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DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 李枝宏(Ju-Hong Lee) | |
dc.contributor.author | Hao-Hsiang Chan | en |
dc.contributor.author | 詹皓翔 | zh_TW |
dc.date.accessioned | 2021-06-13T15:30:22Z | - |
dc.date.available | 2009-07-24 | |
dc.date.copyright | 2008-07-24 | |
dc.date.issued | 2008 | |
dc.date.submitted | 2008-07-15 | |
dc.identifier.citation | [1] 李永定 2000, 利用信號週期恆定特性之可適性陣列信號處理. 國立台灣大學電信工程學研究所碩士論文
[2] Lee, Y. T., Lee, J.H & Shih, W.H 2000, ‘Efficient Robust Adaptive Beamforming for Cyclostationary Signals’, Signal Processing, vol. 48, no. 7, pp. 1893-1901. [3] Lee, Y. T & Lee, J.H 1999, ‘Robust Adaptive Array Beamforming for Cyclostationary Signals Under Cycle Frequency Error’, IEEE Trans. on Antennas and Propagation, vol.AP-47, pp.233-241. [4] Lee, Y. T & Lee, J.H 2001, ‘Robust Adaptive Array Beamforming with Random Error in Cycle Frequency’, IEEE Proceedings-Radar, Sonar and Navigation, vol.148, no.4, pp.193-199. [5] Castedo, L & Figueiras, A.R 1995, ‘An Adaptive Beamforming Technique Based on Cyclostationary Signal Properties’, IEEE Trans. Signal Process, vol.43, pp. 1637–1650. [6] Gardner, W.A 1991, ‘Exploitation of Spectral Redundancy in Cyclostationary Signals. Signal Processing Magazine, IEEE. vol. 8, no.2 , pp.14-36. [7] Adlard, J.F 2000, ‘Stationarity, Cyclostationarity and Spectral Correlation’, in JF Adlard, Frequency Shift Filtering for Cyclostationary Signals, D. Phil Thesis, University of York. pp. 12-41. [8] Yu, S. J & Lee, J. H 1996, ‘Adaptive Array Beamforming for Cyclostationary Signals’, Antennas and Propagation, vol. 44, no. 7, pp. 943-953. [9] L. Izzo & Napolitano 2002, ‘Linear Time-Variant Transformations of Generalized Almost Cyclostationary Signals, Part I: Theory and method’, Signal Processing, vol. 50, pp. 2947-2961. [10] Zhang, J., Liao, G & Wang, J 2004, ‘A Novel Robust Adaptive Beamforming for Cyclostationary Signals’, IEEE 7th Int. Conf on Signal Processing, vol. 1, pp. 339–342. [11] Park, S.Y & Kim, K.M 1999, ‘An Adaptive Array Beamforming Technique Using Cyclostationarity’, TENCON 99. Proceedings of the IEEE Region 10 Conference, vol.12, pp. 1319-1322. [12] Chevalier, P & Maurice, A 1997, ‘Constrained Beamforming for Cyclostationary Signals’, ICASSP, Munich, Germany, pp. 3789-3792. [13] Cox, H., Zeskind, R. M & Owen, M. H 1987, ’Robust Adaptive Beamforming’, IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-35, pp. 1365-1376. [14] Tang, H., Wong, K.M., Gershman, A.B & Vorobyov, S 2002, ‘Blind Adaptive Beamforming for Cyclostationary Signals with Robustness Against Cycle Frequency Mismatch’, IEEE Sensor Array and Multichannel Signal Processing Workshop, Rosslyn, VA, USA, pp. 18–22. [15] Markhi, H. El., Haibala, M. M. O., Mrabti, F., Charge, P & Zouak, M 2007, ‘An Improved Cyclic Beamforming Method for Signal DOA Estimation’, Signal, Image and Video Processing, vol. 1, no.3, pp. 1863-1703. [16] Gardner, W.A. & Franks, L.E 1975, ‘Characterization of Cyclostationary Random Signal Process’, IEEE Transactions on Information Theory, vol.21, no.1, pp. 4–14. [17] Agee, B. G., Schell, S. V. & Gardner, W. A 1990, ‘Spectral Self-Coherence Restoral: A New Approach to Blind Adaptive Signal Extraction Using Antenna Arrays’, Proc. IEEE, vol. 78, pp. 753-766. [18] Biedka, T. E 1993, ‘Subspace constrained SCORE algorithms’, Asilomar Conf. Signals, Systems, and Computers, pp. 716-720. [19] Jafari, M.G., Alty, S.R. & Chambers, J.A 2004, ‘New Natural Gradient Algorithm for Cyclostationary Sources’, Vision, Image and Signal Processing, IEE Proceedings, vol. 151, no. 1, pp 62-68. [20] Le, D., Wu, R., Su, Z & Feng, Q 2006, ‘A Novel Robust Cyclic Adaptive Beamforming Algorithm’, Signal Processing of the 8th International Conference, vol.1. [21] Liu, H.G., Liao, G.S., Zhang, J & Hu, J 2005, ‘Robust Blind Adaptive Beamforming For Cyclostationary Signals’, Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, vol. 1, pp. 346- 349. [22] Du, K.-L & Swamy, M.N.S 2004, ‘Simple and Practical Cyclostationary Beamforming Algorithms’, Vision, Image and Signal Processing, IEE Proceedings, vol. 151, no.3, pp.175- 179. [23] Castedo, L., Tseng, C.Y., Figueiras-Vidal, A. R & Griffiths, L.J 1994, ‘Linearly-constrained Adaptive Beamforming Using Cyclostationary Signal Properties’, Acoustics, Speech, and Signal Processing, vol.4, pp.249-252. [24] Peng, J., Ye, Z & Xu, X 2006, ‘A Novel Robust Cyclostationary Beamformer Based On Conjugate Gradient Algorithm’, Communications, Circuits and Systems Proceedings, vol. 2, pp. 777-780. [25] Li, H. S., He, Y & Yang, R 2005,’A Neural Blind Beamformer For Cyclostationary Signals’, Wireless Communications and Applied Computational Electromagnetics, pp. 345- 348. [26] Ueng, F.B & Yu, S.J 2005, ‘A New Implementation Approach for Cyclostationary Signal-Based Adaptive Arrays’, Wireless Communications and Applied Computational Electromagnetics, pp. 979- 982. [27] Wu, Q & Wong, K.M 1996, ‘Blind Adaptive Beamforming for Cyclostationary Signals’, Signal Processing, IEEE, vol. 44, no.11, pp.2757-2767. [28] Jin, H.E., Zhong L.I.U & Wong, K.T 2007, ‘Linearly-Constrained Minimum-“Geometric Power”Adaptive Beamforming Using Logarithmic-Moments of Data Containing Heavy-Tailed Noise of Unknown Statistics’, Antennas and Wireless Propagation Letters, IEEE, vol. 6, pp. 600-603. [29] Gardner, W. A & Franks, L. E 1975, ‘Characterization of Cyclostationary Random Signal Process’, IEEE Transactions On Information Theory, vol. 21, no.1, pp.4-14. [30] Jianhui, P & Zhongfu, Y 2005, ‘Adaptive Cyclostationary Beamforming Based On Conjugate Gradient Algorithm’, Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, vol. 2, pp.1030- 1032. [31] Lee, J & Lee, Y 1996, ‘Adaptive Beamforming Using Cyclic Signals in The Presence of Cyclefrequency Error’, Antennas and Propagation Society International Symposium, vol.2, pp. 1180-1183. [32] Ioannides, P & Balanis, C. A 2005, ‘Uniform circular arrays for smart antennas’, IEEE Antennas and Propagation Magazine, vol. 47, no. 4, pp.192–206. [33] Compton, R.T 1988, Adaptive antennas: concepts and Performance, Prentice Hall, NJ. [34] 石文昊 1998, 在非理想條件下利用週期恆定特性之強健式波束成型技術. 國 立台灣大學電信工程學研究所碩士論文 [35] Moon, T. K & Stirling, W. C 2000, Mathematical Methods and Algorithms for Signal Processing, Prentice Hall, NJ. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37500 | - |
dc.description.abstract | 本論文提供了一個適當的方法來解決在強健式的可適性陣列天線信號處理上因為都卜勒效應所產生的誤差問題。藉由信號的週期性特性,我們可以有效率的接收需要的信號而不使用到信號的方位角(DOA)。傳統接收週期信號的方法,如LS-SCORE、CAB皆能良好接收,但相對而言,當在接收週期頻率時,所欲設定接收的週期頻率和信號發射的頻率有些微不同,便會造成嚴重的衰減,也因此使得理論無法正常運作。在過去文獻中提到使用不同的方法來解決週期頻率誤差(CFE)的問題,但除了收斂速度較慢外,複雜度也相對增加了不少。因此本論文中提出方法在修正週期誤差頻率時能夠較快速收斂,且效能相較之下也有較好的表現。其利用最大化設定的目標函數的方法,可以有效找尋到正確的週期頻率,使得基於信號週期性的可適性陣列天線能運作更良好。
此外,在電信領域的實際應用上,常常使用多信號的接收,被提出過的論文研究中皆是接收具有相同週期頻率的信號,故本研究提出一次接收多個週期頻率的信號方法,以期能更進一步降低硬體的負擔並節省更多的運算時間。 | zh_TW |
dc.description.abstract | This essay aims to provide a proper method to solve the error problem of the cycle frequency caused by Doppler Effect while dealing with robust adaptive beamforming for cyclostationary signals. The desired signals with cyclostationarity can be received efficiently without requiring the direction of Arrival (DOA). It is argued that some traditional methods such as LS-SCORE [17] and CAB [27] algorithms can help in receiving signals properly. However, if there is a small mismatch in the cycle frequency of the desired signal, these algorithms could suffer from severe performance degradation. According to previous researches [2] [21], LS-SCORE and CAB were proved to solve the problem of the cycle frequency error (CFE), but they seem to suffer from slow convergence speed and complexity. Therefore, one possible solution of this issue is to consider using the method proposed in this essay that could find the correct frequency error faster. Also this method has been proved as an improvement with better performance comparing to LS-SCORE algorithm.
In many practical applications of telecommunication, the system usually receives multiple signals at the same time. This essay also attempts to demonstrate a proper algorithm which allows receiving different cycle frequencies at the same time in order to release the loading of the hardware and save more processing time in adaptive array beamforming. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T15:30:22Z (GMT). No. of bitstreams: 1 ntu-97-R95942095-1.pdf: 1498737 bytes, checksum: 78fe783869415245b1a29c559ed30017 (MD5) Previous issue date: 2008 | en |
dc.description.tableofcontents | 摘要………………………………………………………………………………... I
Abstract…..………………………………………………………………………... II 目錄………………………………………………………………………………. III 第一章 緒論….………………………………………………………………….. 1 1.1研究背景………..…………………………………………………………. 1 1.2研究動機…………………………………………………………………. 2 1.3論文之主要貢獻…………………………………………………………. 3 1.4論文架構…………………………………………………………………. 3 第二章 週期性陣列信號處理之數學架構與基本概念……………………….. 4 2.1天線陣列架構…..…………………………………………………………. 4 2.1.1線性陣列天線架構………………………………….……………… 4 2.1.2圓形陣列天線架構………………………………….……………… 9 2.2自相關矩陣之特性..……………………………………….…………….. 11 2.2.1自相關矩陣之數學定義…………………………….…………….. 12 2.2.2自相關矩陣之特徵分解…………………………….…………….. 14 2.3週期信號之特性..………………………………………….…………….. 15 2.3.1週期恆定性質……………………………………….…………….. 16 2.3.2週期之自相關函數………………………………….…………….. 16 2.3.3時域相關係數………………………………….………………….. 20 2.4週期信號之陣列處理技術..……………………………….…………….. 22 2.4.1 LS-SCORE 之理論技術…………………………........………….. 22 2.4.2 CAB之相關理論技術………………….…………………………. 23 2.4.2.1 CAB技術…………………………..……………..………… 23 2.4.2.2 C-CAB技術 ...…………………..…..………...…………… 25 2.4.2.3 Robust-CAB 技術..…………………..………...…………... 25 第三章 結合SCORE和CAB的週期信號之陣列處理技術………………… 28 3.1簡介……………..………………………………………………………... 28 3.2理論步驟………..………………………………………………………... 28 3.2.1針對所須接收信號的處理………………………………………... 29 3.2.2使用最大相關性技術增進權重效能……………………………... 30 3.2.3干擾與雜訊信號消除....…………………………………………... 31 3.3接收多個不同週期頻率信號..…………………………………………... 33 3.3.1針對多個接收信號的變化....……………………………………... 33 3.3.2尋找信號能量與自相關矩陣……………………………………... 37 3.3.3多信號CAB演算法之模擬..……………………………………... 39 3.4實驗模擬……………………..…………………………………………... 40 3.4.1陣列天線之效能比較....…………………………………………... 40 3.4.2實驗模擬比較....…………………………………………………... 41 3.5結論……………………..………………………………………………... 77 第四章 在有週期頻率誤差情況下之解決方法………………………………. 78 4.1簡介……………..………………………………………………………... 78 4.2有效的目標函數..………………………………………………………... 78 4.2.1最大化輸出能量……....…………………………………………... 78 4.2.2限制條件下最小化輸出能量……………………………………... 79 4.3 Steepest-Decent修正頻率誤差..……………………………….………... 85 4.4目標函數的遞迴運算………...……………………………….…..……... 85 4.4.1最大化輸出能量修正式…………………………………………... 86 4.4.2限制條件下的最小化輸出能量修正式…………………………... 87 4.5針對多信號的修正方式……...……………………………….…..……... 87 4.5實驗模擬……………………..…………………………………………... 89 4.6結論……………………..………………………………………………. 103 第五章 遞迴修正週期頻率誤差之收斂性證明…………….………………. 104 5.1簡介……………..………………………………………………………. 104 5.2目標函數之初步分析…. ………………………………………………. 105 5.2.1限制條件下之最小化能量之目標函數分析………………….… 105 5.2.2最大化能量之目標函數分析……………………………….…… 107 5.3 BPSK信號模型..……….………………………………………………. 108 5.3.1目標函數針對週期頻率的微分結果……………………….…… 108 5.3.2互相關矩陣針對週期頻率的微分結果…………………….…… 111 5.4收斂性證明……..…………………………………………………….… 113 5.5滿足收斂之不等式條件分析...………………………………………… 119 5.6模型一之條件不等式分析…...………………………………………… 120 5.7結論……….……………..……………………………………………… 126 第六章 總結與未來研究方向…………………………………………...…… 127 參考文獻………………………………………………………………………... 128 | |
dc.language.iso | zh-TW | |
dc.title | 在非理想環境下利用信號之週期穩態特性之陣列天線信號處理 | zh_TW |
dc.title | Adaptive Array Signal Processing using Cyclostationary property
under Non-ideal Situations | en |
dc.type | Thesis | |
dc.date.schoolyear | 96-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 王晉良,陳巽璋 | |
dc.subject.keyword | 陣列天線,週期信號,頻率誤差, | zh_TW |
dc.subject.keyword | NULL | en |
dc.relation.page | 131 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2008-07-15 | |
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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