Control and Dynamic Systems, Volume 20 is a collection of papers that discusses the techniques and technology of the application of nonlinear filters and Kalman filters.
This collection deals with issues on computation techniques along with many examples of applications of these filters. One paper reviews the bias-separated estimation theory with some alternate derivations by investigators which can provide further extensions. Another paper shows that methods and techniques used in estimating stochastic parameters that have been derived from conventional stochastic operations are effective in various applications. Other papers describe the many advanced applications of Kalman filters and nonlinear estimators in aerospace systems such as the application of adaptive Kalman filtering for aided strapdown navigation systems. As an example, a software package can test the technique of model switching; as well as other applications of the methods of adaptive Kalman filtering for aided strapdown navigation systems. Total system development of ballistic missiles concerns system-level understanding that uses modern analytic methods including applications of filtering and smoothing theory.
This book can prove useful for people working in industrial process control or in econometrics, as well as nuclear physicists.
Contents Contributors Preface Contents of Previous Volumes Separated-Bias Estimation and Some Applications I. Introduction II. Review of Theory III. Extensions of Theory IV. Fixed-Interval Smoothing V. Failure Detection and Estimation VI. Additional Applications VII. Conclusions Appendix: Bias-Separation Theory for Discrete-Time Systems References Techniques and Methodologies for the Estimation of Covariances, Power Spectra, and Filter-State Augmentation I. Introduction II. Determination of Stationary Measurements III. Weighting Functions IV. Test of Gaussian Distribution V. Estimation of Covariances and Power Spectra VI. Estimation of Linear Shaping Filters VII. Conclusion References Advanced Applications of Kalman Filters and Nonlinear Estimators in Aerospace Systems I. Introduction II. Prospective Filter Designs III. Performance Analysis IV. Use of Performance Analysis in Design V. Example of Reduced-Order Linear Kalman Filter Design VI. An Adaptive Extended Kalman Filter for Target-Image Tracking VII. Conclusion References Application of Model Switching and Adaptive Kalman Filtering for Aided Strapdown Navigation Systems I. Introduction II. The Technique of Model Switching for Strapdown Navigation Systems III. Application of Adaptive Kalman Filtering for Aided Strapdown Navigation Systems IV. Software Design for Error-Model Testing V. Summary References Use of Filtering and Smoothing Algorithms in the Analysis of Missile-System Test Data I. Introduction II. Ballistic Missile Guidance-System Evaluation Using Multiple References III. Validation of Filter/Smoother Models Appendix: Recursive Calculation of Data-Equation Matrices References Inertial Navigation System Error Model Considerations in Kalman Filter Applications I. Introduction II. Local-Level Coordinate System Navigatio
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- © Academic Press 1983
- 1st November 1983
- Academic Press
- eBook ISBN: