Practical Approach for Kalman Filtering with Autocorrelated Noise Containing Uncertain Parameters

No AccessEngineering NotesPractical Approach for Kalman Filtering with Autocorrelated Noise Containing Uncertain ParametersSteven Langel, Mathieu Joerger, Samer Khanafseh and Boris PervanSteven LangelThe MITRE Corporation, Bedford, Massachusetts 01730*Signal Processing Engineer, Department of Communications, SIGINT & PNT; currently Virginia Tech, Blacksburg, VA 24061.Search for more papers by this author, Mathieu JoergerVirginia Tech, Blacksburg, Virginia 24061†Assistant Professor, Department of Aerospace & Mechanical Engineering; currently .Search for more papers by this author, Samer KhanafsehIllinois Institute of Technology, Chicago, Illinois 60616‡Research Assistant Professor, Department of Mechanical, Materials and Aerospace Engineering.Search for more papers by this author and Boris PervanIllinois Institute of Technology, Chicago, Illinois 60616§Professor, Department of Mechanical, Materials and Aerospace Engineering.Search for more papers by this authorPublished Online:25 Jun 2020https://doi.org/10.2514/1.G004431SectionsRead Now ToolsAdd to favoritesDownload citationTrack citations ShareShare onFacebookTwitterLinked InRedditEmail About References [1] Langel S., Khanafseh S. and Pervan B., “Bounding Integrity Risk for Sequential State Estimators with Stochastic Modeling Uncertainty,” Journal of Guidance, Control, and Dynamics, Vol. 37, No. 1, 2014, pp. 36–46. https://doi.org/10.2514/1.62056 LinkGoogle Scholar[2] Gelb A. (ed.), Applied Optimal Estimation, MIT Press, Cambridge, MA, 1974, pp. 246–254, Chap. 7. Google Scholar[3] Papoulis A. and Pillai S. U., Probability, Random Variables and Stochastic Processes, McGraw–Hill, New York, 2002, pp. 397–404, Chap. 9. Google Scholar[4] Anderson B. D. O. and Moore J. B., Optimal Filtering, Dover, New York, 1979, pp. 296–303, Chap. 11. Google Scholar[5] Gradshteyn I. S. and Ryzhik I. M., Table of Integrals, Series and Products, 7th ed., Elsevier, Burlington, MA, 2007, p. 22. Google Scholar[6] Boyd J. P., Solving Transcendental Equations: The Chebyshev Polynomial Proxy and Other Numerical Rootfinders, Perturbation Series, and Oracles, Soc. for Industrial and Applied Mathematics, Philadelphia, 2014. Google Scholar[7] “Instrument Flying Handbook,” Federal Aviation Administration FAA-H-8083-15B, 2012. Google Scholar[8] “Minimum Operational Performance Standards for Global Positioning System/Wide Area Augmentation System Airborne Equipment,” Special Committee 159, DO-229C, Radio Technical Commission for Aeronautics, RTCA DO-229C, Washington, D.C., 2006, p. B-3. Google Scholar Previous article Next article FiguresReferencesRelatedDetailsCited byKalman Filter and Correlated Measurement Noise: The Variance Inflation FactorIEEE Transactions on Aerospace and Electronic Systems, Vol. 58, No. 2 What's Popular Volume 43, Number 8August 2020 CrossmarkInformationCopyright © 2020 by Steven Langel, The MITRE Corporation. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. 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. TopicsAir NavigationAircraft Navigation SystemsCommunications SatelliteControl SystemsControl TheoryEarth Observation SatelliteGlobal Positioning SystemGuidance, Navigation, and Control SystemsKalman FilterSatellite Navigation SystemsSatellitesSpace Systems and VehiclesSpacecraft Guidance and ControlSpacecrafts KeywordsKalman FilterTaylor SeriesGPSSatellitesLinear Time InvariantAerospace EngineeringConstellationsEarthSatellite ReceiverInertial NavigationAcknowledgmentsThe author’s affiliation with MITRE Corporation is provided for identification purposes only and is not intended to convey or imply MITRE’s concurrence with, or support of, the positions, opinions or viewpoints expressed by the author.PDF Received2 March 2019Accepted11 May 2020Published online25 June 2020