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Non-Cooperative Target Tracking, Fusion and Control

Algorithms and Advances

  • Book
  • © 2018

Overview

Authors:
  1. Zhongliang Jing

    1. School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China

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  2. Han Pan

    1. School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China

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  3. Yuankai Li

    1. University of Electronic Science and Technology of China, Chengdu, China

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  4. Peng Dong

    1. School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China

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  • Contains a wide survey of models and algorithmic aspects of non-cooperative target tracking, fusion and control
  • Features theoretical background for aerospace applications or remote sensing
  • Provides many illustrative and computational examples

Part of the book series: Information Fusion and Data Science (IFDS)

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Table of contents (17 chapters)

  1. Front Matter

    Pages i-xix
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  2. Background and Fundamentals

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 3-6

    3. Nonlinear Filter

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 7-22

  3. Target Tracking and Fusion

    1. Front Matter

      Pages 23-23
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    2. Dynamic Bias Estimation with Gaussian Mean Shift Registration

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 25-40

    3. Target Tracking and Multi-Sensor Fusion with Adaptive Cubature Information Filter

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 41-70

    4. Multi-Target Tracking with Gaussian Mixture CPHD Filter and Gating Technique

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 71-86

    5. Bearing-Only Multiple Target Tracking with the Sequential PHD Filter for Multi-Sensor Fusion

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 87-103

    6. Joint Detection, Tracking, and Classification Using Finite Set Statistics and Generalized Bayesian Risk

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 105-125

    7. Redundant Adaptive Robust Tracking for Active Satellite

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 127-149

    8. Optimal-Switched H∞ Robust Tracking for Maneuvering Space Target

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 151-160

  4. Visual Tracking and Fusion

    1. Front Matter

      Pages 161-161
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    2. Constrained Image Deblurring with Sparse Proximal Newton Splitting Method

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 163-185

    3. Simultaneous Visual Recognition and Tracking Based on Joint Decision and Estimation

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 187-207

    4. Incremental Visual Tracking with l1 Norm Approximation and Grassmann Update

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 209-228

    5. Image Fusion Using the Quincunx-Sampled Discrete Wavelet Frame

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 229-249

    6. Multi-Focus Image Fusion Using Pulse Coupled Neural Network

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 251-268

    7. Evaluation of Focus Measures in Multi-Focus Image Fusion

      • Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong
      Pages 269-281

  5. Spacecraft Control for Tracking

    1. Front Matter

      Pages 283-283
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Keywords

About this book

This book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of advanced techniques, including Gaussian mixture cardinalized probability hypothesis density (CPHD) filter, optimization on manifold, construction of filter banks and tight frames, structured sparse representation, and others. Containing a variety of illustrative and computational examples, Non-cooperative Target Tracking, Fusion and Control will be useful for students as well as engineers with an interest in information fusion, aerospace applications, radar data processing and remote sensing.

Authors and Affiliations

  • School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China

    Zhongliang Jing, Han Pan, Peng Dong

  • University of Electronic Science and Technology of China, Chengdu, China

    Yuankai Li

About the authors

Professor Zhongliang Jing is the Cheung Kong professor and the Executive Dean working in the School of Aeronautics and Astronautics at Shanghai Jiao Tong University.  He is the recipient of the Science and Technology Award for Chinese Youth and a member of the National High-Tech R&D Program Space and Aviation Expert Group. His research interests include adaptive filtering, target tracking, information fusion, avionics integration, and aerospace control.

Dr. Han Pan works at Shanghai Jiao Tong University's School of Aeronautics and Astronautics with skills and expertise in information fusion, optimization algorithms and space robotics. 

Dr. Yuankai Li is currently at the School of Aeronautics and Astronautics, University of Electronic Science and Technology of China. His research interests include nonlinear estimation and control, autonomous target tracking and GNC techniques for aerospace vehicles.

 Dr. Peng Dong works at Shanghai Jiao Tong University's School of Aeronautics and Astronautics with skills and expertise in information fusion, target tracking and nonlinear filtering.


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