针对双基地逆合成孔径雷达(bistatic inverse synthetic aperture radar,Bi-ISAR)稀疏孔径条件下机动目标的越距离单元徙动(migration through range cells,MTRC)补偿难的问题,提出了一种将Keystone变换与加权l 1范数稀疏约束最优化算...针对双基地逆合成孔径雷达(bistatic inverse synthetic aperture radar,Bi-ISAR)稀疏孔径条件下机动目标的越距离单元徙动(migration through range cells,MTRC)补偿难的问题,提出了一种将Keystone变换与加权l 1范数稀疏约束最优化算法相结合的补偿并成像的算法。Bi-ISAR稀疏孔径机动目标回波完成平动补偿后,假设目标图像各像元稀疏非同分布,对每个距离单元建立含Keystone变换参数与时变双基地角的变尺度傅里叶变换稀疏基,使用加权l 1范数稀疏约束最优化算法逐距离单元恢复方位向的散射系数并成像。实验结果证明了所提算法的有效性和鲁棒性。展开更多
The development of inverse synthetic aperture radar （ISAR） imaging techniques is of notable significance for moni- toring, tracking and identifying space targets in orbit. Usually, a well-focused ISAR image of a spa...The development of inverse synthetic aperture radar （ISAR） imaging techniques is of notable significance for moni- toring, tracking and identifying space targets in orbit. Usually, a well-focused ISAR image of a space target can be obtained in a deliberately selected imaging segment in which the target moves with only uniform planar rotation. However, in some imaging segments, the nonlinear range migration through resolution cells （MTRCs） and time-varying Doppler caused by the three-dimensional rotation of the target would degrade the ISAR imaging performance, and it is troublesome to realize accurate motion compensation with conventional methods. Especially in the case of low signal-to-noise ratio （SNR）, the estimation of motion parameters is more difficult. In this paper, a novel algorithm for high-resolution ISAR imaging of a space target by using its precise ephemeris and orbital motion model is proposed. The innovative contributions are as follows. 1） The change of a scatterer projection position is described with the spatial-variant angles of imaging plane calculated based on the orbital motion model of the three-axis-stabilized space target. 2） A correction method of MTRC in slant- and cross-range dimensions for arbitrarily imaging segment is proposed. 3） Coarse compensation for translational motion using the precise ephemeris and the fine compensation for residual phase errors by using sparsity-driven autofo- cus method are introduced to achieve a high-resolution ISAR image. Simulation results confirm the effectiveness of the proposed method.展开更多
文摘针对双基地逆合成孔径雷达(bistatic inverse synthetic aperture radar,Bi-ISAR)稀疏孔径条件下机动目标的越距离单元徙动(migration through range cells,MTRC)补偿难的问题,提出了一种将Keystone变换与加权l 1范数稀疏约束最优化算法相结合的补偿并成像的算法。Bi-ISAR稀疏孔径机动目标回波完成平动补偿后,假设目标图像各像元稀疏非同分布,对每个距离单元建立含Keystone变换参数与时变双基地角的变尺度傅里叶变换稀疏基,使用加权l 1范数稀疏约束最优化算法逐距离单元恢复方位向的散射系数并成像。实验结果证明了所提算法的有效性和鲁棒性。
基金supported by the National Natural Science Foundation of China(Grant Nos.61601496 and 61401024)
文摘The development of inverse synthetic aperture radar （ISAR） imaging techniques is of notable significance for moni- toring, tracking and identifying space targets in orbit. Usually, a well-focused ISAR image of a space target can be obtained in a deliberately selected imaging segment in which the target moves with only uniform planar rotation. However, in some imaging segments, the nonlinear range migration through resolution cells （MTRCs） and time-varying Doppler caused by the three-dimensional rotation of the target would degrade the ISAR imaging performance, and it is troublesome to realize accurate motion compensation with conventional methods. Especially in the case of low signal-to-noise ratio （SNR）, the estimation of motion parameters is more difficult. In this paper, a novel algorithm for high-resolution ISAR imaging of a space target by using its precise ephemeris and orbital motion model is proposed. The innovative contributions are as follows. 1） The change of a scatterer projection position is described with the spatial-variant angles of imaging plane calculated based on the orbital motion model of the three-axis-stabilized space target. 2） A correction method of MTRC in slant- and cross-range dimensions for arbitrarily imaging segment is proposed. 3） Coarse compensation for translational motion using the precise ephemeris and the fine compensation for residual phase errors by using sparsity-driven autofo- cus method are introduced to achieve a high-resolution ISAR image. Simulation results confirm the effectiveness of the proposed method.
