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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 江簡富 | zh_TW |
| dc.contributor.advisor | Jean-Fu Kiang | en |
| dc.contributor.author | 吳道明 | zh_TW |
| dc.contributor.author | Dau-Ming Wu | en |
| dc.date.accessioned | 2023-08-15T17:50:50Z | - |
| dc.date.available | 2023-11-09 | - |
| dc.date.copyright | 2023-08-15 | - |
| dc.date.issued | 2023 | - |
| dc.date.submitted | 2023-08-08 | - |
| dc.identifier.citation | [1] J. Pei, Y. Huang, W. Huo, Y. Zhang, J. Yang and T. Yeo, “SAR automatic target recognition based on multiview deep learning framework,” IEEE Trans. Geosci. Remote Sensing, vol. 56, no. 4, pp. 2196-2210, April 2018.
[2] Z. Yang, H. Xu, P. Huang, A. Liu, M. Tian and G. Liao, “Preliminary results of multichannel SAR-GMTI experiments for airborne quad-pol radar System,” IEEE Trans. Geosci. Remote Sensing, vol. 58, no. 6, pp. 3822-3840, June 2020. [3] M. -S. Kang and K. -T. Kim, “Ground moving target imaging based on compressive sensing framework with single-channel SAR,” IEEE Sensors J., vol. 20, no. 3, pp. 1238- 1250, 1 Feb., 2020. [4] P. Huang, X. Xia, Y. Gao, X. Liu, G. Liao and X. Jiang, “Ground moving target refocusing in SAR imagery based on RFRT-FrFt,” IEEE Trans. Geosci. Remote Sensing, vol. 57, no. 8, pp. 5476-5492, Aug. 2019. [5] C. Zeng, D. Li, X. Luo, D. Song, H. Liu and J. Su, “Ground maneuvering targets imaging for synthetic aperture radar based on second-order Keystone transform and high-order motion parameter estimation,” IEEE J. Select. Topics Appl. Earth Observ. Remote Sensing, vol. 12, no. 11, pp. 4486-4501, Nov. 2019. [6] Y. Guo, G. Liao, J. Li and X. Chen, “A novel moving target detection method based on RPCA for SAR systems,” IEEE Trans. Geosci. Remote Sensing, vol. 58, no. 9, pp. 6677-6690, Sept. 2020. [7] Y. Guo, G. Liao, J. Li and T. Gu, “A clutter suppression method based on NSS-RPCA in heterogeneous environments for SAR-GMTI,” IEEE Trans. Geosci. Remote Sensing, vol. 58, no. 8, pp. 5880-5891, Aug. 2020. [8] G. Xu, B. Zhang, H. Yu, J. Chen, M. Xing and W. Hong, “Sparse synthetic aperture radar imaging from compressed sensing and machine learning: Theories, applications, and trends,” IEEE Geosci. Remote Sensing Mag., 2022. [9] G. Xu, B. Zhang, J. Chen and W. Hong, “Structured low-rank and sparse method for ISAR imaging with 2-D compressive sampling,,” IEEE Trans. Geosci. Remote Sensing, vol. 60, pp. 1-14, 2022. [10] G. Xu, X. -G. Xia and W. Hong, “Non-ambiguous SAR image formation of maritime targets using weighted sparse approach,,” IEEE Trans. Geosci. Remote Sensing, vol. 56, no. 3, pp. 1454-1465, Mar. 2018. [11] G. Jin, Z. Dong, F. He and A. Yu, “SAR ground moving target imaging based on a new range model using a modified Keystone transform,” IEEE Trans. Geosci. Remote Sensing, vol. 57, no. 6, pp. 3283-3295, June 2019. [12] J.Wan, X. Tan, Z. Chen, D. Li, Y. Zhou and L. Zhang, “Fast approach for SAR imaging of ground moving target with Doppler ambiguity based on 2-D SCFT and IRFCCF,” IEEE Geosci. Remote Sensing Lett., vol.19, pp.1-5, 2022. [13] D. You, G. C. Sun, M. Xing, Y. Li and Z. Bao, “SAR ground maneuvering targets imaging and motion parameters estimation based on the adaptive polynomial Fourier transform,” IEEE Geosci. Remote Sensing Lett., vol.19, pp.1-5, 2022. [14] G. Jin, Z. Dong, F. He and A. Yu, “Background-free ground moving target imaging for multi-PRF airborne SAR,” IEEE Trans. Geosci. Remote Sensing, vol. 57, no. 4, pp. 1949-1962, April 2019. [15] D. Henke, E. Mendez Dominguez, D. Small, M. E. Schaepman and E. Meier, “ Moving target tracking in SAR data using combined exo- and endo-clutter processing,” IEEE Trans. Geosci. Remote Sensing, vol. 56, no. 1, pp. 251-263, Jan. 2018. [16] Y. Huang, G. Liao, J. Xu and J. Li, “GMTI and parameter estimation via time-Doppler chirp-varying approach for single-channel airborne SAR system,” IEEE Trans. Geosci. Remote Sensing, vol. 55, no. 8, pp. 4367-4383, Aug. 2017. [17] P. Huang, G. Liao, Z. Yang, X. Xia, J. Ma and X. Zhang, “An approach for refocusing of ground moving target without target motion parameter estimation,” IEEE Trans. Geosci. Remote Sensing, vol. 55, no. 1, pp. 336-350, Jan. 2017. [18] D. Cristallini and I. Walterscheid, “Joint monostatic and bistatic STAP for improved SAR-GMTI capabilities,” IEEE Trans. Geosci. Remote Sensing, vol. 54, no. 3, pp. 1834-1848, March 2016. [19] D. Cerutti-Maori and I. Sikaneta, “A generalization of DPCA processing for multichannel SAR/GMTI radars,” IEEE Trans. Geosci. Remote Sensing, vol. 51, no. 1, pp. 560-572, Jan. 2013. [20] J. Kim, Y. Kim, T. Yeo, S. Khang and J. Yu, “Fast Fourier-domain optimization using hybrid L1/Lp-norm for autofocus in airborne SAR imaging,” IEEE Trans. Geosci. Remote Sensing, vol. 57, no. 10, pp. 7934-7954, Oct. 2019. [21] L. Chen, Z. Liu and Fang, “An accurate motion compensation for SAR imagery based on INS/GPS with dual-filter correction,” J. Navigation, vol. 72, no. 6, pp. 1399-1416, Feb. 2019. [22] J. Li, J. Chen, P. Wang and O. Loffeld, “A coarse-to-fine autofocus approach for very high-resolution airborne stripmap SAR imagery,” IEEE Trans. Geosci. Remote Sensing, vol.56, no.7, pp.3814-3829, July 2018. [23] D. Huang, X. Guo, Z. Zhang, W. Yu and T. Truong, “Full-aperture azimuth spatial variant autofocus based on contrast maximization for highly squinted synthetic aperture radar,” IEEE Trans. Geosci. Remote Sensing, vol. 58, no. 1, pp. 330-347, Jan. 2020. [24] S. Shi, C. Li, J. Hu, X. Zhang and G. Fang, “Motion compensation for terahertz synthetic aperture radar based on subaperture decomposition and minimum entropy theorem,” IEEE Sensors J., vol. 20, no. 24, pp. 14940-14949, 15 Dec.15, 2020. [25] G. Wang, M. Zhang, Y. Huang, L. Zhang, and F. Wang, “Robust two-dimensional spatial-variant map-drift algorithm for UAV SAR autofocusing,” Remote Sensing, vol.11, no.3, 2019. [26] O. O. Bezvesilniy, I. M. Gorovyi and D. M. Vavriv, “Autofocusing SAR images via local estimates of flight trajectory,” Int. J. Microwave Wireless Technol., vol. 8, no. 6, pp. 881-889, 2016. [27] D. E.Wahl, P. H. Eichel, D. C. Ghiglia and C. V. Jakowatz, “Phase gradient autofocus-A robust tool for high resolution SAR phase correction,” IEEE Trans. Aerospace Electron. Syst., vol.30, no.3, pp.827-835, July 1994. [28] Y. Li and S. O. Young, “Kalman filter disciplined phase gradient autofocus for stripmap SAR,” IEEE Trans. Geosci. Remote Sensing, vol. 58, no. 9, pp. 6298-6308, Sept. 2020. [29] M. -S. Kang and K. -T. Kim, “Ccompressive sensing based SAR imaging and autofocus using improved Tikhonov regularization,,,” IEEE Sensors J., vol. 19, no. 14, pp. 5529- 5540, 15 July15, 2019. [30] Z. Liu, S. Yang, Z. Feng, Q. Gao and M.Wang, “ Fast SAR autofocus based on ensemble convolutional extreme learning machine,” Remote Sensing, vol.13, no.14, pp.2683, 2021. [31] J. R. Fienup, “Detecting moving targets in SAR imagery by focusing,” IEEE Trans. Aerospace Electron. Syst., vol.37, no.3, pp.794-809, July 2001. [32] L. Ran, Z. Liu, L. Zhang, T. Li and R. Xie, “An autofocus algorithm for estimating residual trajectory deviations in synthetic aperture radar,” IEEE Trans. Geosci. Remote Sensing, vol.55, no.6, pp.3408-3425, June 2017. [33] Y. C. Chen, G. Li, Q. Zhang, Q. J. Zhang and X. G. Xia, “Motion compensation for airborne SAR via parametric sparse representation,” IEEE Trans. Geosci. Remote Sensing, vol.55, no.1, pp. 551-562, Jan. 2017. [34] L. Ran, Z. Liu, R. Xie and L. Zhang, “Focusing high-squint synthetic aperture radar data based on factorized back-projection and precise spectrum fusion,” Remote Sensing, vol.11, pp.2885, 2019. [35] Y. Zhang, J. Sun, P. Lei, G. Li and W. Hong, “High-resolution SAR-based ground moving target imaging with defocused ROI data,” IEEE Trans. Geosci. Remote Sensing, vol.54, no.2, pp.1062-1073, Feb. 2016. [36] A. R. Brenner, “Ultra-high resolution airborne SAR imaging of vegetation and manmade objects based on 40% relative bandwidth in X-band,” IEEE Int. Geosci. Remote Sensing Symp., pp. 7397-7400, 2012. [37] I. G. Cumming and F. H. Wong, Digital Processing of Synthetic Aperture Radar Data, Artech House, 2005. [38] W. G. Carrara, R. S. Goodman, and R. M. Majewski, Spotlight Synthetic Aperture Radar, Artech House, 1995. [39] C. V. J. Jakowatz, D. E. Wahl, P. H. Eichel, D. C. Ghiglia, and P. A. Thompson, Spotlight-mode Synthetic Aperture Radar: A Signal Processing Approach, Springer Science & Business Media, 2012. [40] E. D. Jansing, Introduction to Synthetic Aperture Radar: Concepts and Practice, McGraw-Hill Education, 2021. [41] L. Zhang, M. Xing, C.-W. Qiu, J. Li, J. Sheng, Y. Li, Z. Bao, “Resolution enhancement for inversed synthetic aperture radar imaging under low SNR via improved compressive sensing,” IEEE Trans. Geosci. Remote Sensing, vol. 48, no. 10, pp. 3824-3838, Oct. 2010. [42] W. Qiu, H. Zhao, J. Zhou and Q. Fu, “High-resolution fully polarimetric ISAR imaging based on compressive sensing,” IEEE Trans. Geosci. Remote Sensing, vol.52, no.10, pp.6119-6131, Oct. 2014. [43] L. Zhao, L. Wang, G. Bi, L. Yang, “An autofocus technique for high-resolution inverse synthetic aperture radar imagery,” IEEE Trans. Geosci. Remote Sensing, vol. 52, no. 10, pp. 6392-6403, Oct. 2014. [44] http://cvxr.com/cvx/. [45] J.Wang, L. Zhang, L. Du, D. Yang and B. Chen, “Noise-robust motion compensation for aerial maneuvering target ISAR imaging by parametric minimum entropy optimization,” IEEE Trans. Geosci. Remote Sensing, vol.57, no.7, pp. 4202-4217, July 2019. [46] P. C. Chen and J. F. Kiang, “Improved chirp scaling algorithms for SAR imaging under high squint angles,” IET Radar, Sonar & Navigation, vol.11, no.11, pp.1629-1636, 2017. [47] S. Mehrotra, S. Das, S. Shikha and C. Kar, “Comparative analysis of traditional methods with game of life in cellular automata for edge detection,” Int. J. Computer Appl., vol. 118, no. 18, pp. 18-24, May 2015. [48] https://www.sdms.afrl.af.mil/index.php | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/88802 | - |
| dc.description.abstract | 本論文提出了一種雙通道機載合成孔徑雷達(SAR)成像方法,並補償平台軌跡偏差來獲取地面運動目標的圖像,聚焦效果良好。歸因於平台軌跡偏差或目標運動的相位誤差各由一個慢時間多項式表示。將運動補償前的SAR圖像分割成多個子圖像,並應用壓縮感知技術對每個子圖像估計平台軌跡偏差的多項式係數。再結合距離頻率逆轉換 (RFRT) 和分數傅立葉轉換 (FrFT) 以估計每個運動目標的運動參數和位置。所提出的方法分別用真實數據和模擬數據驗證,聚焦圖像中的運動目標可準確地識別。 | zh_TW |
| dc.description.abstract | A dual-channel airborne SAR imaging approach is proposed to acquire well focused images of ground moving targets after compensating the platform trajectory deviation. The phase error attributed to either platform trajectory deviation or target motion is given by a polynomial of slow time. The SAR image before motion compensation is segmented into multiple sub-images, and a compressive-sensing (CS) technique is applied on each sub-image to estimate the polynomial coefficients featuring platform trajectory deviation. A range-frequency reversal transform (RFRT) and fractional Fourier transform (FrFT) are combined to estimate the motion parameters and position of each moving target. The proposed approach is verified with real data and simulated data, respectively, and the moving targets in the acquired image are well recognized. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-08-15T17:50:50Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2023-08-15T17:50:50Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Abstract i
Contents ii List of Figures iii Acknowledgment iv 1 Introduction 1 2 Range Model and Proposed Approach 7 3 Compensation of Phase Error Due to Platform Trajectory Deviation 17 3.1 Estimation of PTD Range Error 20 3.2 Compensation of Range Error 23 4 Imaging of Moving Targets 27 4.1 Detection of GMTs with Entropy 27 4.2 Estimation of GMT Range Error with RFRT-FrFT 29 4.3 Estimation of Target Position and Velocity 31 4.4 Imaging of Individual Moving Target 33 4.5 Enhancement of Moving Target Image 34 4.6 Computational Load and Velocity Error 35 5 Target Recognition and Highlights 41 5.1 Real-Data for PTD Compensation 43 5.2 Highlights of Contributions 43 6 Conclusions 46 Bibliography 47 | - |
| dc.language.iso | en | - |
| dc.subject | 雷達遙測 | zh_TW |
| dc.subject | 合成孔徑雷達 | zh_TW |
| dc.subject | 數位訊號處理 | zh_TW |
| dc.subject | synthetic aperture radar | en |
| dc.subject | digital signal processing | en |
| dc.subject | remote sensing | en |
| dc.title | 雙通道機載合成孔徑雷達於平台擾動效應下 對地面運動目標之成像 | zh_TW |
| dc.title | Dual-Channel Airborne SAR Imaging of Ground Moving Targets on Perturbed Platform | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 111-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 丁建均;李翔傑 | zh_TW |
| dc.contributor.oralexamcommittee | Jian-Jiun Ding;Hsiang-Chieh Lee | en |
| dc.subject.keyword | 合成孔徑雷達,雷達遙測,數位訊號處理, | zh_TW |
| dc.subject.keyword | synthetic aperture radar,remote sensing,digital signal processing, | en |
| dc.relation.page | 55 | - |
| dc.identifier.doi | 10.6342/NTU202302447 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2023-08-09 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 電信工程學研究所 | - |
| 顯示於系所單位: | 電信工程學研究所 | |
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