請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/61435
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 李枝宏(Ju-Hong Lee) | |
dc.contributor.author | Yen-Lin Chen | en |
dc.contributor.author | 陳彥霖 | zh_TW |
dc.date.accessioned | 2021-06-16T13:02:58Z | - |
dc.date.available | 2016-08-07 | |
dc.date.copyright | 2013-08-07 | |
dc.date.issued | 2013 | |
dc.date.submitted | 2013-08-06 | |
dc.identifier.citation | [1] B. Widrow, P. E. Mantey, L. J. Griffiths, B. B. Goode, “Adaptive antenna systems,” Proceedings of the IEEE, vol. 55, no. 12, pp. 2143-2159, Dec. 1967.
[2] O. L. Frost, “An algorithm for linearly constrained adaptive array processing,” Proceedings of the IEEE, vol. 60, no. 8, pp. 926-935, Aug. 1972. [3] I. S. Reed, J. D. Mallett, and L. E. Brennan, “Rapid convergence rate in adaptive arrays,” IEEE Transactions on Aerospace and Electronic Systems, vol. AES-10, no. 6, pp. 853-863, Nov. 1974. [4] S. P. Applebaum, “Adaptive arrays,” IEEE Transactions on Antennas and Propagation, vol. 24, no. 5, pp. 585-598, Sep. 1976. [5] R. A. Monzingo and T. W. Miller, Introduction to Adaptive Arrays, John Wiley & Sons, New York, 1980. [6] J. E. Hudson, Adaptive Array Principles, Stevenage, UK, 1981. [7] R. T. Compton, Adaptive Antennas, Prentice Hall, New Jersey, 1988. [8] S. U. Pillai, Array Signal Processing, Springer-Verlag, New York, 1989. [9] H. L. Van Trees, Optimum Array Processing, John Wiley & Sons, New York, 2002. [10] W. Liu and S. Weiss, Wideband Beamforming: Concepts and Techniques. Chichester, U.K.: Wiley, 2010. [11] R. O. Schmidt, “Multiple emitter location and signal parameter estimation,” IEEE Transactions on Antennas and Propagation, vol. 34, no. 3, pp. 276-280, Mar. 1986. [12] R. Roy and T. Kailath, “ESPRIT – estimation of signal parameters via rotational invariance techniques,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37, no. 7, pp. 984-995, Jul. 1989. [13] X. Mestre and M. A. Lagunas, “Finite sample size effect on minimum variance beamformers: optimum diagonal loading factor for large arrays,” IEEE Transactions on Signal Processing, vol. 54, no. 1, pp. 69-82, Jan. 2006. [14] M. Wax and Y. Anu, “Performance analysis of the minimum variance beamformer in the presence of steering vector errors,” IEEE Transactions on Signal Processing, vol. 44, no. 4, pp. 938-947, Apr. 1996. [15] Y. J. Gu, Z.-G. Shi, K. S. Chen, and Y. Li, “Robust adaptive beamforming for a class of Gaussian steering vector mismatch,” Progress In Electromagnetics Research, vol. 81, pp. 315-328, 2008. [16] W.-X. Li, Y.-P. Li, and W.-H. Yu, “On adaptive beamforming for coherent interference suppression via virtual antenna array,” Progress In Electromagnetics Research, vol. 125, pp. 165-184, 2012. [17] Z. Huang, C. A. Balanis, and C. R. Birtcher, “Mutual coupling compensation in UCAs: simulations and experiment,” IEEE Transactions on Antennas and Propagation, vol. 54, no. 11, pp. 3082-3086, Nov. 2006. [18] A. Elnashar, S. M. Elnoubi, and H. A. El-Mikati, “Further study on robust adaptive beamforming with optimum diagonal loading,” IEEE Transactions on Antennas and Propagation, vol. 54, no. 12, pp. 3647-3658, Dec. 2006. [19] D. M. Boroson, “Sample size considerations for adaptive arrays,” IEEE Transactions on Aerospace and Electronic Systems, vol. 16, no. 4, pp. 446-451, Jul. 1980. [20] L. Chang and C.-C. Yeh, “Performance of DMI and Eigenspace-based beamformers,” IEEE Transactions on Antennas and Propagation, vol. 40, no. 11, pp. 1336-1347, Nov. 1992. [21] M. Wax and Y. Anu, “Performance analysis of the minimum variance beamformer,” IEEE Transactions on Signal Processing, vol. 44, no. 4, pp. 928-937, Apr. 1996. [22] B. Widrow, K. M. Duvall, R. P. Gooch, and W. C. Newman, “Signal cancellation phenomena in adaptive antennas: Causes and cures,” IEEE Transactions on Antennas and Propagation, vol. AP-30, no. 3, pp. 469-478, May 1982. [23] L. Yu, W. Liu, and R. Langley, “SINR analysis of the subtraction-based SMI beamformer,” IEEE Transactions on Signal Processing, vol. 58, no. 11, pp. 5926-5932, Nov. 2010. [24] B. D. Carlson, “Covariance matrix estimation errors and diagonal loading in adaptive arrays,” IEEE Transactions on Aerospace and Electronic Systems, vol. 24, no. 4, pp. 397-401, Jul. 1988. [25] A. M. Haimovich and Y. Bar-Ness, “An eigenanalysis interference canceler,” IEEE Transactions on Signal Processing, vol. 39, no. 1, pp. 76-84, Jan. 1991. [26] D. D. Feldman and L. J. Griffiths, “A projection approach for robust adaptive beamforming,” IEEE Transactions on Signal Processing, vol. 42, no. 4, pp. 867-876, Apr. 1994. [27] D. W. Tufts, R. Kumaresan, and I. Kirsteins, “Data adaptive signal estimation by singular value decomposition of a data matrix,” Proceedings of the IEEE, vol. 70, no. 6, pp. 684-685, Jun. 1982. [28] X. Wang and H. V. Poor, “Blind multiuser detection: A subspace approach,” IEEE Transactions on Information Theory, vol. 44, no. 2, pp. 677-690, Mar. 1998. [29] I. P. Kirsteins and D. W. Tufts, “Adaptive detection using low rank approximation to a data matrix,” IEEE Transactions on Aerospace and Electronic Systems, vol. 30, no. 1, pp. 55-67, Jan. 1994. [30] J. S. Goldstein and I. S. Reed, “Reduced-rank adaptive filtering,” IEEE Transactions on Signal Processing, vol. 45, no. 2, pp. 492-496, Feb. 1997. [31] J. S. Goldstein and I. S. Reed, “Subspace selection for partially adaptive sensor array processing,” IEEE Transactions on Aerospace and Electronic Systems, vol. 33, no. 2, pp. 539-544, Apr. 1997. [32] S. D. Berger and B. M. Welsh, “Selecting a reduced-rank transformation for STAP – a direct form perspective,” IEEE Transactions on Aerospace and Electronic Systems, vol. 35, no. 2, pp. 722-729, Apr. 1999. [33] J. S. Goldstein, I. S. Reed, and L. L. Scharf, “A multistage representation of the Wiener filter based on orthogonal projections,” IEEE Transactions on Information Theory, vol. 44, no. 7, pp. 2943-2959, Nov. 1998. [34] J. R. Guerci, J. S. Goldstein, and I. S. Reed, “Optimal and adaptive reduced-rank STAP,” IEEE Transactions on Aerospace and Electronic Systems, vol. 36, no. 2, pp. 647–663, Apr. 2000. [35] D.-H. Tuan and P. Russer, “Signal processing for wideband smart antenna array applications,” IEEE Microwave Magazine, vol. 5, no. 1, pp. 57–67, Mar. 2004. [36] L. L. Rennie, “The TAP III beamforming system,” IEEE Journal of Oceanic Engineering, vol. 6, no. 1, pp. 18–25, Jan. 1981. [37] A. Spriet, M. Moonen, and J. Wouters, “Robustness analysis of multichannel Wiener filtering and generalized sidelobe cancellation for multimicrophone noise reduction in hearing aid applications,” IEEE Transactions on Speech and Audio Processing, vol. 13, no. 4, pp. 487–503, Jul. 2005. [38] B. H. Wang, H. T. Hui, and M. S. Leong, “Optimal wideband beamforming for uniform linear arrays based on frequency-domain MISO system identification,” IEEE Transactions on Antennas and Propagation, vol. 58, no. 8, pp. 2580–2587, Aug. 2010. [39] Y. Zhao, W. Liu, and R. J. Langley, “Adaptive wideband beamforming with frequency invariance constraints,” IEEE Transactions on Antennas and Propagation, vol. 59, no. 4, pp. 1175–1184, Apr. 2011. [40] M. S. Hossain, G. N. Milford, M. C. Reed, and L. C. Godara, “Efficient robust broadband antenna array processor in the presence of look direction errors,” IEEE Transactions on Antennas and Propagation, vol. 61, no. 2, pp. 718–727, Feb. 2013. [41] L. C. Godara, “Application of the fast Fourier transform to broadband beamforming,” Journal of the Acoustical Society of America, vol. 98, no. 1, pp. 230–240, Jul. 1995. [42] R. T. Compton, “The relationship between tapped delay-line and FFT processing in adaptive arrays,” IEEE Transactions on Antennas and Propagation, vol. 36, no. 1, pp. 15–26, Jan. 1988. [43] D. Trim, Calculus for Engineers, Prentice Hall, Toronto, 2008. [44] I. S. Sominskii, The Method of Mathematical Induction, Pergamon, London, 1961. [45] L. J. Griffiths and C. W. Jim, “An alternative approach to linearly constrained adaptive beamforming,” IEEE Transactions on Antennas and Propagation, vol. 30, no. 1, pp. 27-34, Jan. 1982. [46] J. Dmochowski, J. Benesty, and S. Affes, “Direction of arrival estimation using the parameterized spatial correlation matrix,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 15, no. 4, pp. 1327–1339, May 2007. [47] M. Souden, J. Benesty, and S. Affes, “Broadband source localization from an eigenanalysis perspective,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 18, no. 6, pp. 1575–1587, Aug. 2010. [48] Y.-H. Choi, “Performance improvement of adaptive arrays with signal blocking,” IEICE Transactions on Communications, vol. E86-B, no. 8, pp. 2553-2557, Aug. 2003. [49] Y.-H. Choi, “Signal-blocking-based adaptive beamformer with simple direction error correction,” Electronics Letters, vol. 40, no. 8, pp. 463-464, Apr. 2004. [50] C. D. Peckham, A. M. Haimovich, T. F. Ayoub, J. S. Goldstein, and I. S. Reed, “Reduced-Rank STAP performance analysis,” IEEE Transactions on Aerospace and Electronic Systems, vol. 36, no. 2, pp. 664-676, Apr. 2000. [51] B. D. Van Veen, “Eigenstructure based partially adaptive array design,” IEEE Transactions on Antennas and Propagation, vol. 36, no. 3, pp. 357-362, Mar. 1988. [52] A. M. Haimovich, “Asymptotic distribution of the conditional signal-to-noise ratio in an eigenanalysis-based adaptive array,” IEEE Transactions on Aerospace and Electronic Systems, vol. 33, no. 3, pp. 988-997, Jul. 1997. [53] J.-H. Lee and C.-C. Lee, “Analysis of the performance and sensitivity of an eigenspace-based interference canceler,” IEEE Transactions on Antennas and Propagation, vol. 48, no. 5, pp. 826-835, May 2000. [54] B. R. Breed and J. Strauss, “A short proof of the equivalence of LCMV and GSC beamforming,” IEEE Signal Processing Letters, vol. 9, no. 6, pp. 168-169, Jun. 2002. [55] R. Larson, B. H. Edwards, and D. C. Falvo, Elementary Linear Algebra, Brooks Code, CA, 2009. [56] K. S. Miller and J. B. Walsh, Elementary and Advanced Trigonometry, Harper & Brothers, New York, 1962, pp. 212-215. [57] C. Jordan, Calculus of Finite Differences, Chelsea, New York, 1947, pp. 100-107. [58] A. O. Steinhardt, “The PDF of adaptive beamforming weights,” IEEE Transactions on Signal Processing, vol. 39, no. 5, pp. 1232-1235, May 1991. [59] C. D. Richmond, “PDF’s confidence regions, and relevant statistics for a class of sample covariance-based array processors,” IEEE Transactions on Signal Processing, vol. 44, no. 7, pp. 1779-1793, Jul. 1996. [60] W. Liu and S. Ding, “An efficient method to determine the diagonal loading factor using the constant modulus feature,” IEEE Transactions on Signal Processing, vol. 56, no. 12, pp. 6102-6106, Dec. 2008. [61] L. Du, J. Li, and P. Stoica, “Fully automatic computation of diagonal loading levels for robust adaptive beamforming,” IEEE Transactions on Aerospace and Electronic Systems, vol. 46, no. 1, pp. 449-458, Jan. 2010. [62] Y. Li, Y. J. Gu, Z. G. Shi, and K. S. Chen, “Robust adaptive beamforming based on particle filter with noise unknown,” Progress In Electromagnetics Research, vol. 90, pp. 151-169, 2009. [63] L. B. Fertig, “Statistical performance of the MVDR beamformer in the presence of diagonal loading,” in Proceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop, Cambridge, Massachusetts, 2000, pp. 77-81. [64] X. Liu, C. Liu, and G. Liao, “Diagonal loading for STAP and its performance analysis,” in Proceedings of the 6th International Conference on Wireless Communications, Networking and Mobile Computing, Chengdu, China, 2010, pp. 1-4. [65] R. L. Dilsavor and R. L. Moses, “Analysis of modified SMI method for adaptive array weight control,” IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 721-726, Feb. 1993. [66] M. W. Ganz, R. L. Moses, and S. L. Wilson, “Convergence of the SMI and the diagonally loaded SMI algorithms with weak interference,” IEEE Transactions on Antennas and Propagation, vol. 38, no. 3, pp. 394-399, Mar. 1990. [67] S. Haykin, Adaptive filter theory, Prentice Hall, New Jersey, 2002. [68] B. E. Freburger and D. W. Tufts, “Adaptive detection performance of principal components inverse, cross spectral metric and the partially adaptive multistage Wiener filter,” in Proceedings of the 32nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 1998, vol. 2, pp. 1522-1526. [69] P. A. Zulch, J. S. Goldstein, J. R. Guerci, and I. S. Reed, “Comparison of reduced-rank signal processing techniques,” in Proceedings of the 32nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 1998, vol. 1, pp. 421-425. [70] N. Thirion, J.-L. Lacoume, J. Mars, “Resolving power of spectral matrix filtering: a discussion on the links steering vectors/eigenvectors,” in Proceedings of the 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, Corfu, Greece, 1996, pp. 340-343. [71] H. Cox, R. Pitre, and H. Lai, “Robust adaptive matched field processing,” in Proceedings of the 32th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 1998, vol. 1, pp. 127-131. [72] M. Kaveh and H. Wang, Advances in Spectrum Analysis and Array Processing, S. Haykin, Ed. Englewood Cliffs, NJ: Prentice-Hall, 1991. [73] N. Thirion, J. Mars, and J.-L. Lacoume, “Analytical links between steering vectors and eigenvectors,” in European Signal Processing Conference, Trieste, Italy, 1996, pp. 81–84. [74] T. W. Anderson, “Asymptotic theory for principal component analysis,” Annals of Mathematical Statistics, vol. 34, pp. 122-148, 1963. [75] R. P. Gupta, “Asymptotic theory for principal component analysis in the complex case,” Journal of the Indian Statistical Association, vol. 3, pp. 97-106, 1965. [76] P. Stoica and A. Nehorai, “MUSIC, maximum likelihood, and Cramer-Rao bound,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37, no. 5, pp. 720-741, May 1989. [77] J. P. Delmas and Y. Meurisse, “On the second-order statistics of the EVD of sample covariance matrices – application to the detection of noncircular or/and nonGaussian components,” IEEE Transactions on Signal Processing, vol. 59, no. 8, pp. 4017-4023, Aug. 2011. [78] I. M. Johnstone, “On the distribution of the largest eigenvalue in principal components analysis,” Annals of Statistics, vol. 29, no. 2, pp. 295-327, 2001. [79] O. N. Feldheim and S. Sodin, “A universality result for the smallest eigenvalues of certain sample covariance matrices,” Geometric and Functional Analysis, vol. 20, no. 1, pp. 88-123, Apr. 2010. [80] F. Haddadi, M. Malek-Mohammadi, M. M. Nayebi, and M. R. Aref, “Statistical performance analysis of MDL source enumeration in array processing,” IEEE Transactions on Signal Processing, vol. 58, no. 1, pp. 452-457, Jan. 2010. [81] F. Bornemann, “On the numerical evaluation of distributions in random matrix theory: a review,” Markov Processes and Related Fields, vol. 16, pp. 803-866, 2010. [82] B. D. Van Veen and K. M. Buckley, “Beamforming: a versatile approach to spatial filtering,” IEEE ASSP Magazine, vol. 5, no. 2, pp. 4-24, Apr. 1988. [83] W. Liu, “Adaptive wideband beamforming with sensor delay-lines,” Signal Processing, vol. 89, pp. 876-882, 2009. [84] M. Lin, W. Liu, and R. J. Langley, “Performance analysis of an adaptive broadband beamformer based on a two-element linear array with sensor delay-line processing,” Signal Processing, vol. 90, pp. 269-281, 2010. [85] Y. Zhang, K. Yang, M. G. Amin, and Y. Karasawa, “Performance analysis of subband arrays,” IEICE Transactions on Communication, vol. E84-B, no. 9, pp. 2507-2515, Sep. 2001. [86] Y. Zhang, K. Yang, and M. G. Amin, “Subband array implementations for space-time adaptive processing,” EURASIP Journal on Applied Signal Processing, vol. 2005, no. 1, pp. 99-111, 2005. [87] L. C. Godara and M. R. Sayyah Jahromi, “Convolution constraints for broadband antenna arrays,” IEEE Transactions on Antennas and Propagation, vol. 55, no. 11, pp. 3146-3154, Nov. 2007. [88] L. C. Godara and M. R. Sayyah Jahromi, “Limitations and capabilities of frequency domain broadband constrained beamforming schemes,” IEEE Transactions on Signal Processing, vol. 47, no. 9, pp. 2386-2395, Sep. 1999. [89] S. Haykin, Communication systems, John Wiley & Sons, New Jersey, 2001. [90] M. Grigoriu, “Simulation of stationary process via a sampling theorem,” Journal of sound and vibration, vol. 166, no. 2, pp. 301-313, 1993. [91] S. L. Miller and D. Childers, Probability and random processes with applications to signal processing and communications, Elsevier, Boston, 2004. [92] K. M. Buckley and L. J. Griffiths, “Broad-band signal-subspace spatial-spectrum (BASS-ALE) estimation,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 36, no. 7, pp. 953-964, Jul. 1988. [93] H. Messer and Y. Rockah, “On the eigenstructure of the signal-only tempo-spatial covariance matrix of broad-band sources using a circular array,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 38, no. 3, pp. 557-559, Mar. 1990. [94] M. Wax and T. Kailath, “Detection of signals by information theoretic criteria,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 33, no. 2, pp. 387-392, Apr. 1985. [95] R. A. Johnson and D. W. Wichern, Applied Multivariate Statistical Analysis, Prentice Hall, New Jersey, 2007. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/61435 | - |
dc.description.abstract | 在過去數十年中,可適性陣列波束成型技術由於其卓越的干擾消除能力已被廣泛地應用及討論。當接收信號的自相關矩陣及所欲信號的指引向量已知時,波束成型器可根據最小變異無失真響應(minimum variance distortionless response, MVDR)準則,以使陣列輸出之信噪比最大化。然而在實際應用上,這兩項資訊通常無法精確得知並且需估計而求得,當接收信號之自相關矩陣是以有限資料點估計求得時,陣列的效能可能會因此衰減,這種現象我們稱之為有限資料點效應。
在本論文中,我們假設所欲信號的指引向量已知,並探討有限資料點效應對可適性陣列天線效能的影響。首先,我們分析傳統上常用之最小變異無失真響應與廣義旁瓣消除式(generalized sidelobe canceller)波束成型器的效能,由此分析可看出有限資料點效應對傳統波束成型器之影響。接著,我們分析一些現有改進傳統陣列效能之方法 – 信號消除法(signal blocking)與對角線負載(diagonal loading),並探討為何這兩種方法可減緩傳統波束成型器之有限資料點效應。此外,我們也討論數種基於特徵空間之減秩技術(eigenspace-based reduced-rank techniques)應用於可適性波束成型下的效能並且比較它們的優缺點。最後,我們討論兩種寬頻波束成型器 – 時域型波束成型器與頻域型波束成型器於有效資料點效應下之能力,並提出有效的方法改善時域型波束成型器之效能。 | zh_TW |
dc.description.abstract | Adaptive array beamforming has been utilized in a variety of fields in the past decades due to its superior anti-interference ability and high resolution. When the correlation matrix of the received data vector and the steering vector of the desired signal are known exactly, the beamforming weight vector can be obtained by the minimum variance distortionless response (MVDR) solution yielding the maximum output signal to interference-plus-noise ratio (SINR). However, these two quantities are usually unknown and have to be estimated in practical situation. The performance degradation due to the estimation of the correlation matrix of the received data vector is commonly referred to as the finite sample effect in adaptive beamforming.
In this dissertation, we assume the steering vector of the desired signal is known precisely and discuss the finite sample effect on different beamforming techniques. First, the output SINR of the MVDR beamformer under finite sample effect is derived. The equivalence of the generalized sidelobe canceller (GSC) and the MVDR beamformer under finite samples is also proved. In this work, we formulate the problem of the MVDR beamformer with deficient sample size theoretically. Next, the performances of MVDR beamformers with signal blocking and diagonal loading are analyzed. The effects of using signal blocking and diagonal loading techniques on the MVDR beamformer are discussed in detail. Several eigenspace-based reduced-rank techniques including the principal component inverse (PCI), cross-spectral metric (CSM), and modified cross-spectral metric (MCSM) considering finite sample effect are compared. The reasons why the PCI and CSM methods deteriorate in performance and how the MCSM alleviates the finite sample effect are investigated. Finally, the performances of the broadband tapped delay-line (TDL) and discrete Fourier transform (DFT) beamformers with and without finite sample effect are evaluated and compared. The capabilities of the broadband beamformers to address the broadband signals are examined through this work. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T13:02:58Z (GMT). No. of bitstreams: 1 ntu-102-D97942011-1.pdf: 7277413 bytes, checksum: f00a6035a3cf1e3008ac163605c20477 (MD5) Previous issue date: 2013 | en |
dc.description.tableofcontents | 1. Introduction
1.1 Motivation and Historical Perspective……………………………………………………… 1 1.2 Organization of the Dissertation …………………………………………………………… 7 2. Mathematical Preliminaries 2.1 Signal Model ……………………………………………………………… 12 2.2 Narrowband Beamformers 2.2.1 The MVDR Beamformer……………………………… 18 2.2.2 Signal Blocking Technique………………………… ..20 2.2.3 Diagonal Loading Technique………………………………… 21 2.2.4 Eigenspace-based Reduced-rank Techniques………………………. 22 2.3 Broadband Beamformers 2.3.1 TDL-based Beamformers…………………………………………. 24 2.3.2 DFT-based Beamformers……………………………………………… 27 3. Performance Analysis of MVDR and GSC Beamformers 3.1 Introduction………………………………………………………… 34 3.2 The Output SINR of MVDR Beamformers 3.2.1 Output SINR in Terms of Q…………………………………….. 38 3.2.2 Derivation of Q−1……………………………………………………. 39 3.2.3 Output SINR for Two Interferers…………………………………. 40 3.3 The Equivalence of MVDR and GSC Beamformers……………………… 43 3.4 Simulation Results……………………………………………………….. 45 3.5 Conclusion………………………………………………………………. 48 Appendix 3-A……………………………………………………………… 50 Appendix 3-B……………………………………………………………… 51 Appendix 3-C……………………………………………………………… 54 Appendix 3-D……………………………………………………………… 61 Appendix 3-E………………………………………………………………. 65 4. Performance Analysis of MVDR Beamformers with Signal Blocking 4.1 Introduction………………………………………………………………… 79 4.2 The Output SINR of MVDR Beamformers with Signal Blocking 4.2.1 Output SINR in Terms of QB…………………………………………. 82 4.2.2 Derivation of QB −1………………………………………………….. 83 4.2.3 Output SINR for Two Interferers…………………………………. 84 4.2.4 The Duvall Beamformer……………………………………………… 88 4.3 Simulation Results……………………………………………………….. 91 4.4 Conclusion…………………………………………………………………. 95 Appendix 4-A……………………………………………………………….. 97 Appendix 4-B………………………………………………………. 107 Appendix 4-C………………………………………………………. 114 Appendix 4-D………………………………………………………. 135 Appendix 4-E………………………………………………………. 142 Appendix 4-F………………………………………………………. 147 Appendix 4-G……………………………………………………… 152 Appendix 4-H……………………………………………………… 154 Appendix 4-I………………………………………………………. 157 Appendix 4-J……………………………………………………… 158 Appendix 4-K…………………………………………………….. 161 5. Performance Analysis of MVDR Beamformers with Diagonal Loading 5.1 Introduction……………………………………………………….. 183 5.2 The Output SINR of MVDR Beamformers with Diagonal Loading 5.2.1 Output SINR in Terms of Q and QD …………………………… 188 5.2.2 Derivation of QD −1……………………………………………… 190 5.2.3 Output SINR for Two Interferers………………………………. 191 5.3 Discussions Regarding The Theoretical Results 5.3.1 The Characteristic of Pid……………………………………….. 194 5.3.2 The Characteristics of Pc,D…………………………………….. 196 5.3.3 Generalize The Explicit Expressions to The D-sources Scenario…. 198 5.4 Simulation Results………………………………………………………. 200 5.5 Conclusion…………………………………………………………….. 203 Appendix 5-A…………………………………………………………….. 205 Appendix 5-B…………………………………………………………….. 207 Appendix 5-C…………………………………………………………… 229 Appendix 5-D………………………………………………………….. 273 Appendix 5-E………………………………………………………….. 286 Appendix 5-F…………………………………………………………. 291 Appendix 5-G……………………………………………………….. 300 Appendix 5-H…………………………………………………………. 324 Appendix 5-I……………………………………………………………. 333 Appendix 5-J…………………………………………………………… 335 6. Performance Comparison of Eigenspace-based Reduced-rank Beamformers 6.1 Introduction……………………………………………………………….. 349 6.2 The Output Power of Beamformers with Low Ranks………………….. 352 6.3 Projections of Steering Vectors onto Eigenvectors 6.3.1 Relationship between σsk2 and |aiHej|2………………………….. 356 6.3.2 Relationship between |aiHej|2 and …………………. 357 6.4 Critical Values of the Reduced-Rank Techniques 6.4.1 The PCI Method……………………………………………… 359 6.4.2 The CSM Method……………………………………………. 361 6.4.3 The MCSM Method…………………………………………. 363 6.5 Simulation Results……………………………………………………. 364 6.6 Conclusion …………………………………………………………… 369 Appendix 6-A…………………………………………………………… 370 Appendix 6-B…………………………………………………………. 372 Appendix 6-C……………………………………………………….. 374 Appendix 6-D……………………………………………………. 375 Appendix 6-E……………………………………………………….. 379 7. Performance Evaluation of DFT-based beamformers 7.1 Introduction………………………………………………………………… 396 7.2 The Output SINR of DFT-based Beamformers 7.2.1 The DFT-based Beamformer with Block Processing……………….. 399 7.2.2 The DFT-based Beamformer with Sliding Window……………… 404 7.2.3 The Special Case of J=1 and Narrowband Signal Sources………. 405 7.3 Finite Sample Estimation for the Covariance Matrix………………… 406 7.4 Simulation Results……………………………………………………. 409 7.5 Conclusion…………………………………………………………… 415 Appendix 7-A……………………………………………………………. 416 8. Performance Evaluation of TDL-based Beamformers 8.1 Introduction……………………………………………………………… 425 8.2 Performance Metrics of TDL-based Beamformers 8.2.1 Output SINR………………………………………………………. 427 8.2.2 Beam Pattern…………………………………………………….. 428 8.3 Finite Sample Estimation for the Covariance Matrix 8.3.1 Block Processing……………………………………………….. 431 8.3.2 Sliding Window………………………………………………… 431 8.4 A Robust Technique against Finite Sample Effect…………………… 432 8.5 An Approach Based on Maximum SINR Criterion…………….. 434 8.6 Simulation Results……………………………………………………. 437 8.7 Conclusion…………………………………………………………… 442 Appendix 8-A…………………………………………………………. 442 Appendix 8-B………………………………………………………… 445 Appendix 8-C…………………………………………………………. 446 Appendix 8-D…………………………………………………………. 446 Appendix 8-E…………………………………………………………. 447 9. Conclusion and Future Work………………………………………. 454 Bibliography…………………………………………………………………………………… 458 | |
dc.language.iso | en | |
dc.title | 可適性天線陣列波束成型於非完美環境下之效能特徵 | zh_TW |
dc.title | Performance Characteristics of Adaptive Antenna Array Beamforming under Imperfect Environments | en |
dc.type | Thesis | |
dc.date.schoolyear | 101-2 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 陳巽璋,李大嵩,祁忠勇,方文賢,楊家輝 | |
dc.subject.keyword | 可適性陣列波束成型,效能分析,有限資料點效應, | zh_TW |
dc.subject.keyword | Adaptive array beamforming,performance analysis,finite sample effect, | en |
dc.relation.page | 472 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2013-08-06 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
顯示於系所單位: | 電信工程學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-102-1.pdf 目前未授權公開取用 | 7.11 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。