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摘要:
机载圆周合成孔径雷达(CSAR)作为一种新兴的成像模式，具有全方位观测、高空间分辨率和可三维成像等优点。随着CSAR成像技术的不断发展，现已逐渐成为对重点区域实施精确观测的有效手段之一。该文重点阐述了作者所在研究团队近年来在机载CSAR成像技术方面完成的研究工作，包括机载CSAR成像模型，空间分辨率评估，CSAR二维成像，基于单圆周CSAR的目标三维图像重构和多基线CSAR(HoloSAR)三维成像等技术，并给出了P, X两个频段机载CSAR的实测数据处理结果。已取得的研究成果证明了机载CSAR成像的有效性和实用性。该文主要内容基于作者2019年8月16日在“雷达学报第五届青年科学家论坛”上的学术报告。
Abstract:Circular Synthetic Aperture Radar (CSAR) is a novel imaging mode, which has the advantages of all-directional observation, high spatial resolution, and three-dimensional imaging. With the development of airborne CSAR imaging techniques, it has become one of the effective methods for key point area observation. This paper introduces works on airborne CSAR imaging techniques performed by our research team in recent years, including airborne CSAR imaging mode, spatial resolution evaluation, two-dimensional CSAR imaging, three-dimensional target image reconstruction based on a single CSAR, and three-dimensional holographic SAR imaging. In this paper, experimental results based on raw data acquired using airborne CSAR systems with P and X bands are presented. The obtained research results prove the effectivity and practicability of the airborne CSAR imaging mode. The content of this paper is based on a keynote speech presented by the author at the Fifth Young Scientists Forum of Journal of Radars on August 15, 2019.
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图 4 不同子孔径积累角下的分辨率变化曲线
Figure 4. Investigation of the resolutions with respect to the different subaperture angles
图 3 不同子孔径积累角与相对带宽比下的波数展宽因子仿真结果
Figure 3. The simulated results of HPBW factor versus to the different fractional bandwidths and subaperture angles
图 8 机载P波段LSAR和CSAR成像结果对比
Figure 8. Comparison of airborne P-band LSAR and CSAR imaging results
图 12 基于Gotcha实测数据的车辆CSAR成像
Figure 12. The imaging results of a vehicle in Gotcha public release dataset
图 13 基于单圆周CSAR的车辆目标三维图像重构流程
Figure 13. The flowchart of the 3D reconstruction of vehicle’s outline based single-pass CSAR
图 14 Gotcha数据及CSAR成像结果
Figure 14. The Gotcha data and its corresponding CSAR imaging result
图 15 车辆照片(上排)和对应的三维图像重构结果(下排)
Figure 15. The vehicle photos (upper rows) and their corresponding 3D image reconstruction results (lower rows)
图 18 Gotcha数据中雷达平台的实际运动轨迹
Figure 18. The actual trajectory of the radar platform in Gotcha data
图 20 车辆C1三维成像结果在不同平面上的二维投影图像
Figure 20. The two-dimensional projected images of the three-dimensional imaging results on different planes
表 1 车辆的真实尺寸与估计值对比(mm)
Table 1. The comparisons between the actual size of the vehicles and their estimated values
车辆编号(品牌) 长 宽 高 $l$ $\hat l$ $\Delta l$ $w$ $\hat w$ $\Delta w$ $h$ $\hat h$ $\Delta h$ 车辆A(Chevy Malibu) 4840 4814 26 1760 1616 144 1430 1433 –3 车辆B(Toyota Camry) 4790 4710 80 1780 1711 69 1410 1332 78 车辆C(Ford Taurus) 5020 4873 147 1850 1737 113 1470 1482 –12 车辆D(Nissan Maxima) 4770 4834 –64 1770 1687 83 1410 1371 39 车辆E(Nissan Sentra) 4510 4208 302 1710 1610 100 1440 1459 –19 车辆F(Hyundai Santa Fe) 4500 4517 –17 1840 1771 69 1670 1684 –14 车辆J(Chevy Prizm) 4420 4226 194 1690 1447 243 1360 1339 21 误差均值和标准差 ${\mu _{\Delta l} } = 95,\; {\sigma _{\Delta l} } = 128$ ${\mu _{\Delta w} } = {\rm{117} }, \;{\sigma _{\Delta w} } = {\rm{61} }$ ${\mu _{\Delta h} } = {\rm{13} },\; {\sigma _{\Delta h} } = {\rm{36} }$ 
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表 2 车辆的真实尺寸与估计值(mm)
Table 2. Comparison of the actual size of the vehicle with the estimated value
车辆编号(品牌) 长 宽 高 $l$ $\hat l$ $\Delta l$ $w$ $\hat w$ $\Delta w$ $h$ $\hat h$ $\Delta h$ 车辆A(Chevy Malibu) 4840 4800 40 1760 1750 10 1430 1450 –20 车辆B(Toyota Camry) 4790 4800 –10 1780 1800 –20 1410 1400 10 车辆C(Ford Taurus) 5020 5050 –30 1850 1850 0 1470 1480 –10 车辆D(Nissan Maxima) 4770 4750 20 1770 1800 –30 1410 1390 20 车辆E(Nissan Sentra) 4510 4350 160 1710 1450 260 1440 1430 10 车辆F(Hyundai Santa Fe) 4500 4500 0 1840 1850 –10 1670 1680 –10 车辆J(Chevy Prizm) 4420 4300 120 1690 1600 90 1360 1320 40 误差均值和标准差 ${\mu _{\Delta l} } = 40,\; {\sigma _{\Delta l} } = 70$ ${\mu _{\Delta w} } = {\rm{40} },\; {\sigma _{\Delta w} } = 100$ ${\mu _{\Delta h} } = {\rm{10} },\; {\sigma _{\Delta h} } = 20$
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