Residual-Normalized Strong Tracking Filter for Tracking a Noncooperative Maneuvering Spacecraft

No AccessEngineering NotesResidual-Normalized Strong Tracking Filter for Tracking a Noncooperative Maneuvering SpacecraftYuzi Jiang, Pengbin Ma and Hexi BaoyinYuzi JiangTsinghua University, 100084 Beijing, People's Republic of China, Pengbin MaState Key Laboratory of Astronautic Dynamics, Xi'an Satellite Control Center, 710043 Xi'an, People's Republic of China and Hexi BaoyinTsinghua University, 100084 Beijing, People's Republic of ChinaPublished Online:3 Jul 2019https://doi.org/10.2514/1.G004347SectionsRead Now ToolsAdd to favoritesDownload citationTrack citations ShareShare onFacebookTwitterLinked InRedditEmail About References [1] Baird M. A., "Maintaining Space Situational Awareness and Taking It to the Next Level," Air and Space Power Journal, Vol. 27, No. 5, 2013, pp. 50–72. Google Scholar[2] Abbot R. I. and Wallace T. P., "Decision Support in Space Situational Awareness," Lincoln Laboratory Journal, Vol. 16, No. 2, 2007, pp. 297–335. Google Scholar[3] Bobrinsky N. and Del Monte L., "The Space Situational Awareness Program of the European Space Agency," Cosmic Research, Vol. 48, No. 5, 2010, pp. 392–398. doi:https://doi.org/10.1134/S0010952510050035 CrossrefGoogle Scholar[4] Continuing Kepler's Quest: Assessing Air Force Space Command's Astrodynamics Standards, National Academies Press, Washington, D.C., 2012, pp. 38–39. doi:https://doi.org/10.17226/13456 Google Scholar[5] Goff G. M., Black J. T. and Beck J. A., "Orbit Estimation of a Continuously Thrusting Spacecraft Using Variable Dimension Filters," AIAA Guidance, Navigation, and Control Conference, AIAA Paper 2015-0093, 2015. doi:https://doi.org/10.2514/6.2015-0093 LinkGoogle Scholar[6] Lee D. J. and Alfriend K. T., "Precise Real-Time Orbit Estimation Using the Unscented Kalman Filter," Advances in the Astronautical Sciences, Vol. 114, No. 3, 2003, pp. 1853–1872. Google Scholar[7] Montenbruck O. and Ramos-Bosch P., "Precision Real-Time Navigation of LEO Satellites Using Global Positioning System Measurements," GPS Solutions, Vol. 12, No. 3, 2008, pp. 187–198. doi:https://doi.org/10.1007/s10291-007-0080-x CrossrefGoogle Scholar[8] Fitzgerald R., "Divergence of the Kalman Filter," IEEE Transactions on Automatic Control, Vol. 16, No. 6, 1971, pp. 736–747. doi:https://doi.org/10.1109/TAC.1971.1099836 CrossrefGoogle Scholar[9] Kelecy T. and Jah M., "Detection and Orbit Determination of a Satellite Executing Low Thrust Maneuvers," Acta Astronautica, Vol. 66, Nos. 5–6, 2010, pp. 798–809. doi:https://doi.org/10.1016/j.actaastro.2009.08.029 CrossrefGoogle Scholar[10] Goff G. M., Black J. T. and Beck J. A., "Tracking Maneuvering Spacecraft with Filter-Through Approaches Using Interacting Multiple Models," Acta Astronautica, Vol. 114, Sept.–Oct. 2015, pp. 152–163. doi:https://doi.org/10.1016/j.actaastro.2015.05.009 CrossrefGoogle Scholar[11] Ko H. C. and Scheeres D. J., "Tracking Maneuvering Satellite Using Thrust-Fourier-Coefficient Event Representation," Journal of Guidance, Control, and Dynamics, Vol. 39, No. 11, 2016, pp. 2554–2562. doi:https://doi.org/10.2514/1.G000353 LinkGoogle Scholar[12] Zhai G., Bi X., Zhao H. and Liang B., "Non-Cooperative Maneuvering Spacecraft Tracking via a Variable Structure Estimator," Aerospace Science and Technology, Vol. 79, Aug. 2018, pp. 352–363. doi:https://doi.org/10.1016/j.ast.2018.05.052 CrossrefGoogle Scholar[13] Li X. R. and Jilkov V. P., "Survey of Maneuvering Target Tracking. Part I. Dynamic Models," IEEE Transactions on Aerospace and Electronic Systems, Vol. 39, No. 4, 2003, pp. 1333–1364. doi:https://doi.org/10.1109/TAES.2003.1261132 CrossrefGoogle Scholar[14] Liu M., Lai J. Z., Li Z. M. and Liu J. Y., "An Adaptive Cubature Kalman Filter Algorithm for Inertial and Land-Based Navigation System," Aerospace Science and Technology, Vol. 51, April 2016, pp. 52–60. doi:https://doi.org/10.1016/j.ast.2016.01.010 CrossrefGoogle Scholar[15] Mattia Z., "Robust Kalman Filtering Under Model Perturbations," IEEE Transactions on Automatic Control, Vol. 62, No. 6, 2017, pp. 2902–2907. doi:https://doi.org/10.1109/TAC.2016.2601879 CrossrefGoogle Scholar[16] Zhou D. H., Xi Y. G. and Zhang Z. J., "Suboptimal Fading Extended Kalman Filtering for Nonlinear Systems," Control and Decision, Vol. 5, No. 5, 1990, pp. 1–6. Google Scholar[17] Zhou D. H., Xi Y. G. and Zhang Z. J., "A Suboptimal Multiple Fading Extended Kalman Filter," Acta Automatica Sinica, Vol. 17, No. 6, 1991, pp. 689–695. Google Scholar[18] Jwo D. J. and Wang S. H., "Adaptive Fuzzy Strong Tracking Extended Kalman Filtering for GPS Navigation," IEEE Sensors Journal, Vol. 7, No. 5, 2007, pp. 778–789. doi:https://doi.org/10.1109/JSEN.2007.894148 CrossrefGoogle Scholar[19] Ge Z. X., Yang Y. M. and Wen X. S., "Strong Tracking UKF Method and Its Application in Fault Identification," Chinese Journal of Scientific Instrument, Vol. 29, No. 8, 2008, pp. 1670–1674. Google Scholar[20] Jwo D. J. and Lai S. Y., "Navigation Integration Using the Fuzzy Strong Tracking Unscented Kalman Filter," Journal of Navigation, Vol. 62, No. 2, 2009, pp. 303–322. doi:https://doi.org/10.1017/S037346330800516X CrossrefGoogle Scholar[21] Wang Y. D., Sun S. M. and Li L., "Adaptively Robust Unscented Kalman Filter for Tracking a Maneuvering Vehicle," Journal of Guidance, Control, and Dynamics, Vol. 37, No. 5, 2014, pp. 1696–1701. doi:https://doi.org/10.2514/1.G000257 LinkGoogle Scholar[22] Zhang C., Zhao M., Yu X. L., Cui M. L., Zhou Y. and Wang X. G., "Cubature Kalman Filter Based on Strong Tracking," Proceedings of the Third International Conference on Communications, Signal Processing, and Systems, Springer, Cham, Switzerland, 2015, pp. 131–138. Google Scholar[23] Zhang H. W., Xie J. W., Ge J. A., Lu W. L. and Zong B. F., "Adaptive Strong Tracking Square-Root Cubature Kalman Filter for Maneuvering Aircraft Tracking," IEEE Access, Vol. 6, 2018, pp. 10,052–10,061. doi:https://doi.org/10.1109/ACCESS.2018.2808170 CrossrefGoogle Scholar[24] Zhang H. W., Xie J. W., Ge J. A., Lu W. L. and Liu B. Z., "Strong Tracking SCKF Based on Adaptive CS Model for Manoeuvring Aircraft Tracking," IET Radar, Sonar and Navigation, Vol. 12, No. 7, 2018, pp. 742–749. doi:https://doi.org/10.1049/iet-rsn.2017.0467 CrossrefGoogle Scholar Previous article Next article FiguresReferencesRelatedDetailsCited byAn adaptive state estimation for tracking hypersonic glide targets with model uncertaintiesAerospace Science and Technology, Vol. 136Robust UKF-based filtering for tracking a maneuvering hypersonic glide vehicle19 November 2021 | Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, Vol. 236, No. 11Application of Adaptive Weighted Strong Tracking Unscented Kalman Filter in Non-Cooperative Maneuvering Target Tracking22 August 2022 | Aerospace, Vol. 9, No. 8Noise-Adaption Extended Kalman Filter Based on Deep Deterministic Policy Gradient for Maneuvering Targets19 July 2022 | Sensors, Vol. 22, No. 14Gaussian-Binary classification for resident space object maneuver detectionActa Astronautica, Vol. 187Adaptive Tracking Method for Non-Cooperative Continuously Thrusting Spacecraft3 September 2021 | Aerospace, Vol. 8, No. 9Ranging-Measurements-Based Maneuver Detection Method for Space Target TrackingJournal of Physics: Conference Series, Vol. 1828, No. 1INS/Odometer Land Navigation by Accurate Measurement Modeling and Multiple-Model Adaptive EstimationIEEE Transactions on Aerospace and Electronic Systems, Vol. 57, No. 1 What's Popular Volume 42, Number 10October 2019 CrossmarkInformationCopyright © 2019 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the eISSN 1533-3884 to initiate your request. See also AIAA Rights and Permissions www.aiaa.org/randp. TopicsAircraft TrackingControl TheoryGlobal Positioning SystemGuidance, Navigation, and Control SystemsKalman FilterNavigational GuidanceSatellite Navigation SystemsSatellitesSpace Systems and VehiclesSpacecraft Guidance and ControlSpacecraftsTracking and Positioning Systems KeywordsSpacecraftsUnscented Kalman FilterSatellitesGround StationSpace Situational AwarenessMonte Carlo SimulationInteracting Multiple ModelGlobal Positioning SystemGaussian White NoiseNonlinear FilterAcknowledgmentThis research is supported by the National Natural Science Fund for Distinguished Young Scholars of China (no. 11525208).PDF Received21 January 2019Accepted27 May 2019Published online3 July 2019