Davidson et al., "Using low-cost MEMS 3D accelerometer and one gyro to assist GPS based car navigation system," Proceedings of International Conference on Integrated Navigation Systems, 2008. [ Links ]
]]>[8] Z.F. Syed et al., "Civilian Vehicle Navigation: Required Alignment of the Inertial Sensors for Acceptable Navigation Accuracies," IEEE Transactions on Vehicular Technology, vol. 57, no. 6, pp. 3402-3412, Nov. 2008. [ Links ]
[9] Johan B., Willem S., Kalman filter configurations for a low-cost loosely integrated inertial navigation system on an airship, Control Engineering Practice, Volume 16, Issue 12, December 2008. [ Links ]
[10] A. Noureldin et al., "Performance Enhancement of MEMS-Based INS/GPS Integration for Low-Cost Navigation Applications," IEEE Transactions on Vehicular Technology, vol. 58, no. 3, pp. 1077-1096, 2009. [ Links ]
[11] J.H. Wang and Y. Gao, "Land Vehicle Dynamics-Aided Inertial Navigation," IEEE Transactions on Aerospace and Electronic Systems, vol. 46, no.4, pp.1638-1653, Oct. 2010. [ Links ]
[12] L. Hang et al., "Two-Filter Smoothing for Accurate INS/GPS Land-Vehicle Navigation in Urban Centers," IEEE Transactions on Vehicular Technology, vol. 59, no. 9, pp. 4256-4267, Nov. 2010. [ Links ]
]]>[13] T.S. Bruggemann et al., "GPS Fault Detection with IMU and Aircraft Dynamics," IEEE Transactions on Aerospace and Electronic Systems, vol. 47, no. 1, pp. 305-316, January 2011. [ Links ]
[14] J. Dah-Jing and C. Ta-Shun, "Critical remarks on the linearised and Extended Kalman filters with geodetic navigation examples," Measurement, Vol. 43, No. 9, pp. 1077-1089, 2010. [ Links ]
[15] A.H. Mohamed and K.P. Schwarz, "Adaptive Kalman Filtering for INS/GPS," Journal of Geodesy 73: 193-203, 1999. [ Links ]
[16] J.L. Crassidis, "Sigma-point Kalman filtering for integrated GPS and inertial navigation," IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 2, pp. 750-756, April 2006. [ Links ]
[17] H. Carvalho H., et al., "Optimal nonlinear filtering in GPS/INS integration," IEEE Transactions on Aerospace and Electronic Systems, vol. 33, no. 3, pp. 835-850, July 1997. [ Links ]
]]>[18] J. Georgy et al., "Low-Cost Three-Dimensional Navigation Solution for RISS/GPS Integration Using Mixture Particle Filter," IEEE Transactions on Vehicular Technology, vol. 59, no. 2, pp. 599-615, Feb. 2010. [ Links ]
[19] N. El-Sheimy et al., "The Utilization of Artificial Neural Networks for Multisensor System Integration in Navigation and Positioning Instruments," IEEE Transactions on Instrumentation and Measurement, vol. 55, no. 5, pp. 1606-1615, Oct. 2006. [ Links ]
[20] V. Agarwal et al., "Design and Development of a Real-Time DSP and FPGA-Based Integrated GPS-INS System for Compact and Low Power Applications," IEEE Transactions on Aerospace and Electronic Systems, vol. 45, no. 2, pp. 443-454, April 2009. [ Links ]
[21] R. Munguia and A. Grau, "Closing Loops with a Virtual Sensor Base don Monocuar SLAM," IEEE Transactions on Instrumentation and Measurement 2009. [ Links ]
[22] D. Simon, "Kaiman filtering with state constraints: a survey of linear and nonlinear algorithms," IET Control Theory & Applications, vol. 4, no. 8, pp. 1303-1318, August 2010. [ Links ]
]]>[23] I. Skog et al., "Zero-Velocity Detection An Algorithm Evaluation," IEEE Transactions on Biomedical Engineering, vol. 57, no. 11, pp. 2657-2666, November 2010. [ Links ]
[24] J.L. Blanco et al., "A collection of outdoor robotic datasets with centimeter-accuracy ground truth," Autonomous Robots 27, 4, 2009. [ Links ]
[25] J. Zhou et al., "INS/GPS Tightly-coupled Integration using Adaptive Unscented Particle Filter," The Journal of Navigation, vol. 63, pp. 491-511, 2010. [ Links ]
[26] E.J. Ohlmeyer, "Analysis of an Ultra-Tightly Coupled GPS/INS System in Jamming," Position, Location, And Navigation Symposium IEEE/ION, pp. 44-53, 2006. [ Links ]
[27] R. Munguia and A. Grau, "A Practical Method for Implementing an Attitude and Heading Reference System," International Journal of Advanced Robotic Systems, vol. 11, 2014. [ Links ]
]]>[28] J. Rankin, "GPS and differential GPS: An error model for sensor simulation," In Position, Location, and navigation Symposium, pp. 260-266, 1994. [ Links ]
[29] F. Tsai et al., "A positioning scheme combining location tracking with vision assisting for wireless sensor networks," Journal of Applied Research and Technology, vol. 11, no. 2, pp. 292-300, 2013. [ Links ]
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