作者中心
专家审稿
责编办公
编辑办公
Three-dimensional Multiple-Input Multiple-Output Radar Imaging Method Based on Integration of Multi-snapshot Images
-
摘要:
为了提高多输入多输出(MIMO)雷达三维成像沿运动方向的方位分辨率，该文从多快拍图像联合利用的角度入手，提出一种新的多输入多输出-逆合成孔径雷达(MIMO-ISAR)三维成像方法。其基本思路是通过对一段时间观测下二维平面阵列获取的多个单快拍三维图像进行相干处理，沿着散射点线性拟合的方向提取峰值并重构出新的三维图像。仿真实验结果表明，与单快拍三维成像方法相比，该方法可以显著提高成像结果沿运动方向的方位分辨率；与现有基于重排和插值的经典MIMO-ISAR方法相比，该方法对慢速和快速运动目标均适用，得到的成像结果聚焦良好并能够有效抑制沿运动方向的旁瓣。
-
关键词:
- 多输入多输出雷达 /
- 三维成像 /
- 多输入多输出-逆合成孔径雷达成像 /
- 多快拍联合 /
- 多普勒线性拟合
Abstract:To improve the cross-range resolution of three-dimensional (3-D) images obtained along the direction of movement by Multiple-Input Mmultiple-Output (MIMO) radar, a novel MIMO-ISAR 3-D imaging method that combines multi-snapshot images is proposed. This method integrates multiple single-snapshot 3-D images acquired by a planar antenna array during a specific period of observation and extracts the peak slice along the linear fitting direction of the scatterers to construct a new 3-D image. The simulation results demonstrated that the proposed method significantly improves the cross-range resolution of the imaging results along the direction of movement compared with other methods based on single-snapshot 3-D images. Additionally, compared with the classical MIMO-ISAR method based on rearrangement and interpolation, this method is suitable for both fast-moving and slow-moving targets. Moreover, the imaging results are well focused and the side lobes along the direction of movement are effectively suppressed.
-
图 4 10个快拍包络对齐后的回波示意图
Figure 4. Range profiles of 10 snapshots after envelope alignment
图 5 多快拍图像联合三维成像的流程示意图
Figure 5. Flowchart of the 3-D imaging algorithm based on multi-snapshot images integration
图 6 本文方法对散射点PSF分布的影响
Figure 6. The effect of the proposed method on the PSF of the scatterer
图 7 目标运动速度的方向余弦信息示意图
Figure 7. The direction cosine information of the target’s velocity
图 8 “云影”无人机仿真模型三维立体图及3视图
Figure 8. Three different projections and 3-D view of YunYing model
图 9 不同
$\gamma $ 角下的多普勒线性拟合结果Figure 9. The Doppler linear fitting results with different
$\gamma $ angles
图 12 本文方法对慢速目标三维成像结果
Figure 12. 3-D imaging results of the slow target by the proposed method
图 13 经典插值方法对慢速目标三维成像结果
Figure 13. 3-D imaging results of the slow target by the classical interpolation method
图 14 本文方法对快速目标三维成像结果
Figure 14. 3-D imaging results of the fast target by the proposed method
15 经典插值方法对快速目标三维成像结果
15. 3-D imaging results of the fast target by the classical interpolation method
表 1 雷达参数
Table 1. Configuration parameters of the radar system
具体参数 数值 具体参数 数值 载频 ${f_c}$ 10 GHz 带宽B 400 MHz 脉冲重复频率PRF 20 Hz 脉冲宽度 ${T_{\rm{r}}}$ 0.32 μs 码元周期 ${T_{{\rm{rs}}}}$ 2.5 ns 码元长度 ${N_{{\rm{pcm}}}}$ 128 
下载: 导出CSV
表 2 目标参数
Table 2. Configuration parameters of the target
具体参数 数值 具体参数 数值 散射点个数 11 机身长度 9.05 m 机翼宽度 17.8 m 相对雷达距离 12 km 飞行速度 100～620 km/h LOS方向 ${{{n}}_{\rm{0}}} = \left( { - 0.15,0.10,0.98} \right)$ 速度方向 $\gamma $ 角60° 速度方向 $\beta $ 角80°
下载: 导出CSV
-
[1] DING Shanshan, TONG Ningning, ZHANG Yongshun, et al. Super-resolution 3D imaging in MIMO radar using spectrum estimation theory[J]. IET Radar, Sonar & Navigation, 2017, 11(2): 304–312. doi: 10.1049/iet-rsn.2016.0233 [2] DUAN Guangqing, WANG Dangwei, MA Xiaoyan, et al. Three-dimensional imaging via wideband MIMO radar system[J]. IEEE Geoscience and Remote Sensing Letters, 2010, 7(3): 445–449. doi: 10.1109/LGRS.2009.2038728 [3] ZHAO Jia, ZHANG Min, WANG Xin, et al. Three-dimensional super resolution ISAR imaging based on 2D unitary ESPRIT scattering centre extraction technique[J]. IET Radar, Sonar & Navigation, 2017, 11(1): 98–106. doi: 10.1049/iet-rsn.2016.0049 [4] 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/JR18070ZHOU 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 [5] BLEH D, RÖSCH M, KURI M, et al. W-band time-domain multiplexing FMCW MIMO radar for far-field 3-D imaging[J]. IEEE Transactions on Microwave Theory and Techniques, 2017, 65(9): 3474–3484. doi: 10.1109/TMTT.2017.2661742 [6] MARKS D L, YURDUSEVEN O, and SMITH D R. Fourier accelerated multistatic imaging: A fast reconstruction algorithm for multiple-input-multiple-output radar imaging[J]. IEEE Access, 2017, 5: 1796–1809. doi: 10.1109/ACCESS.2017.2661068 [7] CHENG Binbin, CUI Zhenmao, LU Bin, et al. 340-GHz 3-D imaging radar with 4Tx-16Rx MIMO array[J]. IEEE Transactions on Terahertz Science and Technology, 2018, 8(5): 509–519. doi: 10.1109/TTHZ.2018.2853551 [8] 高敬坤, 邓彬, 秦玉亮, 等. 扫描MIMO阵列近场三维成像技术[J]. 雷达学报, 2018, 7(6): 676–684. doi: 10.12000/JR18102GAO Jingkun, DENG Bin, QIN Yuliang, et al. Near-field 3D SAR imaging techniques using a scanning MIMO array[J]. Journal of Radars, 2018, 7(6): 676–684. doi: 10.12000/JR18102 [9] LI Na, YANG Haining, LI Tingjun, et al. MIMO borehole radar imaging based on high degree of freedom for efficient subsurface sensing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(6): 3380–3391. doi: 10.1109/TGRS.2018.2884257 [10] FISHLER E, HAIMOVICH A, BLUM R, et al. MIMO radar: An idea whose time has come[C]. Proceedings of 2004 IEEE Radar Conference, Philadelphia, USA, 2004: 71–78. doi: 10.1109/NRC.2004.1316398. [11] FORSYTHE K W, BLISS D W, and FAWCETT G S. Multiple-input multiple-output (MIMO) radar: Performance issues[C]. Conference Record of the 38th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, 2004: 310–315. doi: 10.1109/ACSSC.2004.1399143. [12] ROBEY F C, COUTTS S, WEIKLE D, et al. MIMO radar theory and experimental results[C]. Conference Record of the 38th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, 2004: 300–304. doi: 10.1109/ACSSC.2004.1399141. [13] WHITE L B and RAY P S. Signal design for MIMO diversity systems[C]. Conference Record of the 38th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, 2004: 973–977. doi: 10.1109/ACSSC.2004.1399284. [14] TABRIKIAN J and BEKKERMAN I. Transmission diversity smoothing for multi-target localization[radar/sonar systems][C]. 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, Philadelphia, USA, 2005: 1041–1044. doi: 10.1109/ICASSP.2005.1416190. [15] TABRIKIAN J. Barankin bounds for target localization by MIMO radars[C]. The 4th IEEE Workshop on Sensor Array and Multichannel Processing, Waltham, USA, 2006: 278–281. doi: 10.1109/SAM.2006.1706137. [16] FISHLER E, HAIMOVICH A, BLUM R S, et al. Spatial diversity in radars-models and detection performance[J]. IEEE Transactions on Signal Processing, 2006, 54(3): 823–838. doi: 10.1109/tsp.2005.862813 [17] LI Jian, STOICA P, XU Luzhou, et al. On parameter identifiability of MIMO radar[J]. IEEE Signal Processing Letters, 2007, 14(12): 968–971. doi: 10.1109/lsp.2007.905051 [18] LEHMANN N H, FISHLER E, HAIMOVICH A M, et al. Evaluation of transmit diversity in MIMO-radar direction finding[J]. IEEE Transactions on Signal Processing, 2007, 55(5): 2215–2225. doi: 10.1109/tsp.2007.893220 [19] KRIEGER G. MIMO-SAR: Opportunities and pitfalls[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(5): 2628–2645. doi: 10.1109/TGRS.2013.2263934 [20] ZHU Yutao, SU Yi, and YU Wenxian. An ISAR imaging method based on MIMO technique[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(8): 3290–3299. doi: 10.1109/tgrs.2010.2045230 [21] ZHU Yutao and SU Yi. A type of M2-transmitter N2-receiver MIMO radar array and 3D imaging theory[J]. Science China Information Sciences, 2011, 54(10): 2147–2157. doi: 10.1007/s11432-011-4400-y [22] MA Changzheng, YEO T S, TAN C S, et al. Three-dimensional imaging of targets using colocated MIMO radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(8): 3009–3021. doi: 10.1109/tgrs.2011.2119321 [23] MA Changzheng, YEO T S, TAN C S, et al. Three-dimensional imaging using colocated MIMO radar and ISAR technique[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(8): 3189–3201. doi: 10.1109/tgrs.2011.2178607 -
计量
- 文章访问数: 3827
- HTML全文浏览量: 1353
- PDF下载量: 251
- 被引次数: 0
