An Introduction to Kalman Filtering with MATLAB Examples
An Introduction to Kalman Filtering with MATLAB Examples
Narayan Kovvali, Mahesh Banavar, and Andreas Spanias
SenSIP Center, Arizona State University
Contents
Acknowledgments . ix
1 Introduction . 1
2 The Estimation Problem 5
2.1 Background . 5
2.1.1 Example: Maximum-Likelihood Estimation in Gaussian Noise 6
2.2 Linear Estimation . 7
2.3 The Bayesian Approach to Parameter Estimation . 9
2.3.1 Example: Estimating the Bias of a Coin 9
2.4 Sequential Bayesian Estimation 10
2.4.1 Example: The 1-D Kalman Filter . 18
3 The Kalman Filter 23
3.1 Theory 23
3.2 Implementation 25
3.2.1 Sample MATLAB Code . 25
3.2.2 Computational Issues 25
3.3 Examples . 27
3.3.1 Target Tracking with Radar . 27
3.3.2 Channel Estimation in Communications Systems 31
3.3.3 Recursive Least Squares (RLS) Adaptive Filtering . 34
4 Extended and Decentralized Kalman Filtering 43
4.1 Extended Kalman Filter 43
4.1.1 Example: Predator-Prey System 46
4.2 Decentralized Kalman Filtering 49
4.2.1 Example: Distributed Object Tracking 53
5 Conclusion . 63
Notation . 65viii
Bibliography 67
Authors’ Biographies . 71
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