Control and Dynamic Systems V20 - 1st Edition - ISBN: 9780120127207, 9780323150729

Control and Dynamic Systems V20

1st Edition

Advances in Theory and Applications

Editors: C.T. Leonides
eBook ISBN: 9780323150729
Imprint: Academic Press
Published Date: 1st November 1983
Page Count: 430
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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.

Table of Contents




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


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


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


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


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


Inertial Navigation System Error Model Considerations in Kalman Filter Applications

I. Introduction

II. Local-Level Coordinate System Navigation Equations

III. Coordinate Frames for Error-Model Development

IV. Error-Model Development

V. Relationship between Coordinate Frames

VI. Kalman Filter Modeling Considerations

VII. Conclusion

Appendix: Summary of Local-Level Navigation-Mechanization


Comparisons of Nonlinear Recursive Filters for Systems with Nonnegligible Nonlinearities

I. General Introduction

II. Comparisons of Continuous-Time Nonlinear Recursive Filters

III. Comparisons of Discrete-Time Nonlinear Recursive Filters

IV. Conclusions




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© Academic Press 1983
Academic Press
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About the Editor

C.T. Leonides

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