Kalman Filtering with Real-Time Applications
Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and min imum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
1987, 1987
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| Edition: | 1st ed. 1987 |
| Series: | Springer Series in Information Sciences
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1. Preliminaries
- 2. Kalman Filter: An Elementary Approach
- 3. Orthogonal Projection and Kalman Filter
- 4. Correlated System and Measurement Noise Processes
- 5. Colored Noise
- 6. Limiting Kalman Filter
- 7. Sequential and Square-Root Algorithms
- 8. Extended Kalman Filter and System Identification
- 9. Decoupling of Filtering Equations
- 10. Notes
- References
- Answers and Hints to Exercises