Ocean Remote Sensing Technologies: High frequency, marine and GNSS-based radar (Radar, Sonar and Navigation)

✍ Scribed by Weimin Huang (editor), Eric W. Gill (editor)

• Publisher: Scitech Publishing
• Year: 2022
• Tongue: English
• Leaves: 755
• Category: Library

✦ Synopsis

A vast array of ocean instrumentation has been developed for research purposes since the middle of the twentieth century, among which remote sensing technologies have become increasingly important. Within this class of instruments, high frequency (HF) surface and skywave radar, microwave marine radar and global navigation satellite systems (GNSS)-based radar have been successfully implemented in gathering information on large tracts of the ocean surface. This book provides a systematic introduction to the principles, state-of-the-art methods and applications of HF surface and sky wave radar, microwave marine radar and GNSS-based radar, as well as an exploration of ongoing challenges in the field.

Ocean Remote Sensing Technologies: High frequency, marine and GNSS-based radar includes 23 chapters that are organized into three parts, mainly according to sensor types. The first part covers work related to HF radar, the second focusses on microwave marine radar, and the third concentrates on GNSS-based radar. Each part consists of an introductory chapter that provides an overview of the corresponding sensor, followed by chapters focussing on fundamental theory, specific applications, or advanced algorithm development. Each of the chapters is self-contained and readers should be aware that there may be across-chapter differences in symbols used for various parameters. The book is intended for a variety of readers in the radar and remotes sensing communities, and content has been selected with a range of interests and backgrounds in mind.

✦ Table of Contents

Halftitle Page
Series Page
Title Page
Copyright
Contents
About the Editors
Preface
1 HF radar in a maritime environment
1.1 HF radar as an ocean remote sensor – introduction
1.1.1 A few fundamentals
1.1.2 Common classes and properties of ocean-mapping HFSWR
1.2 A brief historical perspective on relevant theory and technology
1.2.1 Relevant propagation and scattering theory
1.2.2 Technological advances
1.3 RCSs of the ocean
1.3.1 A technique for developing an RCS of the ocean
1.3.2 Other cross-section results
1.3.3 RCS depictions and discussion
Acknowledgment
References
2 Oceanographic applications of high-­frequency (HF) radar backscatter
2.1 Factors influencing HF backscatter
2.1.1 The electromagnetic spectrum and the speed of light
2.1.2 Factors related to the use of HF transmissions
2.1.3 Impacts of noise and averaging
2.1.4 Relevant time and space scales
2.1.5 Depths observed by HF radar
2.2 Real-time applications of HF radar backscatter
2.2.1 Considerations of real-time applications
2.2.2 Examples of real-time applications
2.3 Example of an intermediate-scale observation
2.4 Process studies using HF radar backscatter
2.5 Conclusions
References
3 Symbiosis of remote sensing and ocean surveillance missions of HF skywave radar
3.1 Modelling the radar observation process
3.1.1 The radar process model
3.1.2 Calibration
3.1.3 Sea clutter modelling I: the direct problem
3.1.4 Sea clutter modelling II: the inverse problem
3.2 Characteristics of OTHR radar missions
3.3 Remote sensing information for enhanced surveillance
3.3.1 Detection
3.3.2 Location
3.3.3 Target classification
3.3.4 Resource management
3.3.5 Tactical intelligence
3.4 Summary
References
4 Sea surface current mapping with HF radar – a primer
4.1 Introduction
4.2 Theory behind radial and vector current derivation from HF radar Doppler spectrum
4.3 Factors affecting current measurements
4.3.1 HF radar system types
4.3.2 Range resolution
4.3.3 Geometrical dilution of precision
4.3.4 Signal propagation and sea state
4.4 HF radar current observations on the West Florida Shelf
4.5 Ongoing HF radar investigations on the West Florida Shelf
4.5.1 An event of offshore working range drop
4.5.2 Average background noise and RFI effect
4.5.3 Atmospheric radio Refractivity (
4.5.4 Wind speed effect
4.6 Summary
Acknowledgment
References
5 An initial evaluation of high-­frequency radar radial currents in the Straits of Florida in comparison with altimetry and model products
5.1 Introduction
5.2 Data sets
5.2.1 High-frequency radar current data and post-processing
5.2.2 Satellite altimetry-derived current products
5.2.3 Numerical model output
5.3 Evaluation metrics
5.4 Comparison with geostrophic currents derived from along-track altimetry
5.5 Comparison with geostrophic currents derived from gridded altimetry
5.6 Comparison with data assimilative model output
5.7 Summary and discussion
Acknowledgment
References
6 Ocean wave measurement
6.1 Introduction to ocean waves
6.2 Waves in the Doppler spectrum
6.2.1 First order
6.2.2 Second order
6.3 Inversion
6.3.1 Approximations and empirical methods
6.3.2 Integral inversion
6.3.3 The constrained iteration method
6.4 Examples and validations
6.4.1 Time series
6.4.2 Statistics
6.4.3 Spatio-temporal wave development
6.5 Sources of error and limitations
6.5.1 Radar data quality
6.5.2 Averaging
6.5.3 The scattering model
6.5.4 Numerical methods
6.6 Summary
Acknowledgment
References
7 A non-­linear method to estimate the wave directional spectrum by HF radar
7.1 Introduction
7.2 Equations of radar cross sections
7.3 Discretization of the integral equation
7.4 Other constraints
7.5 Algorithm
7.6 Procedure of wave spectrum estimation
7.7 Example of wave estimation and issues to be addressed
References
8 HF radar observation of nearshore winds
8.1 Introduction
8.2 Background
8.2.1 Early studies
8.2.2 Wind direction via wave spreading models
8.2.3 Wind speed
8.3 Winds from second-order wave estimates
8.4 Winds from first order
8.5 Discussion
8.5.1 Trade off between first- and second-order wind sensing
8.5.2 Further radar noise issues
8.5.3 Propagation losses
8.5.4 Future directions
8.6 Summary
Acknowledgment
References
9 HF radar in tsunami detection
9.1 The underlying physics
9.2 Observation of surface currents
9.3 Tsunami characteristics
9.3.1 Physics of tsunamis
9.4 HF ocean radar detection of tsunamis
9.4.1 Crossed-loop HF radar systems
9.4.2 Phased-array HF radars
9.5 Definition of a hazardous tsunami
9.6 Discussion and summary
9.6.1 Oblique tsunamis
9.6.2 Maximising the alert period
9.6.3 Achieving surface current resolution
9.7 Conclusion
Acknowledgment
References
10 High-­frequency surface wave radar for target detection
10.1 Introduction to high-frequency surface wave radar basics
10.2 HFSWR system configurations
10.2.1 Bistatic c2onfiguration
10.2.2 Monostatic
10.3 HFSWR for target detection
10.4 Radar power budget
10.4.1 Radar range equation for a noise-limited environment
10.4.2 Radar range equation for an ocean clutter limited environment
10.5 Ocean clutter
10.6 Surface wave propagation
10.7 Maximum detection range
10.8 External noise
10.8.1 Manmade noise
10.8.2 Atmospheric noise level
10.8.3 Galactic noise
10.9 Interference and clutter
10.9.1 External interference
10.9.2 Self interference (clutter)
10.9.3 Ionospheric clutter
10.9.4 Ionospheric clutter scattering modes
10.9.5 Range wrap clutter mitigation
10.9.6 Meteor clutter
10.10 Radar cross section at HF
10.10.1 Definition of RCS at HF
10.10.2 RCS aspect angle dependency
10.10.3 RCS sea state dependency
10.10.4 RCS and stealth
10.10.5 Modelling radar cross section of vessels
10.10.6 RCS of large vessel
10.10.7 RCS of medium vessel
10.10.8 RCS of small vessel
10.10.9 RCS of very small vessels
10.11 Resolution
10.12 Accuracy of estimates
10.13 HFSWR and cognitive sensing
10.14 Challenges and ongoing research
References
11 Introduction to ocean remote sensing with marine radars
11.1 Marine radar ocean observing instrumentation
11.1.1 Hardware
11.1.2 Software
11.2 Applications
11.2.1 Waves
11.2.2 Currents
11.2.3 Bathymetry
11.2.4 Winds
11.3 Recent developments included in this book
11.3.1 Chapter 12: Observation of sea surface waves by noncoherent X-band marine radar
11.3.2 Chapter 13: Wavelet-based methods to invert sea surfaces and bathymetries from X-band radar images
11.3.3 Chapter 14: Wave field reconstruction using orthogonal decomposition of Doppler velocities
11.3.4 Chapter 15: Current mapping from the wave spectrum
11.3.5 Chapter 16: Bathymetry (and current) retrieval: phase-based method
11.3.6 Chapter 17: Wind parameter measurement using X-band marine radar images
References
12 Observation of sea surface waves by noncoherent X-­band marine radar
12.1 Introduction
12.2 FFT-based algorithms
12.2.1 Retrieval of wave spectrum
12.2.2 Estimation of wave parameters
12.2.3 Modulation transfer function
12.2.4 Example
12.3 The algorithm based on EOF analysis
12.3.1 EOF decomposition
12.3.2 Estimation of wave parameters
12.3.3 Physical interpretation of modes
12.3.4 Discussion of mode choice for SWH estimation
12.3.5 Example and validation
12.4 Summary
References
13 Wavelet-­based methods to invert sea surfaces and bathymetries from X-­band radar images
13.1 Simulation of the sea surface elevation and radar images over a laterally uniform bottom profile
13.2 Direct and inverse 2D Continuous Wavelet Transform
13.3 The 2D Wavelet-based Surface Reconstruction method
13.4 Bathymetry reconstruction technique
13.5 Conclusions
Acknowledgment
References
14 Wave field reconstruction using orthogonal decomposition of Doppler velocities
14.1 Potential limitations of the FFT-based wave field processing
14.2 Proper orthogonal decomposition for wave field reconstruction
14.2.1 Data
14.2.2 Proper orthogonal decomposition
14.2.3 Mode selection and physical significance of the POD modes
14.3 Evaluation of POD-based wave field reconstructions
14.3.1 Wave field statistics
14.3.2 Phase resolved wave field comparisons
14.4 Summary and limitations of pod-based wave field reconstructions
References
15 Current mapping from the wave spectrum
15.1 Wave propagation atop background currents
15.2 Appearance of the linear dispersion relation in the spectrum
15.2.1 Practical considerations
15.3 Extracting currents from the spectrum
15.3.1 Least squares method
15.3.2 Normalized scalar product method
15.3.3 Polar current shell method
15.3.4 Algorithm comparison
15.4 Reconstructing depth-dependent flows
15.4.1 Effective depth method
15.4.2 Ha-Campana method
15.4.3 Polynomial effective depth method
15.5 Challenges and further work
15.5.1 Validation
15.5.2 Interpretation of the currents: Stokes drift
15.6 Summary
References
16 Bathymetry (and current) retrieval: phase-­based method
16.1 Introduction
16.2 Brief overview
16.3 Frequency and wavenumber estimates
16.3.1 Fourier series representation of the imaged wave field
16.3.2 Compute the temporal discrete Fourier transform
16.3.3 Compute the cross-spectral coherence spectrum
16.3.4 Extract the dominant cross-spectral eigenvector
16.3.5 Minimize a cost function to estimate wavenumber
16.3.6 Wavenumber estimate quality metrics
16.4 Depth inversion
16.4.1 Problem formulation
16.4.2 Remove temporal water level trends
16.5 Temporal updates
16.5.1 Kalman filter
16.5.2 Moving average
16.6 Revisit current estimation
16.7 Performance
16.8 Summary and future work
References
17 Wind parameter measurement using X-­band marine radar images
17.1 Wind streaks/wind gusts based methods
17.1.1 Local gradient based method
17.1.2 Optical flow based method for wind vector retrieval
17.2 Intensity information and curve fitting based methods
17.2.1 Single curve fitting based algorithm
17.2.2 Two-model curve fitting for rain mitigation
17.2.3 Dual curve fitting for low sea state cases
17.2.4 Significant wave height incorporated curve fitting
17.2.5 Intensity level selection algorithms
17.2.6 Modified ILS
17.2.7 Texture analysis incorporated ILS
17.3 Transform domain and curve fitting based methods
17.3.1 Spectral noise based algorithm
17.3.2 Spectral integration based algorithm
17.3.3 Ensemble empirical mode decomposition based methods
17.4 Nonparametric regression based methods
17.4.1 Neural network based method
17.4.2 Support vector regression based method
17.4.3 Gaussian process regression based method
17.5 Error mitigation
17.6 Conclusions and outlook
References
18 Introduction to remote sensing using GNSS signals of opportunity
18.1 A quick historical review of GNSS-R
18.2 Basic concepts on GNSS
18.2.1 Measurement principle
18.2.2 Structure of the GNSS signals
18.2.3 Received power of the GNSS signals
18.2.4 Atmospheric and ionospheric effects
18.2.5 Satellite navigation systems
18.3 GNSS-R
18.3.1 Spatial resolution
18.3.2 Received power: coherent and incoherent components
18.3.3 The Woodward ambiguity function
18.3.4 GNSS-R observables and techniques
18.3.5 SNR computation
18.4 GNSS-R ocean applications
18.4.1 Ocean Scatterometry
18.4.2 Ocean altimetry
18.4.3 Ocean imaging
18.5. Conclusions
Acknowledgment
References
19 Modeling and simulation of GNSS-­R delay-­Doppler maps over the ocean
19.1 Introduction
19.2 Observation geometry and GNSS signal propagation
19.2.1 Ionospheric delay
19.2.2 Tropospheric delay
19.3 Statistically rough surfaces
19.4 Scattering models for GNSS-R signal simulation
19.4.1 Facet approach
19.4.2 Zavorotny-Voronovich bistatic equation model
19.4.3 Statistical scattering model
19.4.4 Comments to modeling equations
19.5 Simulation of the GNSS-R signal
19.5.1 Observation geometry and specular point calculation
19.5.2 Surface gridding
19.5.3 Simulation with a facet scattering model
19.5.4 Simulation based on the Zavorotny-Voronovich equation
19.5.5 Simulation based on a stochastic model
19.6 Conclusions
References
20 Wind estimation
20.1 Modelling ocean-reflected GNSS signals
20.1.1 Woodward’s Ambiguity Function
20.1.2 The Delay Doppler Map
20.1.3 The Bistatic Radar Equation
20.1.4 Electromagnetic scattering model
20.1.5 Sea surface models
20.2 Processing delay Doppler maps
20.2.1 Feature extraction
20.2.2 Calibration
20.3 Retrieval techniques
20.3.1 Empirical wind speed estimation
20.3.2 Machine Learning
20.3.3 Stare processing
20.4 Summary
20.5 Future challenges
References
21 GNSS-­R ocean altimetry
21.1 Historical overview: technical relevant aspects
21.2 Altimetric tracking point
21.3 Height precision
21.4 Impact of GNSS odes on altimetric performance
21.5 Experimental field campaigns
21.5.1 Ground-based
21.5.2 Air-borne
21.6 Space-borne missions
21.6.1 PARIS IoD
21.6.2 Space-borne Imaging Radar-C
21.6.3 UK TDS-
21.6.4 CYGNSS
21.7 Conclusions
Acknowledgment
References
22 Sea ice sensing using the GNSS-­R technique
22.1 Background and overview
22.2 Sea ice detection
22.2.1 DDM observable based method
22.2.2 Scattering coefficient retrieval based method
22.2.3 Machine learning based method
22.2.4 Empirical model based method
22.3 SIC estimation
22.4 SIT retrieval
22.4.1 Three-layer model
22.4.2 Empirical SIT estimation model
22.4.3 Phase altimetry based SIT retrieval
22.5 Ice altimetry techniques
22.5.1 Waveform based method
22.5.2 Phase based method
22.6 Other applications
22.6.1 Sea ice classification
22.6.2 Sea ice permittivity and roughness retrieval
22.7 Conclusions
References
23 Triton – GNSS Reflectometry Mission in Taiwan
23.1 Introduction
23.2 Triton satellite mission
23.3 GPSR development
23.4 GNSS reflectometry mission payload
23.5 GNSS-R payload validation
23.6 Wind speed retrieval algorithm
23.6.1 The MSS observation principle of the miniature buoy
23.7 Summary
References
Appendix: List of Reviewers
Index
Back Cover