Advanced Kalman Filtering, Least–Squares and Modeling: A Practical Handbook

This book delivers practical methods for developing and implementing least squares and Kalman filtering techniques, emphasizing model development and design so that the reader may design an estimator that meets all application requirements and is robust to modeling assumptions. It presents little–known extensions of least squares estimation or Kalman filtering that provide guidance on model structure and parameters, and discusses implementation issues that make the estimator more accurate or efficient, or that make it flexible so that model alternatives can be easily compared. It will appeal to practicing engineers, designers, and analysts using estimation theory in a variety of fields.