پیوندهای مفید
آمار
| تعداد نشریات | 8 |
| تعداد شمارهها | 438 |
| تعداد مقالات | 5,650 |
| تعداد مشاهده مقاله | 7,683,346 |
| تعداد دریافت فایل اصل مقاله | 6,339,795 |
Adaptive Fusion of Inertial Navigation System and Tracking Radar Data | ||
| AUT Journal of Electrical Engineering | ||
| مقاله 3، دوره 48، شماره 2، بهمن 2016، صفحه 81-92 اصل مقاله (1.49 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/eej.2016.818 | ||
| نویسندگان | ||
| mahdi fathi* 1؛ Nematollah Ghahramani2؛ Mohammad Ali Ashtiani3؛ Ali Mohammadi4؛ Mohsen Fallah5 | ||
| 1Ph.D. Candidate, Department of Aerospace Engineering-Flight Mechanics and Control Group, Malek Ashtar University of Technology | ||
| 2Associate Professor, Department of Electrical Engineering-Control Group, Malek Ashtar University of Technology | ||
| 3Associate Professor, Department of Aerospace Engineering-Flight Mechanics and Control Group, Malek Ashtar University of Technology | ||
| 4Assistant Professor, Department of Electrical Engineering-Control Group, Malek Ashtar University of Technology | ||
| 5Assistant Professor, Department of Electrical Engineering-Communication Group, Malek Ashtar University of Technology | ||
| چکیده | ||
| Against the range-dependent accuracy of the tracking radar measurements including range, elevation and bearing angles, a new hybrid adaptive Kalman filter is proposed to enhance the performance of the radar aided strapdown inertial navigation system (INS/Radar). This filter involves the concept of residual-based adaptive estimation and adaptive fading Kalman filter and tunes dynamically the filter parameters including the fading factors and the measurement and process noises scaling factors based on the ratio of the actual residual covariance to the theoretical one. In fact, due to the unknown and fast-varying statistical parameters of the radar measurement noises and their nonlinear characteristics, applying a conventional Kalman filter to INS/Radar data fusion yields a low performance navigation and in-flight alignment. The Monte Carlo simulation results of the integrated navigation system on an interceptor missile trajectory indicate the new algorithm has an effective performance in face of nonlinearities and uncertainties of the tracking radar measurements. these results allow to know whether the fine in-flight alignment and high performance navigation can be possible for the long-range air defense missile using the low-cost INS/Radar system without aiding global navigation satellite system signals or not. | ||
| کلیدواژهها | ||
| Adaptive Kalman Filter؛ Inertial Navigation؛ in-flight alignment؛ Radar | ||
| عنوان مقاله [English] | ||
| Adaptive Fusion of Inertial Navigation System and Tracking Radar Data | ||
| نویسندگان [English] | ||
| mahdi fathi1؛ Nematollah Ghahramani2؛ Mohammad Ali Ashtiani3؛ Ali Mohammadi4؛ Mohsen Fallah5 | ||
| 1Ph.D. Candidate, Department of Aerospace Engineering-Flight Mechanics and Control Group, Malek Ashtar University of Technology | ||
| 2Associate Professor, Department of Electrical Engineering-Control Group, Malek Ashtar University of Technology | ||
| 3Associate Professor, Department of Aerospace Engineering-Flight Mechanics and Control Group, Malek Ashtar University of Technology | ||
| 4Assistant Professor, Department of Electrical Engineering-Control Group, Malek Ashtar University of Technology | ||
| 5Assistant Professor, Department of Electrical Engineering-Communication Group, Malek Ashtar University of Technology | ||
| چکیده [English] | ||
| Against the range-dependent accuracy of the tracking radar measurements including range, elevation and bearing angles, a new hybrid adaptive Kalman filter is proposed to enhance the performance of the radar aided strapdown inertial navigation system (INS/Radar). This filter involves the concept of residual-based adaptive estimation and adaptive fading Kalman filter and tunes dynamically the filter parameters including the fading factors and the measurement and process noises scaling factors based on the ratio of the actual residual covariance to the theoretical one. In fact, due to the unknown and fast-varying statistical parameters of the radar measurement noises and their nonlinear characteristics, applying a conventional Kalman filter to INS/Radar data fusion yields a low performance navigation and in-flight alignment. The Monte Carlo simulation results of the integrated navigation system on an interceptor missile trajectory indicate the new algorithm has an effective performance in face of nonlinearities and uncertainties of the tracking radar measurements. these results allow to know whether the fine in-flight alignment and high performance navigation can be possible for the long-range air defense missile using the low-cost INS/Radar system without aiding global navigation satellite system signals or not. | ||
| کلیدواژهها [English] | ||
| Adaptive Kalman Filter, Inertial Navigation, in-flight alignment, Radar | ||
| مراجع | ||
|
[1] Titterton, D. H. and Weston, J. L.; “The Alignment of Ship Launched Missile IN Systems,” Inertial Navigation Sensor Development, IEE Colloquium on, London, 1989.
[2] Johnson, C.; Ohlmeyer, E. J. and Pepitone, T. R.; “Attitude Dilution of Precision–A New Metric for Observability of in Flight Alignment Errors,” Guidance, Navigation, and Control Conference and Exhibit, Denver, pp. 2000–2427, 2000.
[3] Ornedo, R. S.; Farnsworth, K. A. and Sandhoo, G. S.; “GPS and Radar Aided Inertial Navigation System for Missile System Applications,” IEEE Position Location and Navigation Symposium, Palm Spring, CA, 1998.
[4] Ohlmeyer, E. J.; Pepitone, T. R. and Hanger, D. B.; “Effect of Trajectory Shaping on Observability of NTW Interceptor In-Flight Alignment Errors,” Dahlgren VA, Naval Surface Warfare Center, 1999.
[5] Ohlmeyer, E. J.; Hanger, D. B. and Pepitone, T. R.; “In-Flight Alignment Techniques for Navy Theater Wide Missiles,” Guidance, Navigation and Control Conference, Montreal, 2001.
[6] Bezick, S. M.; Pue, A. J. and Patzelt, C. M.; “Inertial Navigation for Guided Missile Systems,” Johns Hopkins APL Technical Digest, Applied Physics Laboratory, Vol. 28, pp. 331–342, 2010.
[7] Bar-Itzhack, I. Y. and Porat, B.; “Azimuth Observability Enhancement During Inertial Navigation System In-Flight Alignment,” Journal of Guidance, Control and Dynamics, Vol. 3, No. 4, pp. 337–344, 1980.
[8] Porat, B. and Bar-Itzhack, I. Y.; “Effect of Acceleration Switching During INS In-Flight Alignment,” Journal of Guidance, Control and Dynamics, Vol. 4, No. 4, pp. 385–389, 1981.
[9] Bar-Itzhack, I. Y.; “Minimal Order Time Sharing Filters for INS In-Flight Alignment,” Journal of Guidance, Control and Dynamics, Vol. 5, No. 4, pp. 396–402, 1982.
[10] Anders, J. L.; Johnson, C.; Luckau, A. M.; Moore, T. A. and Ornedo, R. S.; “Successful Flight Test of a GPS and Radar Aided Inertial Navigation System,” Proceedings of the National Technical Meeting of The Institute of Navigation, San Diego, CA, 2002.
[11] Anders, J. L.; Buhar, C.; Estrada, V.; Johnson, C. and Ornedo, R. S.; “New Generation GPS and Radar Aided Inertial Navigation System for Ballistic Missile Interceptor,” Procedings of the 60th Annual Meeting of The Institute of Navigation, Dayton OH, 2004.
[12] Gul, F.; Fang, J. and Khan, S.; “SINS Augmentation by ANS and Secure Radio Positioning System,” 2nd International Conference on Emerging Technologies (ICET), pp. 278–284, 2006.
[13] Li, S. and Peng, Y.; “Radio Beacons/IMU Integrated Navigation for Mars Entry,” Advances in Space Research, Vol. 47, No. 7, pp. 1265–1279, 2011.
[14] Barton, D. K.; “Radar Evaluation Handbook,” Artech House, Norwood MA, 1991.
[15] Skolnik, M. I.; “Introduction to Radar Systems,” McGraw Hill, New York, 3rd Edition, 2001.
[16] Mohamed, A. H. and Schwarz, K. P.; “Adaptive Kalman Filtering for INS/GPS,” J. Geodesy, Vol. 73, No. 4, pp. 193–203. 1999.
[17] Barton, D. K.; “Modern Radar System Analysis,” Artech House, Norwood, MA, 1988.
[18] Ewell, G. W.; Alexander, N. T. and Tomberlin, E. L.; “Investigation of Target Tracking Errors in Monopulse Radars,” Georgia Institute of Technology, Atlanta, Georgia, 1972.
[19] Barton, D. K. and Barton, W. F.; “Modern Radar System Analysis Software and User’s Manual Version 2.0,” Artech House, Norwood MA, 1993.
[20] Jwo, D. J.; Chung, F. C. and Weng, T. P.; “Adaptive Kalman Filter for Navigation Sensor Fusion,” Sensor Fusion and its Applications, Shanghai, InTech, pp. 65–91, 2001.
[21] Hide, C.; Moore, T. and Smith, M.; “Adaptive Kalman Filtering for Low-Cost INS/GPS,” The Journal of Navigation, Vol. 56, Vol. 1, pp. 143–152, 2003.
[22] Xia, Q.; Rao, M.; Ying, Y. and Shen, X.; “Adaptive Fading Kalman Filter with an Application,” Automatica, Vol. 30, No. 8, pp. 1333–1338, 1994.
[23] Jwo, D. J. and Weng, T. P.; “An Adaptive Sensor Fusion Method with Applications in Integrated Navigation,” The Journal of Navigation, Vol. 61, No. 4, pp. 705–721, 2008.
[24] Simon, D.l “Optimal State Estimation,” John Wiley and Sons, Hoboken, New Jersey, 2006.
[25] Titterton, D. H. and Weston, J. L.; “Strapdown Inertial Navigation Technology,” Peter Peregrinus, London, 1997.
[26] Britting, K. R.; “Inertial Navigation Systems Analysis,” John Wiley and Sons Inc., USA, 1971. | ||
|
آمار تعداد مشاهده مقاله: 3,844 تعداد دریافت فایل اصل مقاله: 2,535 |
||