請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72711
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 蘇柏青 | |
dc.contributor.author | Yi-Ying Huang | en |
dc.contributor.author | 黃譯瑩 | zh_TW |
dc.date.accessioned | 2021-06-17T07:04:13Z | - |
dc.date.available | 2020-07-31 | |
dc.date.copyright | 2019-07-31 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-07-29 | |
dc.identifier.citation | [1] Y. I. Abramovich, N. K. Spencer, and A. Y. Gorokhov. Positive-definite Toeplitz completion in doa estimation for nonuniform linear antenna arrays. ii. partially augmentable arrays. IEEE Transactions on Signal Processing, 47(6):1502–1521, 1999.
[2] M. Babtlett. Smoothing periodograms from time-series with continuous spectra. Nature, 161(4096):686, 1948. [3] S. Bubeck et al. Convex optimization: Algorithms and complexity. Foundations and Trends® in Machine Learning, 8(3-4):231–357, 2015. [4] E. J. Candes and Y. Plan. Matrix completion with noise. Proceedings of the IEEE, 98(6):925–936, 2010. [5] E. J. Candès and B. Recht. Exact matrix completion via convex optimization. Foundations of Computational mathematics, 9(6):717, 2009. [6] J. Capon. High-resolution frequency-wavenumber spectrum analysis. Proceedings of the IEEE, 57(8):1408–1418, 1969. [7] W. Chen, K. M. Wong, and J. P. Reilly. Detection of the number of signals: A predicted eigen-threshold approach. IEEE Transactions on Signal Processing, 39(5):1088–1098, 1991. [8] M. Fazel. Matrix rank minimization with applications. PhD thesis, PhD thesis, Stanford University, 2002. [9] M. Haardt and J. A. Nossek. Unitary esprit: How to obtain increased estimation accuracy with a reduced computational burden. IEEE transactions on signal processing, 43(5):1232–1242, 1995. [10] Z. He, A. Cichocki, S. Xie, and K. Choi. Detecting the number of clusters in nway probabilistic clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(11):2006–2021, 2010. [11] R. D. Hill, R. G. Bates, and S. R. Waters. On centrohermitian matrices. SIAM Journal on Matrix Analysis and Applications, 11(1):128–133, 1990. [12] K.-C. Huarng and C.-C. Yeh. A unitary transformation method for angle-of-arrival estimation. IEEE Transactions on Signal Processing, 39(4):975–977, 1991. [13] H. Krim and M. Viberg. Two decades of llrray signal processing research. IEEE signal processing magazine, 1996. [14] A. Lee. Centrohermitian and skew-centrohermitian matrices. Linear algebra and its applications, 29:205–210, 1980. [15] D. A. Linebarger, R. D. DeGroat, and E. M. Dowling. Efficient direction-finding methods employing forward/backward averaging. IEEE Transactions on Signal Processing, 42(8):2136–2145, 1994. [16] C.-L. Liu and P. Vaidyanathan. Remarks on the spatial smoothing step in coarray music. IEEE Signal Processing Letters, 22(9):1438–1442, 2015. [17] C.-L. Liu and P. Vaidyanathan. Cramér–rao bounds for coprime and other sparse arrays, which find more sources than sensors. Digital Signal Processing, 61:43–61, 2017. [18] C.-L. Liu, P. Vaidyanathan, and P. Pal. Coprime coarray interpolation for doa estimation via nuclear norm minimization. In 2016 IEEE International Symposium on Circuits and Systems (ISCAS), pages 2639–2642. IEEE, 2016. [19] P. Pal and P. Vaidyanathan. Nested arrays: A novel approach to array processing withenhanced degrees of freedom. IEEE Transactions on Signal Processing, 58(8):4167–4181, 2010. [20] P. Pal and P. P. Vaidyanathan. Coprime sampling and the music algorithm. In 2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE), pages 289–294. IEEE, 2011. [21] M. Pesavento, A. B. Gershman, and M. Haardt. Unitary root-music with a realvalued eigendecomposition: A theoretical and experimental performance study. IEEE transactions on signal processing, 48(5):1306–1314, 2000. [22] H. Qiao and P. Pal. Unified analysis of co-array interpolation for direction-of-arrival estimation. In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 3056–3060. IEEE, 2017. [23] S. Qin, Y. D. Zhang, and M. G. Amin. Generalized coprime array configurations for direction-of-arrival estimation. IEEE Transactions on Signal Processing, 63(6):1377–1390, 2015. [24] R. Roy and T. Kailath. Esprit-estimation of signal parameters via rotational invariance techniques. IEEE Transactions on acoustics, speech, and signal processing, 37(7):984–995, 1989. [25] R. Schmidt. Multiple emitter location and signal parameter estimation. IEEE transactions on antennas and propagation, 34(3):276–280, 1986. [26] T. E. Tuncer and B. Friedlander. Classical and modern direction-of-arrival estimation. Academic Press, 2009. [27] P. P. Vaidyanathan and P. Pal. Sparse sensing with co-prime samplers and arrays. IEEE Transactions on Signal Processing, 59(2):573–586, 2010. [28] H. L. Van Trees. Optimum array processing: Part IV of detection, estimation, and modulation theory. John Wiley & Sons, 2004. [29] M. Wax and T. Kailath. Detection of signals by information theoretic criteria. IEEE Transactions on acoustics, speech, and signal processing, 33(2):387–392, 1985. [30] Y. D. Zhang, M. G. Amin, and B. Himed. Sparsity-based doa estimation using coprime arrays. In 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pages 3967–3971. IEEE, 2013. [31] C. Zhou, Y. Gu, X. Fan, Z. Shi, G. Mao, and Y. D. Zhang. Direction-of-arrival estimation for coprime array via virtual array interpolation. IEEE Transactions on Signal Processing, 66(22):5956–5971, 2018. [32] Y. Zhu, X. Wang, L. Wan, M. Huang, W. Feng, and J. Wang. Unitary low-rank matrix decomposition for doa estimation in nonuniform noise. In 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), pages 1–4. IEEE, 2018. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72711 | - |
dc.description.abstract | 互質陣列(coprime array) 是由兩個均勻線性陣列(uniform linear array) 組成,互質陣列可以分辨出比感測器數量更多的來源數量。然而,互質陣列的差陣列(difference coarray) 是非連續的,也就是說,差陣列中存在空洞(hole)。近年來,有許多基於陣列內插的入射角度估測方法(direction-of-arrival estimation) 被提出,包括最大熵(entropy)Toeplitz 矩陣補全,最小核範數(nuclear norm) Toeplitz 矩陣補全和重建Toeplitze 共變異矩陣。這些方法透過陣列內插技術,將不連續的差陣列內插為連續的均勻線性陣列,因此,基於陣列內插的入射角度估測方法可以利用互質陣列接收到的所有資訊進行入射角度估測。然而,陣列內插技術涉及求解凸函數最優化問題(convex optimization problem),因此計算所需要的時間顯著地增加。在本論文中,我們提出了一種高效率的陣列內插方法透過核範數最小化和么正轉換(unitary transformation),模擬結果說明,該方法可以大幅減少計算所需要的時間且和其他陣列內插方法擁有非常相近的入射角度估測精準度。 | zh_TW |
dc.description.abstract | A coprime array is composed of two uniform linear arrays (ULAs). A coprime array can resolve more the number of sources than the number of sensors. However, the difference coarray of coprime arrays is non-consecutive. Namely, there are holes in the difference coarray. Recently, coarray interpolation-based direction-of-arrival (DOA) estimation methods, such as the maximum entropy Toeplitz matrix completion method, the minimum nuclear norm Toeplitz completion method, and the reconstructed Toeplitz covariance matrix method, have been proposed. These methods generate a consecutive uniform linear array from the non-consecutive difference coarray through array interpolation. Thus, these methods can utilize all the information received by the coprime array for DOA estimation. However, the coarray interpolation technique involves solving a convex optimization problem. It significantly increases the computational time. In this thesis, we propose an efficient coarray interpolation method via nuclear norm minimization and unitary transformation. Simulation results demonstrate that the proposed method can dramatically reduce computational time. Moreover, the proposed method and other coarray interpolation-based DOA estimation methods achieve a quite similar DOA estimation accuracy. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T07:04:13Z (GMT). No. of bitstreams: 1 ntu-108-R06942051-1.pdf: 1495501 bytes, checksum: e2d80daa0a4e2e83c39650434b143205 (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 誌謝iii
摘要v Abstract vii 1 Introduction 1 1.1 Comparison between Uniform Linear Arrays and Sparse Arrays . . . . . 1 1.1.1 Uniform Linear Arrays (ULA) . . . . . . . . . . . . . . . . . . . 2 1.1.2 Sparse Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Main Contributions of the Thesis . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Outline of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.4 Notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 DOA Estimation for Coprime Array 7 2.1 The Coprime Array Structure . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 Signal Model of the Coprime Array . . . . . . . . . . . . . . . . . . . . 9 2.3 The Spatial Smoothing MUSIC Method . . . . . . . . . . . . . . . . . . 12 2.4 Coarray MUSIC without Spatial Smoothing . . . . . . . . . . . . . . . . 16 2.5 Coarray Interpolation via Nuclear Norm Minimization . . . . . . . . . . 19 3 Proposed Methods 21 3.1 Method 1: Efficient Coarray Interpolation Method via Unitary Transformation (Unitary-NNM) . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.1.1 The Unitary Transformation . . . . . . . . . . . . . . . . . . . . 22 3.1.2 Coarray Interpolation for Even-Dimensional Matrix . . . . . . . 25 3.1.3 Coarray Interpolation for Odd-Dimensional Matrix . . . . . . . . 34 3.2 Method 2: Real-Valued Coarray Interpolation Method (Real-NNM) . . . 38 4 Simulation Results 41 5 Conclusion 55 A Proof of Lemma 3.1.9 57 B Low-rank Terms of the matrixeBV 59 Bibliography 61 | |
dc.language.iso | en | |
dc.title | 互質陣列之入射角度估測中基於么正轉換之高效率內插法 | zh_TW |
dc.title | An Efficient Interpolation Method for Coprime Array DOA Estimation Using Unitary Transformation | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 馮世邁,劉俊麟 | |
dc.subject.keyword | 入射角度估測,么正轉換,互質陣列, | zh_TW |
dc.subject.keyword | DOA Estimation,Unitary Transformation,Coprime Array, | en |
dc.relation.page | 64 | |
dc.identifier.doi | 10.6342/NTU201901846 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-07-29 | |
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-108-1.pdf 目前未授權公開取用 | 1.46 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。