Enhancing Vector Tracking Accuracy of GPS in Weak Signal Condition Based on Adaptive Strong Tracking Kalman Filter​

Document Type : Original Article

Authors

Abstract

"In this paper, a new method for vector tracking of GPS satellite signals in weak signal circumstances is presented. Extended Kalman Filter (EKF) is usually used in vector tracking. As divergence is one of the main problems in common Kalman filters, Adaptive Kalman filters are used to avoid divergence. Common adaptive Kalman filter in vector tracking is implemented using a window with limited length, which cannot be greater than a specified amount and so after a short while Kalman filter will become divergent again. Window length is specified empirically and in accordance to statistical characteristics which may lead to an ideal solution for one specific amount, but not the other. Therefore adaptive Strong Tracking Kalman Filter (STKF) is used in this paper. Simulation results show that adaptive STKF has high accuracy in relation to adaptive EKF, and in case of correctly arranged STKF parameters computing complexity of the proposed vector tracking will be less than the traditional method. Results show that in comparison to traditional vector tracking ,methods based on adaptive STKF have significantly reduced errors in measuring carrier frequency, position and of course velocity.
 

Keywords


[1]     M. R. Mosavi, M. Moazedi, M. J. Rezaei, and A. Tabatabaei, “Interference Mitigation in GPS Receivers,” Iran University of Science & Technology, 2015. (in persian)
[2]     E. Shafiee, M. R. Mosavi, and M. Moazedi, “Detection of Spoofing Attack Based on Multi-Layer Neural Network in Single-Frequency GPS Receivers,” Journal of Electronical & Cyber Defence, vol. 3, no. 1, 2015. (in persian)
[3]     B. Parkinson, J. Spilker, P. Axelrad, and P. Enge, “Global Positioning System: Theory and Applications,” American Institute of Aeronautics and Astronautics, Washington DC, 1996.
[4]     T. Pany, R. Kaniuth, and B. Eissfeller, “Deep Integration of Navigation Solution and Signal Processing,” Proceedings of the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS), pp. 1095-1102, 2005.
[5]     T. Pany, R. Kaniuth, and B. Eissfeller, “Testing a Vector Delay/Frequency Lock Loop Implementation with the Ipex Software Receiver,” In Proceedings of GPS/GNSS Symposium, 2005.
[6]     T. Pany and B. Eissfeller, “Use of a Vector Delay Lock Loop Receiver for GNSS Signal Power Analysis in Bad Signal Conditions,” In IEEE/ION PLANS, pp. 893-903, 2006.
[7]     J. H. Won and B. Eissfeller, “Effectiveness Analysis of Vector-Tracking-Loop in Signal Fading Environment,” In Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing, pp. 1-6, 2010.
[8]     M. Lashley, D. M. Bevly, and J. Y. Hung, “A Valid Comparison of Vector and Scalar Tracking Loops,” In IEEE/Ion Plans, pp. 464-474, 2010.
[9]     S. Zhao and D. M. Akos, “An Open Source GPS/GNSS Vector Tracking Loop-Implementation, Filter Tuning, and Results,” In Ion Itm, pp. 1293-1305, 2011.
[10]  J. Liu, X. W.  Cui, and M. Q. Lu, “A Vector Tracking Loop based on ML Estimation in Dynamic Weak Signal Environments,” in Proc. CSNC, Guangzhou, China, pp.   629-643, 2012.
[11]  L. T. Hsu, P. D. Groves, and Sh. Sh. Jan, “Assessment of the Multipath Mitigation Effect of Vector Tracking in an Urban Environment,” Proceedings of the ION 2013 Pacific PNT Meeting, 2013.
[12]  S. Zhao, S. Hrbek, M. Lu, and D. Akos, “Deep Integration of GPSINS Based on a Software Defined                       Receiver- Implementation and Test Results,” Proceedings of the 27th Internatiional Meeting of the ION Satellite, 2014.
    [13]  Y. Ng and G. X. Gao, “Advanced Multi-Receiver Vector Tracking for Positioning a Land Vehicle,” Proceedings of the 28th Internatiional Meeting of the ION Satellite, 2015.
[14]  Y. Song and B. Lian, “Combined BDS and GPS Adaptive Vector Tracking Loop in Challenge Environment,” International Conference on China Satellite Navigation, pp. 557-570, 2016.
[15]  M. Cuntz, A. Konovaltsev, and M. Meurer, “Concepts, Development, and Validation of Multiantenna GNSS Receivers for Resilient Navigation,” IEEE Magazines on Proceedings, vol. 104, no. 6, pp. 1288-1301, 2016.
[16]  Zh. Su, X. Wang, Sh. Feng, H. Che, and J. Zhang, “Design of an Adaptive GPS Vector Tracking Loop With the Detection and Isolation of Contaminated Channels,” GPS Solutions, vol. 21, no. 2, pp. 701-713, 2016.
[17]  F. Li, R. Wu, and W. Wang, “The Anti-jamming Performance Analysis for Vector Tracking Loop,” International Conference on China Satellite Navigation, pp. 665-675, 2016.
[18]  A. Tabatabaei, M. R. Mosavi, H. S. Shahhoseini, and K. Borre, “Vectorized and Federated Software Receivers Combining GLONASS and GPS,” GPS Solutions, vol. 21, no. 3, pp. 1331-1339, 2017.
[19]  G. Liu, R. Zhang, M. Guo, and X. Cui, “Accuracy Comparison of GNSS Vector and Scalar Tracking Loop,” IEEE Conference on Navigation and Control, pp. 1346-1351, 2014.
[20]  M. Lashley and D. M. Bevly, “Analysis of Discriminator Based Vector Tracking Algorithms,” Proceedings of the Institute of Navigation (ION), San Diego, pp. 570-576, 2007.
[21]  D. W. Lim, H. W. Kang, S. L. Cho, S. J. Lee, and M. B. Heo, “Performance Evaluation of a GPS Receiver with VDFLL in Harsh Environments,” International Global Navigation Satellite Systems Society IGNSS Symposium, 2013.
[22]  D. J. Jwo, Z. M. Wen, and Y. C. Lee, “Vector Tracking Loop Assisted by the Neural Network for GPS Signal Blockage,” Applied Mathematical Modeling, vol. 39, no.19, pp. 5949-5968, 2015.
[23]  Y. Song and B. Lian, “Combined BDS and GPS Adaptive Vector Tracking Loop in Challenge Environment,” International Conference on China Satellite Navigation, pp. 557-570, 2016.
[24]  D. H. Zhou and P. M. Frank, “Strong Tracking Kalman Filtering of Nonlinear Time-Vvarying Stochastic Systems with Colored Noise: Application to Parameter Estimation and Empirical Robustness Analysis,” International Journal Control, vol. 65, no. 2, pp. 295-307, 1996.
[25]  D. J. Jwo and S. H. Wang, “Adaptive Fuzzy Strong Tracking Extended Kalman Filtering for GPS Navigation,” IEEE Sensors Journal, vol. 7, no. 3, pp. 778-789, 2007.
[26]  X. Chen, C. Shen, W-b Zhang, M. Tomizuka, Y. Xu, and K.     Chiu, “Novel Hybrid of Strong Tracking Kalman Filter and Wavelet Neural Network for GPS/INS during GPS Outages,” Measurement Journal, vol. 46, no. 10, pp.     3847-3854, 2013.