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1. |
Record Nr. |
UNINA9910829852903321 |
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Autore |
Özdemir Caner |
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Titolo |
Inverse synthetic aperture radar imaging with MATLAB algorithms : with advanced sar/isar imaging concepts, algorithms, and matlab codes / / Caner Özdemir, PhD Mersin University, Mersin, Turkey |
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Pubbl/distr/stampa |
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Hoboken, New Jersey : , : Wiley, , [2021] |
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©2021 |
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ISBN |
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1-5231-4356-8 |
1-119-52139-4 |
1-119-52136-X |
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Edizione |
[Second edition.] |
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Descrizione fisica |
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1 online resource (xxii, 634 pages) : illustrations |
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Collana |
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Wiley series in microwave and optical engineering |
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Disciplina |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Cover -- Title Page -- Copyright Page -- Contents -- Preface to the Second Edition -- Acknowledgments -- Acronyms -- Chapter 1 Basics of Fourier Analysis -- 1.1 Forward and Inverse Fourier Transform -- 1.1.1 Brief History of FT -- 1.1.2 Forward FT Operation -- 1.1.3 IFT -- 1.2 FT Rules and Pairs -- 1.2.1 Linearity -- 1.2.2 Time Shifting -- 1.2.3 Frequency Shifting -- 1.2.4 Scaling -- 1.2.5 Duality -- 1.2.6 Time Reversal -- 1.2.7 Conjugation -- 1.2.8 Multiplication -- 1.2.9 Convolution -- 1.2.10 Modulation -- 1.2.11 Derivation and Integration -- 1.2.12 Parseval's Relationship -- 1.3 Time-Frequency Representation of a Signal -- 1.3.1 Signal in the Time Domain -- 1.3.2 Signal in the Frequency Domain -- 1.3.3 Signal in the Joint Time-Frequency (JTF) Plane -- 1.4 Convolution and Multiplication Using FT -- 1.5 Filtering/Windowing -- 1.6 Data Sampling -- 1.7 DFT and FFT -- 1.7.1 DFT -- 1.7.2 FFT -- 1.7.3 Bandwidth and Resolutions -- 1.8 Aliasing -- 1.9 Importance of FT in Radar Imaging -- 1.10 Effect of Aliasing in Radar Imaging -- 1.11 Matlab Codes -- References -- Chapter 2 Radar Fundamentals -- 2.1 Electromagnetic Scattering -- 2.2 Scattering from PECs -- 2.3 Radar Cross Section -- 2.3.1 Definition of RCS -- 2.3.2 RCS of Simple-Shaped Objects -- 2.3.3 RCS of Complex-Shaped Objects -- 2.4 Radar Range Equation -- 2.4.1 Bistatic Case -- |
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2.4.2 Monostatic Case -- 2.5 Range of Radar Detection -- 2.5.1 Signal-to-Noise Ratio -- 2.6 Radar Waveforms -- 2.6.1 Continuous Wave -- 2.6.2 Frequency-Modulated Continuous Wave -- 2.6.3 Stepped-Frequency Continuous Wave -- 2.6.4 Short Pulse -- 2.6.5 Chirp (LFM) Pulse -- 2.7 Pulsed Radar -- 2.7.1 Pulse Repetition Frequency -- 2.7.2 Maximum Range and Range Ambiguity -- 2.7.3 Doppler Frequency -- 2.8 Matlab Codes -- References -- Chapter 3 Synthetic Aperture Radar -- 3.1 SAR Modes -- 3.2 SAR System Design. |
3.3 Resolutions in SAR -- 3.4 SAR Image Formation -- 3.5 Range Compression -- 3.5.1 Matched Filter -- 3.5.1.1 Computing Matched Filter Output via Fourier Processing -- 3.5.1.2 Example for Matched Filtering -- 3.5.2 Ambiguity Function -- 3.5.2.1 Relation to Matched Filter -- 3.5.2.2 Ideal Ambiguity Function -- 3.5.2.3 Rectangular-Pulse Ambiguity Function -- 3.5.2.4 LFM-Pulse Ambiguity Function -- 3.5.3 Pulse Compression -- 3.5.3.1 Detailed Processing of Pulse Compression -- 3.5.3.2 Bandwidth, Resolution, and Compression Issues for LFM Signal -- 3.5.3.3 Pulse Compression Example -- 3.6 Azimuth Compression -- 3.6.1 Processing in Azimuth -- 3.6.2 Azimuth Resolution -- 3.6.3 Relation to ISAR -- 3.7 SAR Imaging -- 3.8 SAR Focusing Algorithms -- 3.8.1 RDA -- 3.8.1.1 Range Compression in RDA -- 3.8.1.2 Azimuth Fourier Transform -- 3.8.1.3 Range Cell Migration Correction -- 3.8.1.4 Azimuth Compression -- 3.8.1.5 Simulated SAR Imaging Example -- 3.8.1.6 Drawbacks of RDA -- 3.8.2 Chirp Scaling Algorithm -- 3.8.3 The ω-kA -- 3.8.4 Back-Projection Algorithm -- 3.9 Example of a Real SAR Imagery -- 3.10 Problems in SAR Imaging -- 3.10.1 Range Migration and Range Walk -- 3.10.2 Motion Errors -- 3.10.3 Speckle Noise -- 3.11 Advanced Topics in SAR -- 3.11.1 SAR Interferometry -- 3.11.2 SAR Polarimetry -- 3.12 Matlab Codes -- References -- Chapter 4 Inverse Synthetic Aperture Radar Imaging and Its Basic Concepts -- 4.1 SAR versus ISAR -- 4.2 The Relation of Scattered Field to the Image Function in ISAR -- 4.3 One-Dimensional (1D) Range Profile -- 4.4 1D Cross-Range Profile -- 4.5 Two-Dimensional (2D) ISAR Image Formation (Small Bandwidth, Small Angle) -- 4.5.1 Resolutions in ISAR -- 4.5.1.1 Range Resolution -- 4.5.1.2 Cross-Range Resolution: -- 4.5.2 Range and Cross-Range Extends -- 4.5.3 Imaging Multibounces in ISAR -- 4.5.4 Sample Design Procedure for ISAR. |
4.5.4.1 ISAR Design Example #1: "Aircraft Target -- 4.5.4.2 ISAR Design Example #2: "Military Tank Target -- 4.6 2D ISAR Image Formation (Wide Bandwidth, Large Angles) -- 4.6.1 Direct Integration -- 4.6.2 Polar Reformatting -- 4.7 3D ISAR Image Formation -- 4.7.1 Range and Cross-Range resolutions -- 4.7.2 A Design Example for 3D ISAR -- 4.8 Matlab Codes -- References -- Chapter 5 Imaging Issues in Inverse Synthetic Aperture Radar -- 5.1 Fourier-Related Issues -- 5.1.1 DFT Revisited -- 5.1.2 Positive and Negative Frequencies in DFT -- 5.2 Image Aliasing -- 5.3 Polar Reformatting Revisited -- 5.3.1 Nearest Neighbor Interpolation -- 5.3.2 Bilinear Interpolation -- 5.4 Zero Padding -- 5.5 Point Spread Function -- 5.6 Windowing -- 5.6.1 Common Windowing Functions -- 5.6.1.1 Rectangular Window -- 5.6.1.2 Triangular Window -- 5.6.1.3 Hanning Window -- 5.6.1.4 Hamming Window -- 5.6.1.5 Kaiser Window -- 5.6.1.6 Blackman Window -- 5.6.1.7 Chebyshev Window -- 5.6.2 ISAR Image Smoothing via Windowing -- 5.7 Matlab Codes -- References -- Chapter 6 Range-Doppler Inverse Synthetic Aperture Radar Processing -- 6.1 Scenarios for ISAR -- 6.1.1 Imaging Aerial Targets via Ground-Based Radar -- 6.1.2 Imaging Ground/Sea Targets via Aerial Radar -- 6.2 ISAR Waveforms for Range-Doppler Processing -- 6.2.1 Chirp Pulse Train -- 6.2.2 Stepped Frequency Pulse Train -- 6.3 Doppler Shift's Relation to |
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Cross-Range -- 6.3.1 Doppler Frequency Shift Resolution -- 6.3.2 Resolving Doppler Shift and Cross-Range -- 6.4 Forming the Range-Doppler Image -- 6.5 ISAR Receiver -- 6.5.1 ISAR Receiver for Chirp Pulse Radar -- 6.5.2 ISAR Receiver for SFCW Radar -- 6.6 Quadrature Detection -- 6.6.1 I-Channel Processing -- 6.6.2 Q-Channel Processing -- 6.7 Range Alignment -- 6.8 Defining the Range-Doppler ISAR Imaging Parameters -- 6.8.1 Image Frame Dimension (Image Extends). |
6.8.2 Range and Cross-Range Resolution -- 6.8.3 Frequency Bandwidth and the Center Frequency -- 6.8.4 Doppler Frequency Bandwidth -- 6.8.5 Pulse Repetition Frequency -- 6.8.6 Coherent Integration (Dwell) Time -- 6.8.7 Pulse Width -- 6.9 Example of Chirp Pulse-Based Range-Doppler ISAR Imaging -- 6.10 Example of SFCW-Based Range-Doppler ISAR Imaging -- 6.11 Matlab Codes -- References -- Chapter 7 Scattering Center Representation of Inverse Synthetic Aperture Radar -- 7.1 Scattering/Radiation Center Model -- 7.2 Extraction of Scattering Centers -- 7.2.1 Image Domain Formulation -- 7.2.1.1 Extraction in the Image Domain: The "CLEAN" Algorithm -- 7.2.1.2 Reconstruction in the Image Domain -- 7.2.2 Fourier Domain Formulation -- 7.2.2.1 Extraction in the Fourier Domain -- 7.2.2.2 Reconstruction in the Fourier Domain -- 7.3 Matlab Codes -- References -- Chapter 8 Motion Compensation for Inverse Synthetic Aperture Radar -- 8.1 Doppler Effect Due to Target Motion -- 8.2 Standard MOCOMP Procedures -- 8.2.1 Translational MOCOMP -- 8.2.1.1 Range Tracking -- 8.2.1.2 Doppler Tracking -- 8.2.2 Rotational MOCOMP -- 8.3 Popular ISAR MOCOMP Techniques -- 8.3.1 Cross-Correlation Method -- 8.3.1.1 Example for the Cross-Correlation Method -- 8.3.2 Minimum Entropy Method -- 8.3.2.1 Definition of Entropy in ISAR Images -- 8.3.2.2 Example for the Minimum Entropy Method -- 8.3.3 JTF-Based MOCOMP -- 8.3.3.1 Received Signal from a Moving Target -- 8.3.3.2 An Algorithm for JTF-Based Rotational MOCOMP -- 8.3.3.3 Example for JTF-Based Rotational MOCOMP -- 8.3.4 Algorithm for JTF-Based Translational and Rotational MOCOMP -- 8.3.4.1 A Numerical Example -- 8.4 Matlab Codes -- References -- Chapter 9 Bistatic ISAR Imaging -- 9.1 Why Bi-ISAR Imaging? -- 9.2 Geometry for Bi-Isar Imaging and the Algorithm -- 9.2.1 Bi-ISAR Imaging Algorithm for a Point Scatterer. |
9.2.2 Bistatic ISAR Imaging Algorithm for a Target -- 9.3 Resolutions in Bistatic ISAR -- 9.3.1 Range Resolution -- 9.3.2 Cross-Range Resolution -- 9.3.3 Range and Cross-Range Extends -- 9.4 Design Procedure for Bi-ISAR Imaging -- 9.5 Bi-Isar Imaging Examples -- 9.5.1 Bi-ISAR Design Example #1 -- 9.5.2 Bi-ISAR Design Example #2 -- 9.6 Mu-ISAR Imaging -- 9.6.1 Challenges in Mu-ISAR Imaging -- 9.6.2 Mu-ISAR Imaging Example -- 9.7 Matlab Codes -- References -- Chapter 10 Polarimetric ISAR Imaging -- 10.1 Polarization of an Electromagnetic Wave -- 10.1.1 Polarization Type -- 10.1.2 Polarization Sensitivity -- 10.1.3 Polarization in Radar Systems -- 10.2 Polarization Scattering Matrix -- 10.2.1 Relation to RCS -- 10.2.2 Polarization Characteristics of the Scattered Wave -- 10.2.3 Polarimetric Decompositions of EM Wave Scattering -- 10.2.4 The Pauli Decomposition -- 10.2.4.1 Description of Pauli Decomposition -- 10.2.4.2 Interpretation of Pauli Decomposition -- 10.2.4.3 Polarimetric Image Representation Using Pauli Decomposition -- 10.3 Why Polarimetric ISAR Imaging? -- 10.4 ISAR Imaging with Full Polarization -- 10.4.1 ISAR Data in LP Basis -- 10.4.2 ISAR Data in CP Basis -- 10.5 Polarimetric ISAR Images -- 10.5.1 Pol-ISAR Image of a Benchmark Target -- 10.5.1.1 The "SLICY" Target -- 10.5.1.2 Fully Polarimetric EM Simulation of SLICY -- 10.5.1.3 LP Pol-ISAR Images of SLICY -- |
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10.5.1.4 CP Pol-ISAR Images of SLICY -- 10.5.1.5 Pauli Decomposition Image of SLICY -- 10.5.2 Pol-ISAR Image of a Complex Target -- 10.5.2.1 The "Military Tank" Target -- 10.5.2.2 Fully Polarimetric EM Simulation of "Tank" Target -- 10.5.2.3 LP Pol-ISAR Images of "Tank" Target -- 10.5.2.4 CP Pol-ISAR Images of "Tank" Target -- 10.5.2.5 Pauli Decomposition Image of "Tank" Target -- 10.6 Feature Extraction from Polarimetric Images -- 10.7 Matlab Codes -- References. |
Chapter 11 Near-Field ISAR Imaging. |
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2. |
Record Nr. |
UNINA9910969639103321 |
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Autore |
Kroonen Guus <1979-> |
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Titolo |
The proto-germanic n-stems : a study in diachronic morphophonology / / Guus Kroonen |
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Pubbl/distr/stampa |
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Amsterdam ; ; New York : , : Rodopi, , 2011 |
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ISBN |
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9786613034564 |
9781283034562 |
1283034565 |
9789042032934 |
9042032936 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (416 pages) |
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Collana |
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Leiden studies in Indo-European ; ; 18 |
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Disciplina |
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Soggetti |
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Germanic languages - Phonology |
Proto-Germanic language - Phonology |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references (p. 357-390) and index. |
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Nota di contenuto |
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Preliminary Material -- Preface -- List of abbreviations -- Preliminary Remarks -- Introduction -- The inflection of the n-stems -- The Proto-Germanic geminates -- Kluge’s law and the n-stems -- Kluge’s law and the directionals -- Consonant gradation in the verb -- A life without Kluge’s law? -- Root ablaut in the n-stems -- The evidence -- Pseudo-ablaut -- Summary and outlook -- Bibliography -- Index of cited forms. |
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Sommario/riassunto |
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The n -stems are an intriguing part of Proto-Germanic morphology. Unlike any other noun class, the n -stems have roots that are |
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characterized by systematic consonant and vowel alternations across the different Germanic dialects. This monograph represents a diachronic investigation of this root variation. It traces back the Germanic n -stems to their Indo-European origin, and clarifies their formal characteristics by an interaction of sound law and analogy. This book therefore is not just an attempt to account for the typology of the Germanic n -stems, but also a case study of the impact that sound change may have on the evolution of morphology and derivation. |
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