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The use of a Kalman filter in geodesy and navigation

, L.: Sekvencni vyrovnani, kolokace, Kalmanuv filtr. In: Geodeticky a kartograficky obzor 40/82, 1994, Vol.8, pp. 155-157. Welch, G., Bishop, G.: An Introduction to the Kalman Filter. UNC Chapel Hill, 2001. Welch, G., Bishop, G.: SCAAT: Incremental Tracking with Incomplete Information. UNC Chapel Hill, 1997.

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Kalman Filter Realization for Orientation and Position Estimation on Dedicated Processor

REFERENCES 1. Ahn H.-S., Won C.-H. (2009), DGPS/IMU Integration-Based Geolo-cation System: Airborne Experimental Test Results, Aerospace Science and Technology , 13, 316-324. 2. Ali J., Ullah Baig Mirza M. R. (2010), Performance Comparison among Some Nonlinear Filters for a Low Cost SINS/GPS Integrated Solution, Nonlinear Dynamics , 61, 491-502. 3. Bar-Shalom Y., Rong Li X., Kirubarajan T. (2001), Estimation with Applications to Tracking and Navigation , John Wiley & Sons. 4. Brookner E. (1998), Tracking and Kalman Filtering Made Easy , John

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Automatic Identification System (AIS) Dynamic Data Estimation Based on Discrete Kalman Filter (KF) Algorithm

. [4] Jaskólski K., AIS dynamic data estimation based on Kalman Filter, AIS Seminar, HELCOM ’17, Helsinki 2017. [5] Kaniewski P., Funkcje, struktury i algorytmy w zintegrowanych systemach pozycjonujących i nawigacyjnych, habilitation dissertation, WAT, Warszawa 2010 [Functions, structures and algorithms in integrated positioning and navigation systems - available in Polish]. [6] Kantak T., Stateczny A., Urbański J., Podstawy automatyzacji nawigacji, cz. A, Zautomatyzowane systemy nawigacyjne, AMW, Gdynia 1988 [Fundamentals of

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Study of the Effectiveness of Different Kalman Filtering Methods and Smoothers in Object Tracking Based on Simulation Tests

Federated Kalman Filter.” ION GPS . Knight, D. T. (1999). „Rapid Development of Tightly Coupled GPS/INS Systems.” Proceeding of ION International Meeting , Nashville, Tennessee. Kwiecień, J., Malinowski, M., Bujnowski, S., Bujarkiewicz, B. (2006) „ATR TRACK III: The real-time GPS for public security.” Reports on Geodesy , No. 2(77), 179-185. Konatowski, S.; Sipa, T. (2004) „Position estimation using Unscented Kalman Filter” Annual of Navigation, No. 8, p. 97-110. Nørgaard M., Poulsen N., Ravn O., (1998) „Advances in Derivative-Free State

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Real-Time Freeway Traffic State Estimation Based on the Second-Order Divided Difference Kalman Filter

. (2004) A particle filter for freeway traffic estimation. In: Proceedings of the 43rd IEEE Conference on Decision and Control , 2106–2111. 12. Mihaylova, L., Boel, R., Hegyi, A. (2006) An Unscented Kalman filter for freeway traffic estimation. In: Proceedings of 11th IFAC Symposium on Control in Transportation Systems , 31-36. 13. Nahi, N.E., Trivedi, A.N. (1973) Recursive estimation of traffic variables: section density and average speed, Transportation Science, 7, 269–286. 14. NGSIM dataset, (2005) - http

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Dynamics of Electricity Demand in Lesotho: A Kalman Filter Approach

References Hansen, B.E., (1992), Tests for Parameter Instability in Regressions with I(1) Processes, Journal of Business and Economic Statistics, Vol.10, no.3, pp. 321-335. Hunt, L.C., Judge, G., Ninomiya, Y., (2003), Underlying Trends and Seasonality in UK Energy Demand: A Sectoral Analysis, Energy Economics, Vol. 25, no. 1, pp. 93-118. Inglesi-Lotz, R., (2011), The Evolution of Price Elasticity of Electricity Demand in South Africa: A Kalman Filter Application, Energy Policy, Vol. 39, no. 6, pp. 3690

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Exploratory Assessment of the Limiting Extended Kalman Filter Properties

Filter: A general approach. Transportation Research Part B , 39, 141-167. 8. Wang, Y., Papageorgiou, M. and A. Messmer (May 2007). Real-time freeway traffic state estimation based on Extended Kalman Filter: A case study. Transportation Science , 41, 167-181. 9. Wang, Y., Papageorgiou, M., Messmer, A., Coppola, P., Tzimitsi, A. and A. Nuzzolo (2009). An adaptive freeway traffic state estimator. Automatica , 45(1), 10-24. 10. Ashok, K. and M. Ben-Akiva (1993). Dynamic O-D matrix estimation and prediction for real

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A Phase Difference Measurement Method Based on the Extended Kalman Filter for Coriolis Mass Flowmeters

, Y., Yang, H., Zhang, H., Liu, X. (2014). CMF signal processing method based on feedback corrected ANF and Hilbert transformation. Measurement Science Review , 14 (1), 41-47. [15] Mallat, S.G. (1989). Multi-frequency channel decomposition of images and wavelet models. IEEE Transactions on Acoustics, Speech and Signal Processing , 37 (12), 2071-2110. [16] Dash, P.K., Jena, R.K., Panda, G., Routray, A. (2000). An extended complex Kalman filter for frequency measurement of distorted signals. IEEE Transactions on Instrumentation & Measurement, 49 (4

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An unscented Kalman filter in designing dynamic GMDH neural networks for robust fault detection

., Gori, M. and Soda, G. (1992). Local feedback multilayered networks, Neural Computation 4 (1): 120-130. Gori, M., Bengio, Y. and De Mori, R. (1989). BPS: A learning algorithm for capturing the dynamic nature of speech, International Joint Conference on Neural Networks, Washington, DC, USA , pp. 417-423. Gupta, M., Liang, J. and Homma, N. (2003). Static and Dynamic Neural Networks , John Wiley & Sons, Hoboken, NJ. Haykin, S. (2001). Kalman Filtering and Neural Networks , John Wiley&Sons, New York, NY

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Sky-Hook Control and Kalman Filtering in Nonlinear Model of Tracked Vehicle Suspension System

REFERENCES 1. Bajkowski J. M. (2012), Design, Analysis and Performance Evaluation of the Linear, Magnetorheological Damper, Acta Mechanica et Automatica , 6, 5-9. 2. Becerra V. M., Roberts P. D., Griffiths G. W. (2001), Applying the extended Kalman filter to systems described by nonlinear differential-algebraic equations, Control Engineering Practice , 9(3), 267-281. 3. Jamroziak K., Kosobudzki M., Ptak J. (2013), Assessment of the comfort of passenger transport in special purpose vehicles, Eksploatacja i Niezawodność , 15(1), 25

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