Improved Nonlinear Filtering For Target Tracking: Particle Filtering: Basics, Concepts and Improvements

Yan Zhai

ISBN 10: 3639070100 / ISBN 13: 9783639070101

Published by VDM Verlag Dr. Müller, 2008

About this Item

Seller Inventory # LU-9783639070101

Bibliographic Details

• Title: Improved Nonlinear Filtering For Target Tracking: Particle Filtering: Basics, Concepts and Improvements
• Publisher: VDM Verlag Dr. Müller
• Publication Date: 2008
• Language: English
• ISBN 10: 3639070100
• ISBN 13: 9783639070101
• Binding: Paperback
• Condition: New
• Dimensions: 15.01W x 1.17H x 22D centimeters 15.01 centimeters width by 1.17 centimeters height by 22 centimeters depth
• Weight: 272 grams

About this title

Synopsis

Particle filtering is a new nonlinear state estimation technique that aims to directly approximate the posterior distribution of the system. This technique was introduced to the engineering community in the early years of 2000. Since then it has drawn significant attentions due to its accuracy, robustness and flexibility in various nonlinear/non-Gaussian estimation applications, such as target tracking, robot localization and mapping, communications, sensor networks, computer vision and others. Latest research has shown that particle filter based algorithms can greatly improve the estimations over conventional methods, such as extended Kalman filter (EKF). This book introduces the basic concept of particle filtering, its advantages and limitations as well as various methods to improve particle filters. The analysis provided by this book should shed some light on how to design advanced particle filter tracking algorithms.

About the Author

Dr. Yan Zhai: Ph.D in ECE from the Univ. of Oklahoma in 2007. His research area is signal processing. He is now with Schlumberger, TX. Dr. Mark Yeary: Ph.D.E.E from Texas A&M University in 1999. Currently, he is a tenured Associate Professor in the Univ. of Oklahoma. His research interest is signal processing in weather radar applications.