- •Contents
- •Preface
- •1.1 Smart Antenna Architecture
- •1.2 Overview of This Book
- •1.3 Notations
- •2.1 Single Transmit Antenna
- •2.1.1 Directivity and Gain
- •2.1.2 Radiation Pattern
- •2.1.3 Equivalent Resonant Circuits and Bandwidth
- •2.2 Single Receive Antenna
- •2.3 Antenna Array
- •2.4 Conclusion
- •Reference
- •3.1 Introduction
- •3.2 Data Model
- •3.2.1 Uniform Linear Array (ULA)
- •3.3 Centro-Symmetric Sensor Arrays
- •3.3.1 Uniform Linear Array
- •3.3.2 Uniform Rectangular Array (URA)
- •3.3.3 Covariance Matrices
- •3.4 Beamforming Techniques
- •3.4.1 Conventional Beamformer
- •3.4.2 Capon’s Beamformer
- •3.4.3 Linear Prediction
- •3.5 Maximum Likelihood Techniques
- •3.6 Subspace-Based Techniques
- •3.6.1 Concept of Subspaces
- •3.6.2 MUSIC
- •3.6.3 Minimum Norm
- •3.6.4 ESPRIT
- •3.7 Conclusion
- •References
- •4.1 Introduction
- •4.2 Preprocessing Schemes
- •4.2.2 Spatial Smoothing
- •4.3 Model Order Estimators
- •4.3.1 Classical Technique
- •4.3.2 Minimum Descriptive Length Criterion
- •4.3.3 Akaike Information Theoretic Criterion
- •4.4 Conclusion
- •References
- •5.1 Introduction
- •5.2 Basic Principle
- •5.2.1 Signal and Data Model
- •5.2.2 Signal Subspace Estimation
- •5.2.3 Estimation of the Subspace Rotating Operator
- •5.3 Standard ESPRIT
- •5.3.1 Signal Subspace Estimation
- •5.3.2 Solution of Invariance Equation
- •5.3.3 Spatial Frequency and DOA Estimation
- •5.4 Real-Valued Transformation
- •5.5 Unitary ESPRIT in Element Space
- •5.6 Beamspace Transformation
- •5.6.1 DFT Beamspace Invariance Structure
- •5.6.2 DFT Beamspace in a Reduced Dimension
- •5.7 Unitary ESPRIT in DFT Beamspace
- •5.8 Conclusion
- •References
- •6.1 Introduction
- •6.2 Performance Analysis
- •6.2.1 Standard ESPRIT
- •6.3 Comparative Analysis
- •6.4 Discussions
- •6.5 Conclusion
- •References
- •7.1 Summary
- •7.2 Advanced Topics on DOA Estimations
- •References
- •Appendix
- •A.1 Kronecker Product
- •A.2 Special Vectors and Matrix Notations
- •A.3 FLOPS
- •List of Abbreviations
- •About the Authors
- •Index
Discussions and Conclusion |
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DOA algorithms in a real-world application. In this respect, not very much documentation has been seen in the public domain.
References
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[9]Xu, X., Z. Ye, and Y. Zhang, “DOA Estimation for Mixed Signals in the Presence of Mutual Coupling,” IEEE Trans. on Signal Processing, 2010.
[10]Gotsis, K. A., K. Siakavara, and J. N. Sahalos, “On the Direction of Arrival (DOA) Estimation for a Switched-Beam Antenna System Using Neural Networks,” IEEE Trans. on Antennas and Propagations, Vol. 57, No. 5, May 2009, pp. 1399–1411.
[11]Zhao, L., Y. Zhao, and H. Cui, “High Resolution Wideband DOA Estimation Based on Modified MUSIC Algorithm,” Proceedings of 2008 International Conference on Information and Automation, June 20–23, 2008, pp. 20–22.
[12]Yasar, T. K., and T. E. Tuncer, “Wideband DOA Estimation for Nonuniform Linear Arrays with Wiener Array Interpolation,” Proceedings of 2008 IEEE Sensor Array and Multichannel Signal Processing Workshop, July 21–23, 2008, pp. 207–211.
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[14]M. Navarro and M. Najar, “TOA and DOA Estimation for Positioning and Tracking in IR-UWB,” Proceedings of 2007 IEEE International Conference on Ultra-Wideband, September 24–26, 2007, pp. 574–579.
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[16]Wang, G., Y. Pan, and W. Dong, “A New Anti-Interference Preprocess Method for DOA Estimation Based on Uniform Circular Array,” Proceedings of 2006 International Conference on Radar, October 16–19, 2006, pp. 1–4.
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