References
- Andersen, B. D. O., Moore, J. B. (1979). „Filtracja optymalna.” WNT, Warszawa, 1984. (oryg. Andersen B.D.O., Moore J. B. „Optimal filtering” Prentice-HallInc.,EnglewoodCliffs, New Jersey, USA, 1979).
- Candy, J. V. (1987). „Signal Processing–The Model-Based Approch” McGraw-Hill, Singapore.
- Christian, K. (2000). „Improvements of GNSS Receiver Performance Using Deeply Coupled INS measurements.” IONGPS.
- Grejner-Brzezinska, D. A., Toth C. K., and Yi Y. (2005) „On Improving Navigation Accuracy of GPS/INS Systems.” PhotogrammetricEngineeringandRemoteSensing, Vol. 71, No. 4, 377–389.10.14358/PERS.71.4.377
- Ito, K., Xiong, K. (2000). „Gaussian Filters for Nonlinear Filtering Problems.” IEEETransactionsonAutomaticControl, 45(5), 910–927.10.1109/CDC.2000.912021
- Kalman R. E., (1960) „A New Approach to Linear Filtering and Prediction Problems”, Trans. of the ASME - Journal of Basic Engineering, p. 35-45.10.1115/1.3662552
- Kaniewski, P., (2006) „Aircraft Positioning with INS/GNSS Integrated System” Molecular and Quantum Acoustics, Vol. 27, p. 149-168.
- Kim, H et al. (2003) „An Ultra Tightly coupled GPS/INS Integration using Federated Kalman Filter.” IONGPS.
- Knight, D. T. (1999). „Rapid Development of Tightly Coupled GPS/INS Systems.” ProceedingofIONInternationalMeeting, Nashville, Tennessee.
- Kwiecień, J., Malinowski, M., Bujnowski, S., Bujarkiewicz, B. (2006) „ATR TRACK III: The real-time GPS for public security.” ReportsonGeodesy, 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 Estimation for Nonlinear Systems”, Technical Report IMM-REP-1998-15, Department of Mathematical Modelling, DTU, (revised Oct. 2004).
- Nørgaard M., Poulsen N., Ravn O., (2000) „New Developments in State Estimation for Nonlinear Systems”, Automatica, 36.10.1016/S0005-1098(00)00089-3
- Rauch, H. E., Tung, F., Striebel, C. T., (1965) „Maximum likelihood estimates of linear dynamic systems”. AIAA Journal, 3(8):1445–1450.10.2514/3.3166
- Rogers, R.M. (2007). „Applied Mathematics in Integrated Navigation Systems.” 3rd ed. Blacksburg, VA, USA: AmericanInstituteofAeronauticsandAstronautics, Inc.
- Särkkä, S. (2006) „Recursive Bayesian Inference on Stochastic Differential Equations.” Doctoraldissertation,HelsinkiUniversityofTechnologyLaboratoryofComputationalEngineeringPublications Raport B54, Espoo.
- Särkkä S., Vehtari A., and Lampinen J., (2007) „Prediction of ESTSP Competition Time Series by Unscented Kalman Filter and RTS Smoother”, In Proceedings of ESTSP 2007, Espoo.
- Särkkä, S., (2008) „Unscented Rauch-Tung-Striebel smoother”. IEEE Transactions on Automatic Control, 53(3):845–849.10.1109/TAC.2008.919531
- Shin E, El-Sheimy N., (2005) „Backward Smoothing for Pipeline Surveying Applications” in Proceedings of ION NTM, pp. 921-927, U. S. Institute of Navigation, Fairfax VA, 24-26 January, San Diego CA.
- Shin E., (2005) „Estimation Techniques for Low-Cost Inertial Navigation”, PhD Thesis, Department of Geomatics Engineering, University of Calgary, UCGE Report No. 20219, Canada.
- van der Merwe, R., Wan, E.A. (2001) „Efficient Derivative-Free Kalman Filters for Online Learning.” InProc.ofESANN, Bruges.
- van der Merwe, R., Wan, E.A. (2001) „The square-root unscented kalman filter for state and parameter-estimation.” InProceedingsoftheInternationalConferenceonAcoustics, Speech, and Signal Processing (ICASSP), Salt Lake City, Utah.
- van der Merwe. R., Wan. E.A., Julier. S.J. (2004). „Sigma-Point Kalman Filters for Nonlinear Estimation and Sensor-Fusion:Applications to Integrated Navigation.” InProceedingsoftheAIAAGuidance,NavigationandControlConference, Providence, RI.
- Vorbrich, K.K., (2011) „Analysis of some low- and high-dynamics errors of Low-Cost IMU”, Geodesy and Cartography, Vol. 60, No 1, 2011, pp. 35-59.10.2478/v10277-012-0016-7