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SHAO Shuai, CHEN Xueyi, ZHUANG Xiaozhi, et al. Sparse array ISAR 3-D imaging method for ship targets via joint error calibration and super-resolution DOA estimation[J]. Journal of Radars, in press. doi: 10.12000/JR26085
Citation: SHAO Shuai, CHEN Xueyi, ZHUANG Xiaozhi, et al. Sparse array ISAR 3-D imaging method for ship targets via joint error calibration and super-resolution DOA estimation[J]. Journal of Radars, in press. doi: 10.12000/JR26085
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Sparse Array ISAR 3-D Imaging Method for Ship Targets via Joint Error Calibration and Super-resolution DOA Estimation

DOI: 10.12000/JR26085 CSTR: 32380.14.JR26085

  • National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds:  The China Postdoctoral Science Foundation (2022M722502), The Shaanxi Postdoctoral Sustentation Fund (2023BSHYDZZ94), The National Key Laboratory of Microwave Imaging Open Fund
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  • Corresponding author: SHAO Shuai, sshao@xidian.edu.cn
  • Received Date: 2026-05-01
  • Rev Recd Date: 2026-07-26
    • Available Online: 2026-08-05
    Abstract
  • Shore-based radar systems are constrained by fixed deployment locations, which limits their detection capability. Owing to their flexible deployment, Unmanned Aerial Vehicles (UAVs) can form a space–time hybrid aperture to enable high-resolution array Inverse Synthetic Aperture Radar (ISAR) three-Dimensional (3-D) imaging of ship targets. However, marine environmental disturbances, such as sea winds, together with nonideal initial states and velocity synchronization errors within the UAV cluster, can distort the array geometry and cause phase misalignment among complex-valued ISAR images, thereby degrading target angle estimation and 3-D reconstruction quality. To address these issues, this paper proposes a sparse-array ISAR 3-D imaging method for ship targets via joint error calibration and super-resolution Direction-of-Arrival (DOA) estimation. The proposed method exploits the correlation between multipulse and ISAR DOA estimates to establish an association-matching mechanism that suppresses phase-error accumulation induced by time-varying differential ranges. A refined two-Dimensional (2-D) velocity-error model and a multicriteria fusion metric are incorporated into super-resolution DOA estimation, enabling the integrated estimation of multidimensional errors and angles. In addition, a joint Range-Azimuth Optimization Strategy (RAOS) is developed by exploiting differences in the spatial spectra of range cells containing either a single prominent scatterer or multiple prominent scatterers, together with the temporal distribution of errors and signal-to-noise ratio weighting, thereby improving both angle-estimation accuracy and computational efficiency. Point-target and electromagnetic simulations demonstrate that the proposed method achieves robust 3-D imaging of ship targets under nonideal sparse UAV-cluster conditions, with reconstruction errors below 10%, providing technical support for early-warning detection and strike guidance.

     

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    • References(37)
  • [1]
    WANG Feng, XU Feng, and JIN Yaqiu. Three-dimensional reconstruction from a multiview sequence of sparse ISAR imaging of a space target[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(2): 611–620. doi: 10.1109/TGRS.2017.2737988.
    [2]
    ZHOU Yejian, ZHANG Lei, CAO Yunhe, et al. Attitude estimation and geometry reconstruction of satellite targets based on ISAR image sequence interpretation[J]. IEEE Transactions on Aerospace and Electronic Systems, 2019, 55(4): 1698–1711. doi: 10.1109/TAES.2018.2875503.
    [3]
    LIU Lei, ZHOU Zuobang, ZHOU Feng, et al. A new 3-D geometry reconstruction method of space target utilizing the scatterer energy accumulation of ISAR image sequence[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(12): 8345–8357. doi: 10.1109/TGRS.2020.2986465.
    [4]
    RONG Jiajia, WANG Yong, and HAN Tao. Interferometric ISAR imaging of maneuvering targets with arbitrary three-antenna configuration[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(2): 1102–1119. doi: 10.1109/TGRS.2019.2943613.
    [5]
    ZHANG Junqiu and WANG Yong. A three-dimensional imaging method of ship target via multistatic distributed InISAR[J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 4511805. doi: 10.1109/LGRS.2022.3195362.
    [6]
    TIAN Biao, WU Wenzhen, LIU Yang, et al. Interferometric ISAR imaging of space targets using pulse-level image registration method[J]. IEEE Transactions on Aerospace and Electronic Systems, 2023, 59(3): 2188–2203. doi: 10.1109/TAES.2022.3209950.
    [7]
    胡凤鸣, 田稷钒, 程国振, 等. 城市建筑SAR三维成像域几何连续性表征与少轨数三维成像[J]. 雷达学报(中英文), 2026, 15(1): 26–41. doi: 10.12000/JR24256.

    HU Fengming, TIAN Jifan, CHENG Guozhen, et al. Geometric continuity characterization of urban buildings in SAR 3D imaging domain and few-tracks 3D imaging[J]. Journal of Radars, 2026, 15(1): 26–41. doi: 10.12000/JR24256.
    [8]
    HADDAD N, BOUARABA A, HADJ-RABAH K, et al. Generalized parametric iterative approach for tomographic SAR reconstruction[J]. IEEE Geoscience and Remote Sensing Letters, 2024, 21: 4011005. doi: 10.1109/LGRS.2024.3406894.
    [9]
    林雨青, 仇晓兰, 彭凌霄, 等. 基于多径模型的建筑区SAR三维成像中非视距目标重定位方法[J]. 雷达学报(中英文), 2024, 13(4): 777–790. doi: 10.12000/JR24057.

    LIN Yuqing, QIU Xiaolan, PENG Lingxiao, et al. Non-line-of-sight target relocation by multipath model in SAR 3D urban area imaging[J]. Journal of Radars, 2024, 13(4): 777–790. doi: 10.12000/JR24057.
    [10]
    WANG Yan, DING Zegang, LI Linghao, et al. First demonstration of single-pass distributed SAR tomographic imaging with a P-band UAV SAR prototype[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5238618. doi: 10.1109/TGRS.2022.3221859.
    [11]
    MA Changzheng, YEO T S, ZHANG Qun, et al. Three-dimensional ISAR imaging based on antenna array[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(2): 504–515. doi: 10.1109/TGRS.2007.909946.
    [12]
    MA Changzheng, YEO T S, TAN C S, et al. Sparse array 3-D ISAR imaging based on maximum likelihood estimation and CLEAN technique[J]. IEEE Transactions on Image Processing, 2010, 19(8): 2127–2142. doi: 10.1109/TIP.2010.2045711.
    [13]
    WANG Yong and LI Xuelu. 3-D imaging based on combination of the ISAR technique and a MIMO radar system[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(10): 6033–6054. doi: 10.1109/TGRS.2018.2829912.
    [14]
    全英汇, 吴耀君, 段丽宁, 等. 基于稀疏恢复的雷达信号处理研究综述[J]. 雷达学报(中英文), 2024, 13(1): 46–67. doi: 10.12000/JR23211.

    QUAN Yinghui, WU Yaojun, DUAN Lining, et al. A review of radar signal processing based on sparse recovery[J]. Journal of Radars, 2024, 13(1): 46–67. doi: 10.12000/JR23211.
    [15]
    夏靖远, 杨志雄, 周治兴, 等. 一种基于元学习的稀疏孔径ISAR成像算法[J]. 雷达学报, 2023, 12(4): 849–859. doi: 10.12000/JR23121.

    XIA Jingyuan, YANG Zhixiong, ZHOU Zhixing, et al. A metalearning-based sparse aperture ISAR imaging method[J]. Journal of Radars, 2023, 12(4): 849–859. doi: 10.12000/JR23121.
    [16]
    LIU Xin, DU Changhao, WANG Jiacheng, et al. An LSTM-assisted calibration approach for self-time transfer performance optimization in multi-UAV networks[J]. IEEE Transactions on Aerospace and Electronic Systems, 2025, 61(6): 17333–17348. doi: 10.1109/TAES.2025.3603798.
    [17]
    SONG Haibo, WEN Gongjian, LIANG Yuanyuan, et al. Target localization and clock refinement in distributed MIMO radar systems with time synchronization errors[J]. IEEE Transactions on Signal Processing, 2021, 69: 3088–3103. doi: 10.1109/TSP.2021.3081038.
    [18]
    ZHANG Ming and ZHU Zhaoda. DOA estimation with sensor gain, phase and position perturbations[C]. IEEE 1993 National Aerospace and Electronics Conference-NAECON 1993, Dayton, USA, 1993: 67–69. doi: 10.1109/NAECON.1993.290894.
    [19]
    NG B C and SEE C M S. Sensor-array calibration using a maximum-likelihood approach[J]. IEEE Transactions on Antennas and Propagation, 1996, 44(6): 827–835. doi: 10.1109/8.509886.
    [20]
    王鼎, 吴瑛. 一种新的阵列误差有源校正算法[J]. 电子学报, 2010, 38(3): 517–524.

    WANG Ding and WU Ying. A novel array errors active calibration algorithm[J]. Acta Electronica Sinica, 2010, 38(3): 517–524.
    [21]
    PAULRAJ A and KAILATH T. Direction of arrival estimation by eigenstructure methods with unknown sensor gain and phase[C]. IEEE International Conference on Acoustics, Speech, and Signal Processing, Tampa, USA, 1985: 640–643. doi: 10.1109/ICASSP.1985.1168341.
    [22]
    CHEN Tao, AN Qi, and LI Minxing. An error self-corrected DOA estimation model for sparse array based on ANM[C]. 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, Republic of, 2024: 41–45. doi: 10.1109/ICASSP48485.2024.10447794.
    [23]
    曹圣红. 存在阵列误差条件下波达方向估计算法研究[D]. [博士论文], 中国科学技术大学, 2014.

    CAO Shenghong. Direction of arrival estimation algorithms in the presence of array error[D]. [Ph.D. dissertation], University of Science and Technology of China, 2014.
    [24]
    FAN Liangyu, ZHU Xiaoqian, ZHU Jiahua, et al. MVDR beamforming algorithm for uniform circular array based on gain and phase errors[C]. 2021 4th International Conference on Information Communication and Signal Processing (ICICSP), Shanghai, China, 2021: 147–151. doi: 10.1109/ICICSP54369.2021.9611976.
    [25]
    ZHAO Lifan, BI Guo’an, WANG Lu, et al. An improved auto-calibration algorithm based on sparse bayesian learning framework[J]. IEEE Signal Processing Letters, 2013, 20(9): 889–892. doi: 10.1109/LSP.2013.2272462.
    [26]
    DAI Fengzhou, FU Haosheng, HONG Ling, et al. Off-grid error and amplitude–phase drift calibration for computational microwave imaging with metasurface aperture based on sparse Bayesian learning[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5115514. doi: 10.1109/TGRS.2022.3188879.
    [27]
    周子铂, 蒋李兵, 王壮. 一种基于波程差补偿的InISAR图像配准方法[J]. 雷达学报, 2018, 7(6): 758–769. doi: 10.12000/JR18070.

    ZHOU Zibo, JIANG Libing, and WANG Zhuang. Image registration based on wave path difference compensation for InISAR[J]. Journal of Radars, 2018, 7(6): 758–769. doi: 10.12000/JR18070.
    [28]
    KRIM H and VIBERG M. Two decades of array signal processing research: The parametric approach[J]. IEEE Signal Processing Magazine, 1996, 13(4): 67–94. doi: 10.1109/79.526899.
    [29]
    LIN Qingqing, XU Jun, CHEN Kai, et al. A single-board integrated millimeter-wave asymmetric full-digital beamforming array for B5G/6G applications[J]. Engineering, 2024, 41: 35–50. doi: 10.1016/j.eng.2024.04.013.
    [30]
    SCHMIDT R. Multiple emitter location and signal parameter estimation[J]. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 276–280. doi: 10.1109/TAP.1986.1143830.
    [31]
    PAN Jingjing, SUN Meng, WANG Yide, et al. An enhanced spatial smoothing technique with ESPRIT algorithm for direction of arrival estimation in coherent scenarios[J]. IEEE Transactions on Signal Processing, 2020, 68: 3635–3643. doi: 10.1109/TSP.2020.2994514.
    [32]
    舒月, 傅东宁, 陈展野, 等. 基于RD-ANM的毫米波雷达动目标超分辨DOA估计方法[J]. 雷达学报, 2023, 12(5): 986–999. doi: 10.12000/JR23040.

    SHU Yue, FU Dongning, CHEN Zhanye, et al. Super-resolution DOA estimation method for a moving target equipped with a millimeter-wave radar based on RD-ANM[J]. Journal of Radars, 2023, 12(5): 986–999. doi: 10.12000/JR23040.
    [33]
    SANTOSA F and SYMES W W. Linear inversion of band-limited reflection seismograms[J]. SIAM Journal on Scientific and Statistical Computing, 1986, 7(4): 1307–1330. doi: 10.1137/0907087.
    [34]
    AGHABABAIYAN K, SHAH-MANSOURI V, and MAHAM B. High-precision OMP-based direction of arrival estimation scheme for hybrid non-uniform array[J]. IEEE Communications Letters, 2020, 24(2): 354–357. doi: 10.1109/LCOMM.2019.2952595.
    [35]
    LEITE W S and DE LAMARE R C. List-based OMP and an enhanced model for DOA estimation with nonuniform arrays[J]. IEEE Transactions on Aerospace and Electronic Systems, 2021, 57(6): 4457–4464. doi: 10.1109/TAES.2021.3087836.
    [36]
    DAI Jisheng and SO H C. Real-valued sparse Bayesian learning for DOA estimation with arbitrary linear arrays[J]. IEEE Transactions on Signal Processing, 2021, 69: 4977–4990. doi: 10.1109/TSP.2021.3106741.
    [37]
    FU Haosheng, DAI Fengzhou, and HONG Ling. Two-dimensional off-grid DOA estimation with metasurface aperture based on MMV sparse Bayesian learning[J]. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 8005818. doi: 10.1109/TIM.2023.3318716.
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