Stochastic Models: Estimation and Control: v. 1

Stochastic Models: Estimation and Control: v. 2

This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.

Compiled by leading authorities, Aerospace Navigation Systems is a compendium of chapters that present modern aircraft and spacecraft navigation methods based on up-to-date inertial, satellite, map matching and other guidance techniques. Ranging from the practical to the theoretical, this book covers navigational applications over a wide range of aerospace vehicles including aircraft, spacecraft and drones, both remotely controlled and operating as autonomous vehicles. It provides a comprehensive background of fundamental theory, the utilisation of newly-developed techniques, incorporates the most complex and advanced types of technical innovation currently available and presents a vision for future developments. Satellite Navigation Systems (SNS), long range navigation systems, short range navigation systems and navigational displays are introduced, and many other detailed topics include Radio Navigation Systems (RNS), Inertial Navigation Systems (INS), Homing Systems, Map Matching and other correlated-extremalsystems, and both optimal and sub-optimal filtering in integrated navigation systems.

The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing. Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed. Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented. Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and their variants.

With Bayesian statistics rapidly becoming accepted as a way to solve applied statisticalproblems, the need for a comprehensive, up-to-date source on the latest advances in thisfield has arisen.Presenting the basic theory of a large variety of linear models from a Bayesian viewpoint,Bayesian Analysis of Linear Models fills this need. Plus, this definitive volume containssomething traditional-a review of Bayesian techniques and methods of estimation, hypothesis,testing, and forecasting as applied to the standard populations ... somethinginnovative-a new approach to mixed models and models not generally studied by statisticianssuch as linear dynamic systems and changing parameter models ... and somethingpractical-clear graphs, eary-to-understand examples, end-of-chapter problems, numerousreferences, and a distribution appendix.Comprehensible, unique, and in-depth, Bayesian Analysis of Linear Models is the definitivemonograph for statisticians, econometricians, and engineers. In addition, this text isideal for students in graduate-level courses such as linear models, econometrics, andBayesian inference.

Developments in sensor and processor sophistication have created a need for effective estimation and control algorithms for hybrid, nonlinear systems. This book presents an effective, flexible family of estimation algorithms that can be used in estimating or controlling a variety of nonlinear plants. Several applications are studied, including tracking a manoeuvring aircraft, automatic target recognition, and the decoding of signals transmitted across a wireless communications link. The authors begin by setting out the necessary theoretical background and then develop a practical, finite-dimensional approximation to an optimal estimator. Throughout the book, they illustrate theoretical results by simulation of control and estimation in real-world hybrid systems, drawn from a variety of engineering fields. The book will be of great interest to graduate students and researchers in electrical and computer engineering. It will also be a useful reference for practising engineers involved in the design of estimation, tracking or wireless communications systems.