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Boundary Analysis and Fast Imaging Arc Selection Experimental Demonstration for Bi-ISAR Imaging with Bistatic Angle Derivative Constraint
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摘要: 双基地ISAR(Bi-ISAR)成像技术在空天目标探测和识别等领域具有广阔的应用前景，然而由于双基构型的复杂多变，导致不同观测构型下的成像性能存在较大差异性，甚至会出现某些观测构型下的成像弧段无法进行二维成像的情况，因此快速准确的筛选出有用的Bi-ISAR成像弧段非常必要。针对空中运动目标的成像边界与成像弧段快速优选需求，该文提出了一种基于双基角一阶变化率约束的Bi-ISAR成像边界分析与快速成像弧段选取方法。首先构建了空中运动目标Bi-ISAR成像模型，推导出了与双基角一阶变换率相关的双基斜距历程表达式；然后分别从距离走动量和方位二次相位两个维度，建立了双基角一阶变化率与Bi-ISAR成像性能的理论边界，并分别给出了各自独立的成像边界约束条件；最后基于最小融合准则，给出了双基角一阶变化率约束下的Bi-ISAR成像边界，证明了基于双基角一阶变化率的边界约束等效为对Bi-ISAR成像弧段的选取，并基于仿真数据和实测数据进行了验证，仿真数据和实测数据的处理结果均验证了该文方法的有效性。Abstract: Bistatic inverse synthetic aperture radar (Bi-ISAR) imaging has a broad application in air and space target detection and recognition. However, due to the complexity and variability of the bistatic configuration, the Bi-ISAR imaging performance under different observation configurations varies greatly. There may even be imaging arcs under some observation configurations in which the two-dimensional imaging results cannot be acquired. Therefore,, it is quite essential to find out the useful Bi-ISAR imaging arcs quickly and accurately. Aiming at the need of fast and optimal selection of imaging boundary and imaging arcs for aerial moving targets, a boundary analysis and fast imaging arc selection method for Bi-ISAR imaging with bistatic angle derivative constraint is proposed. Firstly, the Bi-ISAR imaging model of moving target is constructed, and the expression of bistatic slant range history related to the bistatic angle derivative is derived. Then, the boundary of the Bi-ISAR imaging performance is theoretically analyzed from the dimensions of range cell migration (RCM) and azimuth-quadratic phase (AQP), and the corresponding constraints are figured out. Finally, based on the minimum fusion criterion, the Bi-ISAR imaging boundary constrained by the bistatic angle derivative is presented. Moreover, it is proved that the boundary constraint of the bistatic angle derivative is equivalent to the selection of the Bi-ISAR imaging arc. The processing results of both simulation data and measured data verify the effectiveness of the proposed method.
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图 2 不同带宽下的双基角一阶变化率随双基角变化曲线
Figure 2. Bistatic angle derivative curves with different bistatic angles under different bandwidths
图 3 不同转速下的双基角一阶变化率随双基角变化曲线
Figure 3. Bistatic angle derivative with different bistatic angles under different rotation velocities
图 6 不同观测构型下的双基角一阶变化率曲线
Figure 6. Curves of bistatic angle derivative for different observation configurations
图 7 目标速度为50 m/s场景下的双基角及双基角一阶变化率变化曲线
Figure 7. Curves of bistatic angle derivative in the imaging arc under the target velocity of 50 m/s
图 8 目标速度为 50 m/s场景下的单基ISAR和Bi-ISAR成像结果对比
Figure 8. Comparisons of monostatic ISRA and Bi-ISAR imaging results under the target velocity of 50 m/s
图 9 目标速度为50 m/s情况下的边缘点目标二维点扩展函数
Figure 9. Point spread functions of edge points under the target velocity of 50 m/s
图 10 目标速度为120m/s场景下的双基角及双基角一阶变化率变化曲线
Figure 10. Curves of bistatic angle derivative in the imaging arc under the target velocity of 120m/s
图 11 目标速度为 120 m/s场景下的单基ISAR和Bi-ISAR成像结果对比
Figure 11. Comparisons of monostatic ISRA and Bi-ISAR imaging results under the target velocity of 120m/s
图 12 目标速度为120 m/s情况下的边缘点目标二维点扩展函数
Figure 12. Point spread functions of edge points under the target velocity of 120 m/s
图 13 目标速度为200 m/s场景下的双基角及双基角一阶变化率变化曲线
Figure 13. Curves of bistatic angle derivative in the imaging arc under the target velocity of 200 m/s
图 14 目标速度为 200 m/s场景下的单基ISAR和Bi-ISAR成像结果对比
Figure 14. Comparisons of monostatic ISRA and Bi-ISAR imaging results under the target velocity of 200 m/s
图 15 目标速度为200 m/s情况下的边缘点目标二维点扩展函数
Figure 15. Point spread functions of edge points under the target velocity of 200 m/s
图 16 滑轨系统的Bi-ISAR试验构型
Figure 16. Bistatic ISAR imaging geometry with sliding rail system
图 17 试验场景下的双基角及双基角一阶变化率曲线
Figure 17. Curves of bistatic angle derivative in the experiment scenario
图 18 不同观测构型下的双基角一阶变化率曲线
Figure 18. Curves of bistatic angle derivative for different observation configurations
图 19 仿真场景下的双基角及双基角一阶变化率曲线
Figure 19. Curves of bistatic angle derivative in the simulation scenario
图 20 仿真场景下的转动角速度和角加速度
Figure 20. Rotational velocity and acceleration in the simulation scenario
图 21 仿真场景下的不同观测构型和成像结果对比
Figure 21. Comparisons of Bi-ISAR imaging results under the different geometry configurations and imaging arcs
图 22 不同观测构型情况下的边缘点目标二维点扩展函数
Figure 22. Point spread functions of edge points under different geometry configurations and imaging arcs
图 23 滑轨实验系统中不同成像弧段中下的速度曲线
Figure 23. The velocity curves of the imaging arc under different Bistatic configurations in the railway system
图 24 实测数据的不同观测构型和成像结果对比
Figure 24. Comparisons of Bi-ISAR imaging results under the different geometry configurations and imaging arcs with real data
表 1 雷达仿真系统参数
Table 1. Radar parameters for simulation experiment
参数 数值 参数 数值 目标飞行速度 50m/s, 120m/s,200m/s 信号带宽 500 MHz 目标角速度 2.5 mrad/s, 6 mrad/s,
10 mrad/s最短斜距 10 Km 目标角加速度 0.01 mrad/s2 信号时宽 25 μs 3 dB波束宽度 3° 目标高度 1 Km 脉冲重复频率 100 Hz 初始双基角 45° 
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表 2 目标速度为50 m/s情况下的边缘点目标的定量评估
Table 2. Quantitative evaluation results of edge points under the target velocity of 50 m/s
目标 项目 PSLR(dB) ISLR(dB) 最上边缘点 距离维 – 13.2850 – 11.0705 方位维 – 13.1720 – 10.9162 最左边缘点 距离维 – 13.2938 – 11.0818 方位维 – 12.9307 – 10.6883 最右边缘点 距离维 – 13.2873 – 11.0844 方位维 – 12.9270 – 10.6526 最下边缘点 距离维 – 13.2279 – 11.0688 方位维 – 13.2179 – 11.0100
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表 3 目标速度为120 m/s情况下的边缘点目标的定量评估
Table 3. Quantitative evaluation results of edge points under the target velocity of 120m/s
目标 项目 PSLR (dB) ISLR (dB) 最上边缘点 距离维 – 13.2543 – 11.0647 方位维 – 12.4715 – 10.1032 最左边缘点 距离维 – 13.2629 – 11.0415 方位维 – 12.2318 – 9.9696 最右边缘点 距离维 – 13.3084 – 11.0418 方位维 – 12.2530 – 9.9648 最下边缘点 距离维 – 13.3289 – 11.0704 方位维 – 12.4596 – 10.1217
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表 4 目标速度为200 m/s情况下的边缘点目标的定量评估
Table 4. Quantitative evaluation results of edge points under the target velocity of 200 m/s
目标 项目 PSLR (dB) ISLR (dB) 最上边缘点 距离维 – 13.2751 – 11.0256 方位维 – 8.6383 – 6.7553 最左边缘点 距离维 – 13.2841 – 11.0411 方位维 – 9.8544 – 7.6942 最右边缘点 距离维 – 13.2758 – 11.0422 方位维 – 9.8404 – 7.6784 最下边缘点 距离维 – 13.2893 – 11.0346 方位维 – 8.6907 – 6.7839
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