Estimation with Applications to Tracking and Navigation: Theory Algorithms and Software / Edition 1

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Overview

"Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics." "The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems." "Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area."--BOOK JACKET.
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Editorial Reviews

From The Critics
Presenting the material from a graduate-level course on theory and computational algorithms of estimation in the Department of Electrical and Computer Engineering at the University of Connecticut, this text covers the design and evaluation of state estimation algorithms that operate in a stochastic environment. The algorithms are used for information extraction systems, remote sensing of moving objects, and other applications. Knowledge of linear systems and probability theory at the first-semester graduate level is assumed. Annotation c. Book News, Inc., Portland, OR
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Product Details

  • ISBN-13: 9780471416555
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 6/28/2001
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 584
  • Sales rank: 1,013,702
  • Product dimensions: 6.46 (w) x 9.25 (h) x 1.30 (d)

Meet the Author

YAAKOV BAR-SHALOM, PhD, is Distinguished Professor in the Department of Electrical and Computer Engineering and Director of the Estimation and Signal Processing Lab at the University of Connecticut in Storrs.
X. RONG LI, PhD, is Associate Professor in the Department of Electrical Engineering at the University of New Orleans.
THIAGALINGAM KIRUBARAJAN, PhD, is Assistant Research Professor in the Department of Electrical and Computer Engineering and Associate Director of the Estimation and Signal Processing Lab at the University of Connecticut in Storrs.
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Table of Contents

Preface
Acronyms
Mathematical Notations
1 Introduction 1
2 Basic Concepts in Estimation 89
3 Linear Estimation in Static Systems 121
4 Linear Dynamic Systems with Random Inputs 179
5 State Estimation in Discrete-Time Linear Dynamic Systems 199
6 Estimation for Kinematic Models 267
7 Computational Aspects of Estimation 301
8 Extensions of Discrete-Time Linear Estimation 319
9 Continuous-Time Linear State Estimation 341
10 State Estimation for Nonlinear Dynamic Systems 371
11 Adaptive Estimation and Maneuvering Targets 421
12 Introduction to Navigation Applications 491
Bibliography 537
Index 547
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