Intelligent sensor positioning and orientation through constructive neural network-embedded INS/GPS integration algorithms

Sensors (Switzerland)

Volumn 10, Issue 10, 2010, Pages 9252-9285

  Chiang, Kai Wei ^a   Chang, Hsiu Wen ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Constructive neural networks; GPS INS; Mobile mapping systems; Sensor integration

Indexed keywords

CASCADE CORRELATION NEURAL NETWORKS; CONSTRUCTIVE NEURAL NETWORK; GPS/INS; INERTIAL NAVIGATION SYSTEMS (INS); MICRO ELECTROMECHANICAL SYSTEM (MEMS); MOBILE MAPPING SYSTEMS; MULTILAYER FEEDFORWARD NEURAL NETWORKS; SENSOR INTEGRATION;

ALGORITHMS; GLOBAL POSITIONING SYSTEM; INERTIAL NAVIGATION SYSTEMS; INTEGRATED CONTROL; INTELLIGENT CONTROL; MAPPING; MEMS; NEURAL NETWORKS; REACTOR CORES; SMART SENSORS;

THREE DIMENSIONAL COMPUTER GRAPHICS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; GEOGRAPHIC INFORMATION SYSTEM; INSTRUMENTATION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; GEOGRAPHIC INFORMATION SYSTEMS; NEURAL NETWORKS (COMPUTER);

EID: 84871094201     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s101009252     Document Type: Article

References (43)

1. Tao, V.; Li, J. Advances in Mobile Mapping Technology; International Society for Photogrammetry and Remote Sensing (ISPRS) Book Series; Taylor and Francis Group: London, UK, 2007.
2. Goad, C.C. The Ohio State University Mapping System: The positioning component. In Proceedings of the 47th Annual Meeting, Williamsburg, VA, USA, 10-12 June 1991; pp. 121-124.
3. Coetsee, J.; Brown, A.; Bossler, J. GIS data collection using the GPS Van supported by a GPS/inertial mapping system. In Proceedings of ION GPS-94 7th International Technical Meeting of the Satellite Division of the Institute of Navigation, Salt Lake City, UT, USA, 1994, Part 1: 85-93.
4. Li, D.; Zhong, S. D.; He, X.; Zheng, H. A mobile mapping system based on GPS, GIS and multisensor. Int. Arch. Photogramm. Remote Sens. 1999, 32, 1.3.1-1.3.5.
5. Silva, A.R.; Batista, J.C.; Oliveira, R.A.; Camargo, P.O.; Silva, J.F.C. Surveying and mapping of urban streets by photogrammetric traverse. Int. Arch. Photogramm. Remote Sens. 1999, 32, 5.A.5.1-5.A.5.4.
6. Li, R. Mobile Mapping--An emerging technology for spatial data acquisition. Photogramm. Eng. Remote Sens. 1997, 63, 1085-1092.
7. Grejner-Brzezinska, D.; Toth, C. Precision mapping of highway linear features. In Proceedings of the XIXth ISPRS Congress, Amsterdam, The Netherlands, 16-23 July 2000; pp. 233-240
8. Cramer, M.; Stallmann, D.; Halla, N. High precision georeferencing using GPS/INS and image matching. In Proceedings of the International Symposium on Kinematic Systems in Geodesy, Geomatics and Navigation, Banff, Canada, 30 August-2 September 1997; pp. 453-462.
9. Hock, C.; Caspary, W.; Heister, H.; Klemm, J.; Sternberg, H. Architecture and design of the kinematic survey system KiSS. In Proceedings of the 3rd International Workshop on High Precision Navigation, Stuttgart, Germany, April 1995; pp. 569-576.
10. El-Sheimy, N. The development of VISAT--A mobile survey system for GIS applications. Ph.D. thesis, Department of Geomatics Engineering, the University of Calgary: Calgary, Canada, 1996.
11. Greenspan, R.L. Inertial navigation technology from 1970-1995. Navig. J. Inst. Navig. 1995, 42, 165-185.
12. Titterton, D.H.; Weston, J.L. Strapdown Inertial Navigation Technology; Peter Peregrinus Ltd.: Herts, UK, 1997.
13. Brown, R.G.; Hwang, P.Y.C. Introduction to Random Signals; John Wiley & Sons: San Francisco, CA, USA, 1992.
14. Gelb, A. Applied Optimal Estimation. The MIT Press: Cambridge, MA, USA, 1974.
15. Vanicek, P.; Omerbasic, M. Does a navigation algorithm have to use Kalman filter? Can. Aeronaut. Space J. 1999, 45, 292-296.
16. Chang, H.; Xue, L.; Qin, W.; Yuan, G.; Yuan, W. An integrated MEMS gyroscope array with higher accuracy output. Sensors 2008, 8, 2886-2899.
17. Weinberg, M.S.; Kourepenis, A. Error sources in in-plane silicon tuning-fork MEMS gyroscopes. J. Microelectromech. Syst. 2006, 15, 479-491.
18. Gordon, N.J.; Salmond, D.J.; Smith, A.F.M. Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proceedings-F Radar Signal Pro. 1993, 140, 107-113.
19. Maybeck, P.S. Stochastic Models, Estimation, and Control; Academic Press: London, UK, 1994; Volume 1.
20. Sukkarieh, S. Low cost, high integrity, aided inertial navigation systems for autonomous land vehicles. Ph.D. Thesis, Australian Centre for Field Robotics, Dept. of Mechanical and Mechatronic Engineering, The University of Sydney: Sydney, Australia, 2000.
21. Park, M.; Gao, Y. Error and performance analysis of MEMS-based inertial sensors with a low cost GPS receiver. Sensors 2008, 8, 2240-2261.
22. Shin, E.H. A quaternion-based unscented kalman filter for the integration of GPS and MEMS INS. In Proceedings of ION GNSS 2004, Long Beach, CA, USA, 21-24 September 2004.
23. Bergman, N. Recursive Bayesian Estimation Navigation and Tracking Applications. Ph.D. Thesis, Linköping University: Linköping, Sweden, 1999.
24. Aggarwal, P. Hybrid Extended Particle Filter (HEPF) for INS/GPS integrated system, In Proceedings of ION GNSS 2008, Savannah, Georgia, 16-19 September 2008.
25. Kubo, Y.; Wang, J. INS/GPS integration using gaussian sum particle filter. In Proceedings of ION GNSS 2008, Savannah, GA, USA, 16-19 September 2008.
26. Chiang, K.W.; Noureldin, A.; El-Sheimy, N. Multi-sensors integration using neuron computing for land vehicle navigation. GPS Solutions 2003, 6, 209-218.
27. Wang, J.; Ding, W.; Wang, J. Improving Adaptive Kalman Filter in GPS/SDINS integration with neural network. In Proceedings of ION GNSS 2007, Fort Worth, TX, USA, 25-28 September 2007.
28. Sharaf, R.; Noureldin, A. Sensor integration for satellite-based vehicular navigation using neural networks. IEEE Trans. Neural Netw. 2007, 18, 589-594.
29. El-Sheimy, N.; Abdel-Hamid, W.; Lachapelle, G. An adaptive neuro-fuzzy model for bridging GPS outages in MEMS-IMU/GPS land vehicle navigation. In Proceedings of ION GNSS 2004, Long Beach, CA, USA, 21-24 September 2004.
30. Goodall, C.; El-Sheimy, N.; Chiang, K.W. The development of a GPS/MEMS INS integrated system utilizing a hybrid processing architecture. In Proceedings of ION GNSS 2005, Long Beach, CA, USA, 13-16 September 2005.
31. Chiang, K.; Chang, H.; Li, C.; Huang, Y. An artificial neural network embedded position and orientation determination algorithm for low cost MEMS INS/GPS integrated sensors. Sensors 2009, 9, 2586-2610.
32. Doucet, A.; De Freitas, N.; Gordon, N. Sequential Monte Carlo Methods in Practice; Springer: Berlin, Germany, 2001.
33. Thrun, S.; Fox, D.; Burgard, W.; Dellaert, F. Robust monte carlo localization for mobile robots. Arti. Intell. 2001, 128, 99-141.
34. Gustafsson, F.; Gunnarsson, F.; Bergman, N.; Forssell, U.; Jansson, J.; Karlsson, K.; Nordlund, P.J. Particle filters for positioning, navigation and tracking, IEEE Trans. Signal Process. 2002, 50, 425-437.
35. van der Merwe, R.; Doucet, A.; De Freitas, N.; Wan, E. The unscented particle filter. Adv. Neural Inf. Process. Syst. (NIPS13), 2000, 584-590.
36. Aggarwal, P., Syed, Z.; El-Sheimy, N. Hybrid Extended Particle Filter (HEPF) for Integrated Civilian Navigation System. In Proceedings of IEEE/ION PLANS 2008, Monterey, CA, USA, 6-8 2008.
37. Julier, S.J.; Uhlmann, J.K. New extension of the Kalman filter to nonlinear system. Proc. SPIE 1997, 3068, 182-193.
38. Chiang, K.W.; Noureldin, A.; El-Sheimy, N. A new weight updating method for INS/GPS integration architectures based on neural networks. Meas. Sci. Technol. 2003, 15, 2053-2061.
39. Haykin, S. Neural Networks: A Comprehensive Foundation, 2nd ed.; Prentice-Hall: Upper Saddle River, NJ, USA, 1999.
40. Bishop, C.M. Neural Networks for Pattern Recognition; Oxford University Press: New York, NY, USA, 1995.
41. Alpaydin, E. GAL, Neural Networks that Grow When they Learn and Shrink When They Forget; International Computer Science Institute: Berkeley, CA, USA, 1991.
42. Fahlman, S.E.; Lebiere, C. The cascade learning Architecture. In Advances in Neural Information Processing System 2; Touretzky, D.S., Ed.; Morgan Kaufmann Publishers: San Francisco, CA, USA, 1991; pp. 198-209.
43. Chiang, K.W.; Noureldin, A.; El-Sheimy, N. Constructive neural networks based MEMS/GPS integration scheme, IEEE Trans. Aerosp. Electron. Syst. 2008, 44, 582-594.