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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 電信工程學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/96347
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor蘇柏青zh_TW
dc.contributor.advisorBorching Suen
dc.contributor.author張聿維zh_TW
dc.contributor.authorYu-Wei Changen
dc.date.accessioned2024-12-24T16:28:06Z-
dc.date.available2024-12-25-
dc.date.copyright2024-12-24-
dc.date.issued2024-
dc.date.submitted2024-12-03-
dc.identifier.citation[1] M. ApS. The MOSEK optimization toolbox for MATLAB manual. Version 9.0., 2019.
[2] F. Arlery, R. Kassab, U. Tan, and F. Lehmann. Efficient gradient method for locally optimizing the periodic/aperiodic ambiguity function. In 2016 IEEE Radar Conference (RadarConf), pages 1–6, 2016.
[3] L. Auslander and R. Tolimieri. Computing decimated finite cross-ambiguity functions. IEEE Transactions on Acoustics, Speech, and Signal Processing, 36(3):359–364, 1988.
[4] R. Baraniuk and P. Steeghs. Compressive radar imaging. In 2007 IEEE Radar Conference, pages 128–133, 2007.
[5] P. Cao, J. Thompson, and H. V. Poor. A sequential constraint relaxation algorithm for rank-one constrained problems. In 2017 25th European Signal Processing Conference (EUSIPCO), pages 1060–1064, 2017.
[6] Z. Chen, J. Liang, T. Wang, B. Tang, and H. C. So. Generalized mbi algorithm for designing sequence set and mismatched filter bank with ambiguity function constraints. IEEE Transactions on Signal Processing, 70:2918–2933, 2022.
[7] M. Chitre, J. Tian, and H. Vishnu. On ambiguity function shaping for broadband constant-modulus signals. Signal Processing, 166:107224, 2020.
[8] G. Cui, Y. Fu, X. Yu, and J. Li. Local ambiguity function shaping via unimodular sequence design. IEEE Signal Processing Letters, 24(7):977–981, 2017.
[9] J. Dattorro. Convex optimization & Euclidean distance geometry. Meboo USA, Palo Alto, California, 2019.
[10] B. Dumitrescu. Positive Trigonometric Polynomials and Signal Processing Applications. Springer Cham, Cham, Switzerland, 2nd edition, 2018.
[11] H. Esmaeili-Najafabadi, H. Leung, and P. W. Moo. Unimodular waveform design with desired ambiguity function for cognitive radar. IEEE Transactions on Aerospace and Electronic Systems, 56(3):2489–2496, 2020.
[12] W. Fan, J. Liang, G. Yu, H. C. So, and G. Lu. Minimum local peak sidelobe level waveform design with correlation and/or spectral constraints. Signal Processing, 171:107450, 2020.
[13] M. Grant and S. Boyd. CVX: Matlab software for disciplined convex programming, version 2.1. https://cvxr.com/cvx, Mar. 2014.
[14] H. Griffiths, L. Cohen, S. Watts, E. Mokole, C. Baker, M. Wicks, and S. Blunt. Radar spectrum engineering and management: Technical and regulatory issues. Proceedings of the IEEE, 103(1):85–102, 2015.
[15] K. Gröchenig. Foundations of time-frequency analysis. Springer Science & Business Media, 2013.
[16] H. He, J. Li, and P. Stoica. Waveform Design for Active Sensing Systems: A Computational Approach. Cambridge University Press, Cambridge, UK, 2012.
[17] Y. Huang. Matched filtering and pulse waveform. Lecture notes for Algorithm Design for Phased Array Radar, 2024.
[18] Y. Jing, J. Liang, B. Tang, and J. Li. Designing unimodular sequence with low peak of sidelobe level of local ambiguity function. IEEE Transactions on Aerospace and Electronic Systems, 55(3):1393–1406, 2019.
[19] N. Levanon and E. Mozeson. Radar Signals. John Wiley & Sons, Inc., Hoboken, New Jersey, USA, 2004.
[20] B. R. Mahafza. Introduction to radar analysis. CRC Press, 2nd edition, 2017.
[21] A. Ozdemir and O. Arikan. Fast computation of the ambiguity function and the wigner distribution on arbitrary line segments. IEEE Transactions on Signal Processing, 49(2):381–393, 2001.
[22] L. K. Patton. On the satisfaction of modulus and ambiguity function constraints in radar waveform optimization for detection. PhD thesis, Wright State University, 2009.
[23] M. A. Richards. Fundamentals of Radar Signal Processing. McGraw-Hill Education, 2nd edition, 2014.
[24] M. A. Richards, J. A. Scheer, and W. A. Holm, editors. Principles of Modern Radar: Basic principles. Radar, Sonar and Navigation. Institution of Engineering and Technology, 2010.
[25] S. P. Sankuru, R. Jyothi, P. Babu, and M. Alaee-Kerahroodi. Designing sequence set with minimal peak side-lobe level for applications in high resolution radar imaging. IEEE Open Journal of Signal Processing, 2:17–32, 2021.
[26] M. Skolnik. Radar Handbook. McGraw Hill, United States of America, 3th edition, 2008.
[27] J. Song, P. Babu, and D. P. Palomar. Optimization methods for designing sequences with low autocorrelation sidelobes. IEEE Transactions on Signal Processing, 63(15):3998–4009, 2015.
[28] P. Stoica, H. He, and J. Li. On designing sequences with impulse-like periodic correlation. IEEE Signal Processing Letters, 16(8):703–706, 2009.
[29] K. Wang, R. Tao, and T. Shan. Improved method of pre-weighed zoom fft. In 2008 9th International Conference on Signal Processing, pages 2438–2441, 2008.
[30] L. Wu, P. Babu, and D. P. Palomar. Cognitive radar-based sequence design via sinr maximization. IEEE Transactions on Signal Processing, 65(3):779–793, 2017.
[31] S.-P. Wu, S. Boyd, and L. Vandenberghe. Fir filter design via spectral factorization and convex optimization. In Applied and Computational Control, Signals, and Circuits: Volume 1, pages 215–245. Springer, 1999.
[32] J. Yang, G. Cui, X. Yu, Y. Xiao, and L. Kong. Cognitive local ambiguity function shaping with spectral coexistence. IEEE Access, 6:50077–50086, 2018.
[33] D. Zhang and C. Jiang. Fast calculation of cross ambiguity function for passive radar based on smgo. In 2021 China Automation Congress (CAC), pages 6684–6689, 2021.
[34] J. Zhang, C. Shi, X. Qiu, and Y. Wu. Shaping radar ambiguity function by l -phase unimodular sequence. IEEE Sensors Journal, 16(14):5648–5659, 2016.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/96347-
dc.description.abstract在主動感測系統中,設計適當的探測波形對於偵測和估計目標物體的重要參數(如在雷達系統中的距離和速度)至關重要。在匹配濾波器組接收器中,波形應具有低模糊函數旁瓣,以減少干擾。精確來說,峰值旁瓣等級是一個更理想的準則,因為它決定了誤報率。此外,從硬體角度來看,採用單模波形有助於最大化功率放大器的效率。現有文獻已在特定離散化的距離-都卜勒區域內,最小化了模糊函數的格點峰值旁瓣等級。然而,由於目標產生的都卜勒頻率位於連續區間,基於該方法設計的波形可能會導致在都卜勒頻率格點之間出現預料之外的旁瓣,造成如誤報和目標遮蔽等偵測問題。因此,GPSL準則在這種情況下可能不是最合適的。本論文採用了真實峰值旁瓣等級來取代格點峰值旁瓣等級準則,以評估在連續都卜勒頻率區間內的峰值旁瓣等級。我們提出了一個波形設計問題,該問題在單模約束下,考慮了在特定距離-都卜勒區域內連續都卜勒頻率下將真實峰值旁瓣等級最小化。此外,我們引入了涉及三角多項式技巧的凸迭代算法來解決真實峰值旁瓣等級最小化問題。驗證結果顯示,與先前的研究相比,本論文所提出的方法在真實峰值旁瓣等級上取得了更佳的表現,這代表著該方法在整個連續都卜勒頻率區間內保證了低旁瓣等級。zh_TW
dc.description.abstractIn active sensing systems, designing appropriate probing waveforms is crucial for detecting and estimating valuable parameters of the objects of interest, such as range and velocity in radar systems. In a matched filter bank receiver, the waveform should exhibit low ambiguity function sidelobes to mitigate interference. Specifically, the peak sidelobe level is a more desirable criterion since it determines the false alarm rate. Moreover, from a hardware perspective, unimodular waveforms are preferable to maximize power amplifier efficiency. Existing literature has minimized the grid peak sidelobe level (GPSL) of the ambiguity function over a specific discretized range-Doppler region. However, since the Doppler frequency produced by the target falls within a continuous interval, using waveforms based on the method may lead to unexpected sidelobes between Doppler frequency samples, causing detection issues such as false alarms and target masking. Therefore, the GPSL criterion may not be the most suitable criterion in this scenario. In this thesis, the true peak sidelobe level (TPSL) is used instead of the GPSL criterion to evaluate the peak sidelobe level along a continuous Doppler frequency interval. A waveform design problem that minimizes the TPSL, considering continuous Doppler frequency over a specific range-Doppler region under unimodular constraints, is proposed. Also, convex iterative algorithms, involving the technique of trigonometric polynomials, are introduced to solve the TPSL minimization problem. Validation results show that the proposed method achieves a better TPSL compared to previous work, which implies the proposed method guarantees low sidelobe levels across the entire continuous Doppler frequency interval.en
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dc.description.tableofcontentsAcknowledgements iii
摘要 v
Abstract vii
Contents ix
List of Figures xi
List of Tables xiii
Chapter 1 Introduction 1
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Previous Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Approach and Novelty . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.5 Notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Chapter 2 System Model 7
2.1 Radar System with A Matched Filter . . . . . . . . . . . . . . . . . . 8
2.1.1 Range Detection . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2 Radar System with A Bank of Matched Filters . . . . . . . . . . . . 15
Chapter 3 Problem Statement 21
3.1 Interference Identification and Effects on Performance . . . . . . . . 22
3.1.1 Region of Interest . . . . . . . . . . . . . . . . . . . . . . . . 30
3.2 Issues in Prior Studies and Doubts Raised . . . . . . . . . . . . . . . 32
3.3 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Chapter 4 Algorithm Proposal 37
4.1 Problem Reformulation . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.2 Rank-One Constraint Management . . . . . . . . . . . . . . . . . . . 43
4.2.1 SROCR Algorithm . . . . . . . . . . . . . . . . . . . . . . . 43
4.2.2 Dattorro’s Algorithm . . . . . . . . . . . . . . . . . . . . . . 47
4.3 Out-of-ROI Sidelobe Restriction . . . . . . . . . . . . . . . . . . . . 51
Chapter 5 Validation of the Proposed Methods 57
5.1 Comparison Results of AF Optimization . . . . . . . . . . . . . . . . 58
5.1.1 Case 1: N = 32 . . . . . . . . . . . . . . . . . . . . . . . . . 59
5.1.2 Case 2: N = 64 . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.1.3 Case 3: N = 128 . . . . . . . . . . . . . . . . . . . . . . . . 69
5.2 Comparison Results of AF with Out-of-ROI Suppression . . . . . . . 72
5.2.1 Case 4: N = 32 with Sidelobes Restriction . . . . . . . . . . 72
5.2.2 Case 5: N = 64 with Sidelobes Restriction . . . . . . . . . . 77
Chapter 6 Conclusion and Future Work 83
References 85
Appendix A — Derivation from Equation (3.15) to (3.17) 89
Appendix B — Trigonometric Polynomials 95
B.1 Trace Parameterization . . . . . . . . . . . . . . . . . . . . . . . . . 96
B.2 Nonnegative Trigonometric Polynomials on an Interval . . . . . . . . 98
Appendix C — Proof of Theorem 4.1 103
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dc.language.isoen-
dc.title關於設計單模波形以抑制干擾:基於連續都卜勒位移最小化峰值旁瓣等級zh_TW
dc.titleOn Designing Unimodular Waveforms for Interference Suppression: Peak Sidelobe Level Minimization with Continuous Doppler Shift Considerationsen
dc.typeThesis-
dc.date.schoolyear113-1-
dc.description.degree碩士-
dc.contributor.oralexamcommittee馮世邁;林源倍zh_TW
dc.contributor.oralexamcommitteeSee-May Phoong;Yuan-Pei Linen
dc.subject.keyword波型設計,匹配濾波器組,連續都卜勒位移考慮,模糊函數,峰值旁辦等級,三角多項式,凸函數最佳化,單模波型,zh_TW
dc.subject.keywordWaveform design,matched filter bank,continuous Doppler shift consideration,ambiguity function,peak sidelobe level,trigonometric polynomials,convex optimization,unimodular waveform,en
dc.relation.page105-
dc.identifier.doi10.6342/NTU202404638-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2024-12-04-
dc.contributor.author-college電機資訊學院-
dc.contributor.author-dept電信工程學研究所-
dc.date.embargo-lift2029-11-26-
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