Classical and Modern Direction-of-Arrival Estimation

Classical and Modern Direction-of-Arrival Estimation

1st Edition - July 10, 2009

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  • Editors: Engin Tuncer, Benjamin Friedlander
  • Hardcover ISBN: 9780123745248
  • eBook ISBN: 9780080923079

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Description

Classical and Modern Direction of Arrival Estimation contains both theory and practice of direction finding by the leading researchers in the field. This unique blend of techniques used in commercial DF systems and state-of-the art super-resolution methods is a valuable source of information for both practicing engineers and researchers. Key topics covered are: Classical methods of direction finding Practical DF methods used in commercial systems Calibration in antenna arrays Array mapping, fast algorithms and wideband processing Spatial time-frequency distributions for DOA estimation DOA estimation in threshold region Higher order statistics for DOA estimation Localization in sensor networks and direct position estimation

Key Features

  • Brings together in one book classical and modern DOA techniques, showing the connections between them
  • Contains contributions from the leading people in the field
  • Gives a concise and easy- to- read introduction to the classical techniques
  • Evaluates the strengths and weaknesses of key super-resolution techniques
  • Includes applications to sensor networks

Readership

Signal processing researchers, R&D engineers, systems designers and implementers and graduate students.

Table of Contents

  • 1. Wireless Direction-Finding Fundamentals
    Benjamin Friedlander

    1.1. Introduction
    1.2. Problem Formulation
    1.3. Direction-Finding Algorithms
    1.4. Direction-Finding Accuracy
    1.5. Multipath and Co-Channel Interference
    1.6. Direction Finding for Multiple Co-Channel Emitters
    1.7. Discussion

    2. Practical Aspects of Design and Application of Direction-Finding Systems
    Franz Demmel

    2.1. Introduction
    2.2. Application of Direction-Finding Systems
    2.3. Typical System Design—Overview
    2.4. Performance Parameters
    2.5. Antenna Array Design
    2.6. Number of Antenna Elements and Processing Channels
    2.7. Multichannel Receivers
    2.8. Wideband Direction Finding
    2.9. Implementation Aspects of High-Resolution Direction Finding
    2.10. Error Sources
    2.11. Test and Measurement Procedures

    3. Calibration in Array Processing
    Mats Viberg, Maria Lanne, Astrid Lundgren

    3.1. Introduction
    3.2. Data and Error Models
    3.3. Direction-of-Arrival Estimation
    3.4. Auto-Calibration Techniques
    3.5. Calibration Using Sources at Known Positions
    3.6. Array Interpolation Techniques
    3.7. Comparison of Approaches
    3.8. Conclusion

    4. Narrowband and Wideband DOA Estimation for Uniform and Nonuniform Linear Arrays
    T. Engin Tuncer, T. Kaya Yasar, Benjamin Friedlander

    4.1. Introduction
    4.2. Array Models
    4.3. Narrowband Direction-of-Arrival Estimation
    4.4. Wideband Direction-of-Arrival Estimation
    4.5. Conclusion

    5. Search-Free DOA Estimation Algorithms for Nonuniform Sensor Arrays
    Michael Rübsamen, Alex B. Gershman

    5.1. Introduction
    5.2. Background
    5.3. Search-Free Methods for Specific Array Structures
    5.4. Search-Free Methods for Arbitrary Arrays
    5.5. Simulation Results
    5.6. Conclusion

    6. Spatial Time-Frequency Distributions and DOA Estimation
    Moeness Amin, Yimin Zhang

    6.1. Introduction
    6.2. Time-Frequency Distribution
    6.3. Spatial Time-Frequency Distribution
    6.4. Time-Frequency DOA Estimation Techniques
    6.5. Polarimetric Time-Frequency DOA Estimation
    6.6. The Spatial Ambiguity Function and Applications to DOA Estimation
    6.7. Wideband DOA Estimation
    6.8. Time-Frequency Points
    6.9. Conclusion

    7. DOA Estimation in the Small-Sample Threshold Region
    Yuri I. Abramovich, Ben A. Johnson, Xavier Mestre

    7.1. Introduction
    7.2. DOA Estimation in the Threshold Region
    7.3. Expected Likelihood Formulations
    7.4. Use of Expected Likelihood in the MUSIC Threshold Region
    7.5. Subspace Swap and MUSIC Performance Breakdown
    7.6. Subspace Swap and MLE Performance Breakdown
    7.7. Conclusion

    8. High-Resolution DOA Estimation with Higher-Order Statistics
    Pascal Chevalier, Anne Ferréol, Laurent Albera

    8.1. Introduction
    8.2. Observation Model and Data Statistics
    8.3. The 2q-MUSIC Method
    8.4. 2q-MUSIC Identifiability
    8.5. 2q-MUSIC Performance
    8.6. Computer Simulations
    8.7. Extension to Arrays with Diversely Polarized Antennas: The PD-2q-MUSIC Methods
    8.8. Conclusion

    9. Source and Node Localization in Sensor Networks
    Chiao-En Chen, Kung Yao

    9.1. Introduction
    9.2. Source Localization Methods Applied to Sensor Networks
    9.3. Node Localization Methods Applied to Sensor Networks
    9.4. Source Localization Applications Using Sensor Networks

    10. Direct Position Determination: A Single-Step Emitter Localization Approach
    Alon Amar, Anthony J.Weiss

    10.1. Background
    10.2. Localization for Stationary Geometry
    10.3. Localization for Nonstationary Geometry
    10.4. Two-Step versus One-Step Localization
    10.5. Conclusion

Product details

  • No. of pages: 456
  • Language: English
  • Copyright: © Academic Press 2009
  • Published: July 10, 2009
  • Imprint: Academic Press
  • Hardcover ISBN: 9780123745248
  • eBook ISBN: 9780080923079

About the Editors

Engin Tuncer

Temel Engin Tuncer is a Professor in Electrical and Electronics Engineering Department of Middle East Technical University, Ankara, Turkey. His research is focused on sensor array and multichannel signal processing, statistical signal processing and communications. He has a comprehensive experience in direction finding and localization systems. His recent research focuses on beamforming in multi-antenna wireless systems. He is currently the director of the Sensor Array and Multichannel Signal Processing Laboratory in METU and also acts as the general manager of a company, ATARGET, that he has founded.

Benjamin Friedlander

Ben Friedlander is an internationally known expert in the areas of statistical signal processing and its applications to communications and surveillance systems. He has extensive experience spanning over three decades in array processing and direction finding. In recent years his work focused on the use of multiple antennas for wireless communications. Currently he is a professor of electrical engineering at the University of California at Santa Cruz.

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