Principles and Applications of RELAX:A Robust and Universal Estimator

《Principles and Applications of RELAX:A Robust and Universal Estimator》是2018年科學出版社出版的圖書。

基本介紹

• 書名：Principles and Applications of RELAX:A Robust and Universal Estimator
• 作者：吳仁彪
• 出版社：科學出版社
• 出版時間：2018年1月1日
• 開本：16 開
• 裝幀：精裝
• ISBN：9787030606051

內容簡介

　Signal demixing and parameter estimation for multiple overlapped signals in noise and interference background is a problem often encountered in radar， sonar， communication， navigation， and other fields. Improving parameter estimation performance under low signal-to-noise ratio conditions and robustness in the presence of model errors has always been the focus of research in the field of signal pro cessing and control. Aiming at the above problems， this book presents a general and robust relaxation based estimation method（RELAX） and introduces its basic principles and applications in many aspects.

　　This book has seven chapters. Chapter 1 introduces fundamentals of parameter estimation. Chapter 2 introduces the basic principle of RELAX. Chapters 3-5 introduces the application of RELAX in classical line spectrum estimation， time delay estimation， and direction of arrival estimation. Chapter 6 introduces the application of RELAX in radar target imaging. Chapter 7 briefly introduces the typical application of RELAX in other aspects.

　　This book is rich in content. It can be used as a reference reading for a vast number of scientists and technicians in the field of signal processing and control，as well as a teaching material for graduate students in the related fields.

圖書目錄

1 Fundamentals of Parameter Estimation

1．1 Introduction

1．2 Maximum Likelihood Estimation

1．3 Bayesian Estimation

1．3．1 Random Parameter Estimation Model

1．3．2 Common Cost Functions

1．3．3 Risk Assessment

1．4 Linear Minimum Mean Squared Error Estimation

1．4．1 Estimation Criterion

1．4．2 Orthogonality Principle

1．5 Performance Measure of Estimators

1．6 Cramer-Rao Bound

1．7 Comparisons of Several Estimation Methods

1．8 Bayesian Revolution in Big Data Era

1．9 Summary

Appendix 1．1： CRB for Vector Parameter Estimation Under the Conditions of General Distribution

Appendix 1．2： CRB for Vector Parameter Estimation Under the Conditions of Gaussian Distribution

References

2 Basic Principles of the RELAX Estimation Algorithm

2．1 Introduction

2．2 Linear Least Squares Estimation

2．2．1 Ordinary Least Squares Solution

2．2．2 Total Least Squares Solution

2．3 Nonlinear Least Squares Estimation

2．3．1 Problems that Can Be Simplified

2．3．2 Conventional Iterative Algorithm

2．3．3 Cyclic Minimizer

2．4 RELAX Estimation Method

2．4．1 RELAX Algorithm for Multiple Sinusoidal Parameter Estimation

2．4．2 RELAX Algorithm for Multiple General Signal Parameter Estimation

2．5 Summary

References

3 Application of RELAX in Line Spectrum Estimation

3．1 Introduction

3．2 Sinusoidal Signal Parameter Estimation

3．2．1 Hybrid Spectral Estimation of One-Dimensional Sinusoidal Signals

3．2．2 Hybrid Spectral Estimation of Two-Dimensional Sinusoidal Signals

3．2．3 Experimental Results

3．3 Exponential Decay Sinusoidal Signal Parameter Estimation

3．3．1 Data Model

3．3．2 DRELAX Algorithm

3．3．3 Experimental Results

3．4 Arbitrary Envelope Sinusoidal Signal Parameter Estimation

3．4．1 Data Model

3．4．2 Parameter Estimation of a Single Signal

3．4．3 Ambiguous Problem of Multiple Signals

3．4．4 Experimental Results

3．5 Chapter Summary

Appendix 3．1： CRB for Sinusoidal Signal Parameter Estimation

Appendix 3．2： CRB for Exponentially Decaying Sinusoidal Signal Parameter Estimation

Appendix 3．3： CRB for Arbitrary Envelope Sinusoidal Signal Parameter Estimation

References

4 Application of RELAX in Time Delay Estimation

4．1 Introduction

4．2 Data Model

4．3 WRELAX Algorithm

4．3．1 Basic Principle

4．3．2 Experimental Results

4．4 Time Delay Estimation for Highly Oscillatory Cost Functions

4．4．1 Hybrid-WRELAX Algorithm

4．4．2 EXIP-WRELAX Algorithm

4．4．3 Experiment Results

4．5 Super Resolution Time Delay Estimation

4．5．1 MODE-WRELAX Algorithm for Complex-Valued Signals

4．5．2 MODE-WRELAX for Real-Valued Signals

4．5．3 Efficient Implementation of MODE-WRELAX

4．5．4 Experimental Results

4．6 Time Delay Estimation with Multiple Look in Colored Gaussian Noise

4．6．1 Data Model

4．6．2 Basic Principle of TWRELAX

4．6．3 Experimental Results

4．7 Chapter Summary

Appendix 4．1： CRB for Time Delay Estimation of Complex-Valued Signals

Appendix 4．2： CRB for Time Delay Estimation of Real-Valued Signals

Appendix 4．3： CRB for Time Delay Estimation with Multiple Look in Colored Gaussian Noise

References

5 Application of RELAX in Direction of Arrival Estimation

5．1 Introduction

5．2 DOA Estimation of Narrowband Signals

5．2．1 Basic Array Processing Concepts

5．2．2 Data Model

5．2．3 Statistic Characteristics of Array Data

5．2．4 NB-RELAX Algorithm

5．2．5 Experimental Results

5．3 DOA Estimation of Wideband Signals

5．3．1 Data Model

5．3．2 WB-RELAX Algorithm

5．3．3 Experimental Results

5．4 Chapter Summary

Appendix 5．1： CRB for DOA Estimation of Narrowband Signals

Appendix 5．2： CRB for DOA Estimation of Wideband Signals

References

6 Application of RELAX in Radar Target Imaging

6．1 Introduction

6．2 Synthetic Aperture Radar Imaging

6．2．1 Data Model

6．2．2 MCCLEAN Autofocus Algorithm and Experimental Results

6．2．3 Semi-parametric SPAR Imaging Algorithm and Experiment Results

6．3 Three-Dimensional Curvilinear SAR Imaging

6．3．1 Data Model

6．3．2 Autofocus and 3D Imaging Method

6．3．3 Experimental Results

6．4 Inverse Synthetic Aperture Radar Imaging

6．4．1 Data Model

6．4．2 AUTOCLEAN Algorithm Based on a Single Dominant Scatter

6．4．3 AUTOCLEAN Algorithm Based on Multiple Dominant Scatters

6．4．4 Experimental Results

6．5 ISAR Imaging of Maneuvering Target

6．5．1 2D Imaging Model for 3D Motion Targets

6．5．2 Range Cell Target Image Reconstructions from Wavenumber Spectral Function

6．5．3 Reconstruction of Target Image Based on Echo Time-Frequency Distribution

6．6 ISAR Imaging Algorithm for Maneuvering Targets

6．6．1 Experimental Results

6．7 Summary

References

7 Other Typical Applications of RELAX

7．1 Introduction

7．2 Application in Radar Target Detection

7．2．1 Air Maneuvering Target Detection Using Airborne Early Warning Phased Array Radar

7．2．2 High Range Resolution Imaging for Ground Moving Targets

7．2．3 Airborne Weather Radar

7．2．4 Ground Penetrating Radar

7．3 Application in GNSS Interference Mitigation

7．3．1 Anti-jamming

7．3．2 Spoofing Suppression

7．3．3 Multipath Suppression

7．4 Application in Cavity Shape Control for Underwater Supercavitation Vehicles

7．5 Application to Compressive Sensing DOA Estimation

7．6 Application to Neuronal Information Demixing in Biomedical Engineering

7．7 Summary

References

作者簡介

Renbiao Wu is Tianjin Professor and the Director of the Tianjin Key Lab for Advanced Signal Processing at Civil Aviation University of China. He received his B.Sc. and M.Sc. in Electrical Engineering from Northwest Polytechnic University in 1988 and 1991，respectively， and his Ph.D. in Electrical Engineering from Xidian University in 1994. He worked in the Imperial College of London， the University of Florida，and Virginia Tech as a Distinguished Research Scholar，Visiting Professor， and Postdoctoral Fellow for 5 years.His research interests include adaptive array signal processing and spectral estimation， especially in regards to their applications in GNSS and radar. He has published over 300 peer-reviewed papers， more than ten books and book chapters. He was the recipient of the Chinese National Outstanding Young Investigator Award in 2003.

　　Qiongqiong Jia is an Associate Professor of the Tianjin Key Lab for Advanced Signal Processing at the Civil Aviation University of China. She received her B.Sc. and M.Sc. from the Civil Aviation Uruversity of China in 2008 and 2011， respectively， and her specialized master degree in navigation engineering from ENAC in France in 2015. Her research interests include adaptive array signal processing and spectral estimation regarding their applications to GNSS. She has published about 20 papers， and co-authored 3 monographs and 2 book chapters.

　　Lei Yang is currently an Associate Professor of Tianjin Key Lab for Advanced Signal Processing at Civil Aviation University of China. He received his B.Sc. and Ph.D. degrees all from Xidian University，Xi'an， China， in Electronical Engineering， respectively.He has worked at School of Electrical and Electronic Engineering of Nanyang Technology University（NTU）， Singapore and Temasek Lab@NTU， Singapore，as a full-time（Postdoctoral）Research Fellow and Research Scientist， respectively， for 4 years. His research interests include radar imaging for stationary scene and moving targets. He has published over 40 academic papers that are all indexed by SCI and EI database. He is now with the Recruitment Programme of Global Experts（the Thousand Young Talents Plan）of Tianjin， China.

　　Qing Feng is a Lecturer of the Tianjin Key Lab for Advanced Signal Processing at the Civil Aviation University of China. She received her M.Sc. from the Civil Aviation University of China in 2005. Her research interests include adaptive array signal pro-cessing and spectral estimation， especially in regards to their applications in radar. She has published 8 papers and co-authored two books.