Remote Sensing of Earth Based Radar Objects by A.I. KozlovRemote Sensing of Earth Based Radar Objects by A.I. Kozlov

Remote Sensing of Earth Based Radar Objects

byA.I. Kozlov, L.P. Ligthart, A.I. Logvin

Hardcover | October 12, 2019

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The book concerns with the theory and practice of remote radio sensing applied to detection and classification problems with (polarimetric) radar in microwave scattering propagation channel. The first eight (8) chapters (Part II of the book) deal with theory on remote sensing for classification by (polarimetric) contrast of earth-based radar objects. Part III of the book (chapters 9-14) deals with signal processing aspects of (polarimetric) remote sensing for data obtained from experiments carried out at L and X bands. Theory and experiments are compared and an overview of new areas of research on modeling and verification of detection /classification of radar objects are given in Chapters 15 and 16. In Chapter 17 some experimental results of IRCTR radar polarimetry for atmospheric and earth surface applications are given. Part IV gives the conclusions on applications and the results of the research program described in this book.
Title:Remote Sensing of Earth Based Radar ObjectsFormat:HardcoverDimensions:900 pages, 23.5 × 15.5 × 0.03 inPublished:October 12, 2019Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:1402035144

ISBN - 13:9781402035142

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Table of Contents

Preface xivAcknowledgements xvPART I - INTRODUCTION A Scope of the subject-description of the research program xviB Outline of the book xvii PART II : THEORY ON REMOTE SENSING OF EARTH BASED RADAR OBJECTS (CLASSIFICATION -RADAR CONTRAST) Chapter 1: Classification of radar objectsIntroduction 3 1.2 Traditional classification methods for radar objects 51.2.1 Deterministic methods 51.2.1.1 Decision function method 51.2.1.2 Distance method in the signature space 61.2.2 Stochastic methods 71.2.2.1 Bayes' method 71.2.2.2 Accounting errors of experiments 91.3 Modified classification methods for radar objects using polarization parameters 111.3.1 Deterministic methods 111.3.1.1 Classification based on the radio-wave polarization characteristics 111.3.1.2 Classification based on the radar objects polarization characteristics 111.3.2 Stochastic methods 121.3.2.1 Polarization modified Bayes' method 121.3.2.2 The influence of errors on the determination of the boundaries 201.3.2.3 The influence of PDF errors on the errors in the signature measurement 231.4 Application of polarization-based classification methods 261.4.1 Layered vegetation model 261.4.2 Computational results 311.5 Conclusions 40 Chapter 2: Inverse problem, method and analysis.2.1 Introduction 422.2 Inverse scattering methods 432.2.1 Outline of inversion methods 45Inversion algorithms 47 2.2.2.1 Newton method 472.2.2.2 Gradient method 482.2.2.3 Conjugate gradient method 492.2.2.4 Levenberg-Marquardt method 492.3 Example of an electromagnetic inverse scattering problem 502.4 Examples of inversion: experiments and simulations 562.4.1 Imaging of a bounded object by non-linear inversion in TE scattering 57Imaging of single and multiple buried (underground) objects with 61 inverse scattering and SAR processing.2.4.3 Imaging (2D-3D) of biomedical data 652.4.4 Depolarization effects in inverse scattering problems: an appraisal of basic factors. 722.5 Summary and conclusions 732.5.1 Summary of inversion methods 732.5.2 Summary of results and conclusions 75 Chapter 3: Description of direct and interfering electromagnetic waves inscattering problems.3.1 Introduction 783.2 Main characteristics of radio wave scattering 813.2.1 Phenomenological models 813.2.2 Geometrical models 823.2.3 Statistical models 843.2.3.1 Model 1 843.2.3.2 Model 2 863.2.3.3 Model 3 883.3 The system of independent scatterers 903.3.1 General relations 903.3.2 Completely chaotic orientation of scatterers 933.3.3 Scatterers with predominant horizontal orientation 943.3.4 Scatterers with predominant vertical orientation 953.4 Classification of the forms of Earth surfaces 983.5 Generalized reflection characteristics of Earth surfaces 1003.6 Polarization characteristics of Earth surfaces 1083.6.1 Water surface 1083.6.2 Ground surface 1153.7 Scattering-reflection modeling: summary 1223.7.1 Application 1223.7.2 Verification 1223.8 Conclusions 123  Chapter 4: Relation between electrodynamic characteristics and radar polarizationstate.4.1 Introduction 1244.2 Smooth homogeneous medium 1264.3 Smooth inhomogeneous medium 1374.3.1 General relations 1374.3.2 Exponential layer 1394.3.3 Quadratic layer 1394.3.4 Vertical scanning incidence 1404.3.4.1 Polynomial layer 1404.3.4.2 Linear layer 1414.3.4.3 Parabolic layer 1424.3.4.4 Matching layer 1434.3.4.5 Intermediate layer 1454.3.5 Equation for the scattering matrix elements 1474.4 Rough surfaces 1524.4.1 Scattering matrix for model 1 1544.4.2 Scattering matrix for model 2 1554.4.3 Scattering matrix for model 3 1564.4.4 Scattering matrix for model 4 1574.4.5 Statistical characteristics of the scattering matrix elements 158Relation between eigenvalues, proper polarization basis coordinates and complex permittivity 1654.5.1 Scattering matrix invariants 1654.5.1.1 Smooth homogeneous surface model 1654.5.1.2 Smooth inhomogeneous surface model 1654.5.1.3 Model 1 1664.5.1.4 Model 2 1664.5.1.5 Model 3 1664.5.2 Eigenvalues and proper polarization basis 1674.5.2.1 Model 1 1684.5.2.2 Model 2 1684.6 Conclusions 169Chapter 5: Deterministic and stochastic modeling of objects. 5.1 Introduction 1725.1.1 KLL sphere 1735.2 Deterministic modeling 1745.2.1 Main characteristics of the radar target scattering matrix elements 174 5.2.2 Modeling with use of the KLL sphere 1785.3 Statistical modeling 188 5.3.1 Transformation of the statistical characteristics of the scatteringmatrix elements. 1885.3.1.1 Probability density function (PDF) 1885.3.1.2 Average values and dispersion 1905.3.2 Construction of statistical models of radar targets 1945.3.2.1 The main principle of model synthesis 1945.3.2.2 generalized algorithm for determination of the distribution laws 1955.4 Summary 2065.4.1 Applications 2065.4.2 Verification 2075.4.2.1 Deterministic modeling 2075.4.2.2 Statistical modeling 2075.5 Conclusions 207Chapter 6: Method to increase polarization contrast of radar objects 6.1 Introduction 2096.2 General principles of polarization discrimination of radar objects 2126.3 Radar contrast control 2156.4 Orthogonalization method 2226.4.1 Effect of angle 2276.4.1.1 Uniform distribution of angle 2276.4.1.2 Gaussian distribution of angle 2316.4.2 Effect of signal and interference power characteristics 2346.5 Polarization-compensation method 2386.6 Methods to increase the radar contrast: summary 2436.6.1 Applications 2436.6.2 Verification 2436.7 Conclusions 244 Chapter 7: Accuracy and sensitivity analysis of object parameters. 7.1 Introduction 246Application of Markov filtering for the increase of accuracy and reliability of objects parameters determination 2487.2.1 Problem statement 2487.2.2 Main principles of the Markov message filtering 2517.2.3 Markov filtering of linearly polarized radar signals 2547.2.4 Markov filtering of an elliptically polarized radar signal 261Experimental test of operating performance of non-linear Markov filtering algorithm 2637.4 Description of the equipment 2727.5 Summary 2807.5.1 Applications 2807.5.2 Verification 2807.6 Conclusions 281Chapter 8: Requirements to the accuracy and reliability of the equipment forDetermining objects parameters and signal characteristics 8.1 Introduction 2828.2 The main sources of measurements errors 2848.3 The angle noise 286The polarization algorithms for increasing the accuracy of determining objects coordinates 2878.5 The probabilistic characteristics of fluctuations of signal's angles of arrival 289 8.5.1 The analysis of statistical modeling results 3018.6 The effects of the underlying surface 3038.7 The estimation of the polarization methods efficiency 307Summary 310 8.8.1 Applications 3108.8.2 Verification 3108.9 Conclusions 311     PART III: EXPERIMENTS AND DATA-SIGNAL PROCESSINGChapter 9: Requirements-system specifications-functional diagrams of radar equipment for experiments allowing polarization diagnostics.9.1 Introduction 3129.2 Mode of complete polarization scanning 315Main requirements for radars with varying polarization modes of emitted electromagnetic waves 3179.4 Radar with linear polarization modes 3199.5 Radar with circular polarization mode 322Radar with combined modes of polarization for study of the statistical characteristics of the objects. 3289.7 Radar with combined modes of polarization and with spectral analysis 3339.8 Software for polarization parameters processing 3379.9 Summary 3399.9.1 Applications 3399.9.2 Verification 3409.10 Conclusions 340   Chapter 10: Adaptive algorithms and signal processing.10.1 Introduction 34210.2 Statement of the problem 344Optimal filtering of information and concomitant (non-information) signal parameters. 34610.4 Application of 'separation' algorithm 35310.5 Correlation relations with optimal filtering of polarized signals. 35610.6 Summary 36210.6.1 Application. 36210.6.2 Verification 36310.7 Conclusions 363Chapter 11: Criteria for testing the radar functions. 365Chapter 12: Methods for parameter evaluation. ~415Chapter 13: Measurement campaigns using 1.8 cm and 3.2 cm coherent radar with ~455controlled polarization capabilities. Part I and II.Chapter 14: Part I: Data processing and data analysis of experiments. ~495Part II: Refinement of theory and experiments. ~530Chapter 15: Comparisons between theory and experiments. ~560Chapter 16: Overview and new areas of research on modeling and verification of ~590Earth based radar objects.Chapter 17: Detection and classification obtained by polarimetric radars. 17.1 Introduction: Results obtained from remote sensing of the atmosphere,precipitation, clouds, turbulence, and on earth surface, urban areas, forests. ~650 17.2 Radar remote sensing data for applications in forestry (source: 123 pages)17.3 Cloud measurements with radar (source: 63 pages)17.4 Doppler-polarimetric radar signal processing (source: 72 pages)17.5 Contrast enhancement for depolarizing radar targets (source: 41 pages)17.6 From snowflake to raindrop, Doppler radar observations and simulations ofprecipitation (source: 64 pages)17.7 Ground-based remote sensing of precipitation using a multi-polarized FM-CWDoppler radar (source: 86 pages)17.8 Conclusions ~745   PART IV: CONCLUSIONS Chapter 18: Review of methods and applications of remote sensing ~750Introduction Results of remote sensing applications Comparison-review of the inverse scattering methods analyzed Areas of further developments of remote sensing 18.5 Concluding remarks Appendices A to R. ~770References. ~890