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http://dx.doi.org/10.7848/ksgpc.2014.32.6.599

Analysis of Factors Affecting Performance of Integrated INS/SPR Positioning during GPS Signal Blockage  

Kang, Beom Yeon (Dept. of Geoinformatics, University of Seoul)
Han, Joong-hee (Dept. of Geoinformatics, University of Seoul)
Kwon, Jay Hyoun (Dept. of Geoinformatics, University of Seoul)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.32, no.6, 2014 , pp. 599-606 More about this Journal
Abstract
Since the accuracy of Global Positioning System (GPS)-based vehicle positioning system is significantly degraded or does not work appropriately in the urban canyon, the integration techniques of GPS with Inertial Navigation System (INS) have intensively been developed to improve the continuity and reliability of positioning. However, its accuracy is degraded as INS errors are not properly corrected due to the GPS signal blockage. Recently, the image-based positioning techniques have been started to apply for the vehicle positioning for the advanced in processing techniques as well as the increased the number of cars installing the camera. In this study, Single Photo Resection (SPR), which calculates the camera exterior orientation parameters using the Ground Control Points (GCPs,) has been integrated with the INS/GPS for continuous and stable positioning. The INS/GPS/SPR integration was implemented in both of a loosely and a tightly coupled modes, based on the Extended Kalman Filter (EKF). In order to analyze the performance of INS/SPR integration during the GPS outage, the simulation tests were conducted with a consideration of factors affecting SPR performance. The results demonstrate that the accuracy of INS/SPR integration is depended on magnitudes of the GCP errors and SPR processing intervals. Additionally, the simulation results suggest some required conditions to achieve accurate and continuous positioning, used the INS/SPR integration.
Keywords
GPS Signal Blockage; INS; SPR; EKF; GCPs;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 Han, J., Kang, B.Y., and Kwon, J.H. (2014), Development of GPS/IMU/SPR integration algorithm and performance analysis for determination of precise car positioning, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 32, No. 2, pp. 163-171. (in Korean with English abstract)   DOI
2 Yang, Y. and Farrell, J.A. (2003), 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.   DOI   ScienceOn
3 Zhou, J., Edwan, E., Knedlik, S., and Loffeld, O. (2010), Low-cost INS/GPS with nonlinear filtering methods, Proceeding of the 2010 13th Conference on Information Fusion (FUSION), IEEE, 26-29 July, Edinburgh, Scotland, pp. 1-8.
4 Jo, K., Chu, K., and Sunwoo, M. (2012), Real-time computer vision/DGPS-aided inertial navigation system for lanelevel vehicle navigation, IEEE Transactions on Intelligent Transportation Systems, Vol. 13, No. 2, pp. 899-913.   DOI
5 Nister, D., Naroditsky, O., and Berfen, J. (2004), Visual odometry, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 27 June-2 July, Washington D.C., USA, Vol. 1, pp. 652-659.
6 Kang, B.Y., Han, J., and Kwon, J.H. (2014), Positioning accuracy analysis of GPS/INS/SPR integration with measurement error of ground control points and image points, Proceedings of the Korean Association of Geographic Information Studies Spring Conference 2014, KAGIS, 24-25 April, Seoul, Korea, pp. 84-85. (in Korean)
7 Kim, K., Park, C.G., Yu, M.J., and Park, Y.B. (2006), A performance comparison of extended and unscented kalman filters for INS/GPS tightly coupled approach, Journal of Control, Automation, and Systems Engineering, Vol. 12, No. 8, pp. 780-788. (in Korean with English abstract)   과학기술학회마을   DOI
8 Leung, K.T., Whidborne, J.F., Purdy, D., and Barber, P. (2011), Road vehicle state estimation using low-cost GPS/INS, Mechanical Systems and Signal Processing, Vol. 25, No. 6, pp. 1988-2004.   DOI
9 Park, J.H. (2013), Estimation for Displacement of Vehicle Based on GPS and Monocular Vision Sensor, Master's thesis, Korea Aerospace University, Goyang-si, Gyeonggido, Korea, 101p. (in Korean with English abstract)
10 Skog, I. and Handel, P. (2009), In-car positioning and navigation technologies-a survey, IEEE Transactions on Intelligent Transportation Systems, Vol. 10, No. 1, pp. 4-21.   DOI   ScienceOn
11 Vu, A., Ramanandan, A., Chen, A., Farrell, J.A., and Barth, M. (2012), Real-time computer vision/DGPS-aided inertial navigation system for lane-level vehicle navigation, IEEE Transactions on Intelligent Transportation Systems, Vol. 13, No. 2, pp. 899-913.   DOI
12 Godha, S. and Cannon, M.E. (2007), GPS/MEMS INS integrated system for navigation in urban areas, GPS Solutions, Vol. 11, No. 3, pp. 193-203.   DOI   ScienceOn
13 Gao, J., Petovello, M., and Cannon, M.E. (2008), Integration of steering angle sensor with global positioning system and micro-electro-mechanical systems inertial measurement unit for vehicular positioning, Journal of Intelligent Transportation Systems, Vol. 12, No. 4, pp.159-167.   DOI
14 Georgy, J., Karamat, T., Iqbal, U., and Noureldin, A. (2011), Enhanced MEMS-IMU/odometer/GPS integration using mixture particle filter, GPS Solutions, Vol. 15, No. 3, pp. 239-252.   DOI