Book description
This book is intended primarily as a handbook for engineers who must
design practical systems.
Its primary goal is to discuss model development in sufficient detail
so that the reader may design an estimator that meets all application
requirements and is robust to modeling assumptions. Since it is
sometimes difficult to a priori determine the best model
structure, use of exploratory data analysis to define model
structure is discussed. Methods for deciding on the “best” model are
also presented.
A second goal is to present little known extensions of least squares
estimation or Kalman filtering that provide guidance on model
structure and parameters, or make the estimator more robust to changes
in real-world behavior.
A third goal is discussion of implementation issues that make the
estimator more accurate or efficient, or that make it flexible so that
model alternatives can be easily compared.
The fourth goal is to provide the designer/analyst with guidance in
evaluating estimator performance and in determining/correcting problems.
The final goal is to provide a subroutine library that simplifies
implementation, and flexible general purpose high-level drivers that
allow both easy analysis of alternative models and access to
extensions of the basic filtering.
BRUCE P. GIBBS
has forty-one years of experience applying estimation and control
theory to applications for NASA, the Department of Defense, the
Department of Energy, the National Science Foundation, and private
industry. He is currently a consulting scientist at Carr Astronautics,
where he designs image navigation software for the GOES-R geosynchronous
weather satellite. Gibbs previously developed similar systems for the
GOES-NOP weather satellites and GPS.
