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商品簡介
《Adaptive Interference Mitigation in GNSS》向讀者介紹了基於多天線的自適應幹擾抑制技術，用於全球導航衛星系統（GNSS）的時間，做主要的，空間和時空域。由於全球導航衛星系統的性能很容易受到各種有意和無意幹擾的影響，《Adaptive Interference Mitigation in GNSS》詳細地探討了各種幹擾，包括幹擾、高動態幹擾、欺騙、多徑和脈衝幹擾。它提供了一個有價值的參考咨詢工作的研究生和工程師在現場衛星導航信號處理。
作者簡介
Renbiao Wu is the Tianjin Professor and the Director of the Tianjin Key Lab for Advanced Signal Processing at the Civil Aviation University of China. He received his B.Sc. and M.Sc. in Electrical Engineering from the Northwest Polytechnic University in 1988 and 1991 respectively， and his Ph.D. in Electrical Engineering from Xidian University in 1994. He has worked at 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， and ten plus books and book chapters. He is the recipient of the Chinese National Outstanding Young Investigator Award in 2003.
目次
1 Principles of Satellite Navigation System
1．1 Introduction
1．2 Development and Current Status of GNSS
1．2．1 GPS
1．2．2 GLONASS
1．2．3 Galileo
1．2．4 Beidou
1．3 Composition of GNSS
1．4 GNSS Signals
1．4．1 GNSS Signal Structure
1．4．2 Transmission Carrier
1．4．3 Ranging Code
1．4．4 Navigation Message
1．5 GNSS Receiver
1．5．1 Types of GNSS Receivers
1．5．2 Working Principle of GNSS Receivers
1．6 The Impacts of Interference on GNSS Receivers
1．7 Summary
References
2 Jamming Suppression
2．1 Introduction
2．2 Temporal Domain and Frequency Domain Adaptive Filtering．
2．2．1 Temporal Domain Filtering
2．2．2 Frequency Domain Filter
2．2．3 Simulation Results
2．3 Conventional Spatial Domain Adaptive Filtering
2．3．1 Adaptive Array Overview
2．3．2 Statistical Optimal Beamforming
2．3．3 Power Minimization Algorithm
2．4 Spatial Domain Adaptive Filtering Using Periodic Repetitive Characteristic of GNSS Signals
2．4．1 Periodic Repetitive Characteristic of GNSS Signals
2．4．2 SCORE Algorithm
2．4．3 Single-Channel Single-Delay Crosscorrelation Algorithm
2．4．4 Multiple Channel Single Delay Cross Correlation Algorithm
2．4．5 Simulation Results
2．5 Spatial Domain Adaptive Filtering Using Known Spreading Code Information
2．5．1 Least-Squares De-spread Re-spread Multi-target Array．．．
2．5．2 New De-spread Re-spread Jamming Mitigation Algorithm
2．5．3 Simulation Results
2．5．4 Results on Hardware Platform Experiments
2．6 Space Time Adaptive Filtering
2．6．1 Space-Time Processing Data Model
2．6．2 Space-Time Power Minimization Algorithm
2．6．3 Space-Time De-spread Re-spread Algorithm
2．6．4 Reduced Rank Space-Time Adaptive Filtering Algorithm
2．6．5 Impacts on GNSS Signal by Space-Time Processing and Equalization Technique
2．6．6 Simulation Results
2．7 Summary
References
3 High-Dynamic GNSS Jamming Suppression Techniques
3．1 Introduction
3．2 Definition of High-Dynamic and Signal Model
3．3 Null-Widen Spatial Domain Adaptive Filtering Based on Derivative Constraints
3．3．1 Derivative Constraint Power Minimization Algorithm for Uniform Linear Array
3．3．2 Derivative Constraint Power Minimization Algorithm for a Uniform Circular Array
3．3．3 Simulation Results
3．4 Null-Widen Spatial Domain Adaptive Filtering
Based on Covariance Matrix Taper
3．4．1 Mailloux Algorithm
3．4．2 Zatman Algorithm
3．4．3 Laplace Algorithm
3．4．4 Simulation Results
3．5 Null-Widen Space-Time Adaptive Filtering
3．5．1 Space-Time Laplace Null-Widen Algorithm
3．5．2 Reduced Rank Space-Time Null-Widen Algorithm
3．5．3 Simulation Results
3．6 Sparsely Represented Jamming DOA Estimation Algorithm
Based on Small Number of Snapshots
3．6．1 Convex Optimization Algorithm
3．6．2 Greeding Algorithm
3．6．3 Simulation Results
3．7 Summary
References
4 Spoofing Countermeasure Techniques
4．1 Introduction
4．2 Spoofing and the Impacts of Spoofing
4．2．1 Receiver Based Spoofing
4．2．2 Generator Based Spoofing
4．2．3 Spoofing Data Model
4．2．4 Analyses on the Impacts on GNSS Receivers by Spoofing
4．3 Spoofing Detection
4．4 Spoofing Countermeasure
4．4．1 Single Spoofer Suppression
4．4．2 Multiple Spoofer Suppression
4．4．3 Combined Suppression on Jamming and Spoofing
4．4．4 Simulation Results
4．5 Summary
References
5 Multipath Interference Suppression
5．1 Introduction
5．2 Multipath Signal Model and Impact Analyses
5．2．1 Signal Model
5．2．2 Impacts of Multipath Interferences
5．3 Temporal Domain Multipath Interference Suppression '．．
5．3．1 Narrow Correlator Technique
5．3．2 Multipath Estimate Delay-Lock-Loop （MEDLL）
5．3．3 Multipath Interference Suppression Based on WRELAX
5．3．4 Simulation Results
5．4 Spatial Domain Multipath Interference Suppression
5．4．1 Multipath Interference Suppression Based on Antenna Design
5．4．2 Multipath Interference Suppression Based on Low Sidelobe Weighting
5．4．3 Multipath Interference Suppression Based on Spatial Domain Decoupled Parameter Estimation Theory
5．4．4 Simulation Results
5．5 Summary
References
6 Pulse Interference Suppression Techniques
6．1 Introduction
6．2 Conventional Pulse Interference Suppression
6．2．1 Temporal Domain Pulse Blanking Method
6．2．2 Frequency Domain Notch Filtering Algorithm
6．2．3 Temporal-Frequency Hybrid Filtering Algorithm
6．3 Pulse Interference Suppression Based on Parameterized Algorithm
6．4 Pulse Interference Suppression Based on Wavelet Packet Transformation
6．4．1 Wavelet Theory
6．4．2 Suppression Method Based on Wavelet Packet Transformation
6．5 An Integrated Pulse Interference Suppression
6．5．1 The Hybrid Algorithm
6．5．2 Integrated DME Pulse Interference Suppression Method
6．6 Simulation Results
6．7 Summary
References
Erratum to： Adaptive Interference Mitigation in GNSS
1．1 Introduction
1．2 Development and Current Status of GNSS
1．2．1 GPS
1．2．2 GLONASS
1．2．3 Galileo
1．2．4 Beidou
1．3 Composition of GNSS
1．4 GNSS Signals
1．4．1 GNSS Signal Structure
1．4．2 Transmission Carrier
1．4．3 Ranging Code
1．4．4 Navigation Message
1．5 GNSS Receiver
1．5．1 Types of GNSS Receivers
1．5．2 Working Principle of GNSS Receivers
1．6 The Impacts of Interference on GNSS Receivers
1．7 Summary
References
2 Jamming Suppression
2．1 Introduction
2．2 Temporal Domain and Frequency Domain Adaptive Filtering．
2．2．1 Temporal Domain Filtering
2．2．2 Frequency Domain Filter
2．2．3 Simulation Results
2．3 Conventional Spatial Domain Adaptive Filtering
2．3．1 Adaptive Array Overview
2．3．2 Statistical Optimal Beamforming
2．3．3 Power Minimization Algorithm
2．4 Spatial Domain Adaptive Filtering Using Periodic Repetitive Characteristic of GNSS Signals
2．4．1 Periodic Repetitive Characteristic of GNSS Signals
2．4．2 SCORE Algorithm
2．4．3 Single-Channel Single-Delay Crosscorrelation Algorithm
2．4．4 Multiple Channel Single Delay Cross Correlation Algorithm
2．4．5 Simulation Results
2．5 Spatial Domain Adaptive Filtering Using Known Spreading Code Information
2．5．1 Least-Squares De-spread Re-spread Multi-target Array．．．
2．5．2 New De-spread Re-spread Jamming Mitigation Algorithm
2．5．3 Simulation Results
2．5．4 Results on Hardware Platform Experiments
2．6 Space Time Adaptive Filtering
2．6．1 Space-Time Processing Data Model
2．6．2 Space-Time Power Minimization Algorithm
2．6．3 Space-Time De-spread Re-spread Algorithm
2．6．4 Reduced Rank Space-Time Adaptive Filtering Algorithm
2．6．5 Impacts on GNSS Signal by Space-Time Processing and Equalization Technique
2．6．6 Simulation Results
2．7 Summary
References
3 High-Dynamic GNSS Jamming Suppression Techniques
3．1 Introduction
3．2 Definition of High-Dynamic and Signal Model
3．3 Null-Widen Spatial Domain Adaptive Filtering Based on Derivative Constraints
3．3．1 Derivative Constraint Power Minimization Algorithm for Uniform Linear Array
3．3．2 Derivative Constraint Power Minimization Algorithm for a Uniform Circular Array
3．3．3 Simulation Results
3．4 Null-Widen Spatial Domain Adaptive Filtering
Based on Covariance Matrix Taper
3．4．1 Mailloux Algorithm
3．4．2 Zatman Algorithm
3．4．3 Laplace Algorithm
3．4．4 Simulation Results
3．5 Null-Widen Space-Time Adaptive Filtering
3．5．1 Space-Time Laplace Null-Widen Algorithm
3．5．2 Reduced Rank Space-Time Null-Widen Algorithm
3．5．3 Simulation Results
3．6 Sparsely Represented Jamming DOA Estimation Algorithm
Based on Small Number of Snapshots
3．6．1 Convex Optimization Algorithm
3．6．2 Greeding Algorithm
3．6．3 Simulation Results
3．7 Summary
References
4 Spoofing Countermeasure Techniques
4．1 Introduction
4．2 Spoofing and the Impacts of Spoofing
4．2．1 Receiver Based Spoofing
4．2．2 Generator Based Spoofing
4．2．3 Spoofing Data Model
4．2．4 Analyses on the Impacts on GNSS Receivers by Spoofing
4．3 Spoofing Detection
4．4 Spoofing Countermeasure
4．4．1 Single Spoofer Suppression
4．4．2 Multiple Spoofer Suppression
4．4．3 Combined Suppression on Jamming and Spoofing
4．4．4 Simulation Results
4．5 Summary
References
5 Multipath Interference Suppression
5．1 Introduction
5．2 Multipath Signal Model and Impact Analyses
5．2．1 Signal Model
5．2．2 Impacts of Multipath Interferences
5．3 Temporal Domain Multipath Interference Suppression '．．
5．3．1 Narrow Correlator Technique
5．3．2 Multipath Estimate Delay-Lock-Loop （MEDLL）
5．3．3 Multipath Interference Suppression Based on WRELAX
5．3．4 Simulation Results
5．4 Spatial Domain Multipath Interference Suppression
5．4．1 Multipath Interference Suppression Based on Antenna Design
5．4．2 Multipath Interference Suppression Based on Low Sidelobe Weighting
5．4．3 Multipath Interference Suppression Based on Spatial Domain Decoupled Parameter Estimation Theory
5．4．4 Simulation Results
5．5 Summary
References
6 Pulse Interference Suppression Techniques
6．1 Introduction
6．2 Conventional Pulse Interference Suppression
6．2．1 Temporal Domain Pulse Blanking Method
6．2．2 Frequency Domain Notch Filtering Algorithm
6．2．3 Temporal-Frequency Hybrid Filtering Algorithm
6．3 Pulse Interference Suppression Based on Parameterized Algorithm
6．4 Pulse Interference Suppression Based on Wavelet Packet Transformation
6．4．1 Wavelet Theory
6．4．2 Suppression Method Based on Wavelet Packet Transformation
6．5 An Integrated Pulse Interference Suppression
6．5．1 The Hybrid Algorithm
6．5．2 Integrated DME Pulse Interference Suppression Method
6．6 Simulation Results
6．7 Summary
References
Erratum to： Adaptive Interference Mitigation in GNSS
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