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| 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 | |
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| 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.subject | 可適性陣列波束成型 | zh_TW |
| dc.subject | 效能分析 | zh_TW |
| dc.subject | 有限資料點效應 | zh_TW |
| dc.subject | Adaptive array beamforming | en |
| dc.subject | finite sample effect | en |
| dc.subject | performance analysis | 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 | |
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| ntu-102-1.pdf 未授權公開取用 | 7.11 MB | Adobe PDF |
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