基于最小能量准则的参数估计圆周SAR三维成像方法
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摘要
针对圆周合成孔径雷达成像模式下应用参数化估计的三维成像算法效率低、精度差的问题,提出一种基于最小能量准则的参数估计圆周SAR三维成像算法。该算法首先对成像场景进行粗略网格划分,利用参数估计的方法得到目标的粗略位置,其次利用最小能量准则和精细化网格的方法得到目标精确三维位置和散射强度系数,最后通过CLEAN技术消除已估计点带来的影响,实现场景的三维成像。仿真实验结果表明:所提成像方法能有效对圆周观测下目标进行三维成像,同时与传统算法相比,解决了传统算法效率低、对目标估计不准确的问题,验证了所提算法的有效性。
In order to solve the problem of low efficiency and poor accuracy of the 3-D imaging algorithm using parameter estimation in the imaging mode of circular synthetic aperture radar, a 3-D imaging algorithm of parameter estimation circular SAR based on the minimum energy criterion was proposed. Firstly, the imaging scene was divided into a rough mesh with the algorithm, the method of parameter estimation was used to get the rough position of the target. Secondly, the minimum energy criterion and the fine grid method were used to get the accurate 3-D position and scattering intensity coefficient of the target. Finally, the CLEAN technology was used to eliminate the impact of estimated points and realize 3-D imaging of the scene. The simulation results show that the proposed imaging method can effectively carry out 3-D imaging of the objects under circular observation. Meanwhile,compared with the traditional algorithm, it solves the problems of low efficiency and inaccurate target estimation of the traditional algorithm, and verifies the effectiveness of the proposed algorithm.
In order to solve the problem of low efficiency and poor accuracy of the 3-D imaging algorithm using parameter estimation in the imaging mode of circular synthetic aperture radar, a 3-D imaging algorithm of parameter estimation circular SAR based on the minimum energy criterion was proposed. Firstly, the imaging scene was divided into a rough mesh with the algorithm, the method of parameter estimation was used to get the rough position of the target. Secondly, the minimum energy criterion and the fine grid method were used to get the accurate 3-D position and scattering intensity coefficient of the target. Finally, the CLEAN technology was used to eliminate the impact of estimated points and realize 3-D imaging of the scene. The simulation results show that the proposed imaging method can effectively carry out 3-D imaging of the objects under circular observation. Meanwhile,compared with the traditional algorithm, it solves the problems of low efficiency and inaccurate target estimation of the traditional algorithm, and verifies the effectiveness of the proposed algorithm.
引文
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[2]Zhang Lamei,Chen Zexi,Zou Bin.Fine classification of polarimetric SAR images based on 3D convolutional neural network[J].Infrared and Laser Engineering,2018,47(7):0703001.(in Chinese)
[3]Dong Lei,Lu Zhenwu,Liu Xinyue,et al.Research of the effect of echo outside field of view on fringes scanning imaging[J].Optics and Precision Engineering,2018,26(3):689-697.(in Chinese)
[4]Wang Qi,Xing Mengdao,Lu Guangyue,et al.SRMF-CLEAN imaging algorithm for space debris[J].IEEETranscation on Antennas&Propagation,2007,55(12):3524-3533.
[5]Soumekh M.Synthetic Aperture Radar Signal Processing with MATLAB Algorithms[M].New York:Wiley,1999.
[6]Zhao Y,Lin Y,Hong W,et al.Adaptive imaging of anisotropic target based on circular-SAR[J].Electronics Letters,2016,52(16):1406-1408.
[7]Bu Yuming,Du Xiaoping,Zeng Zhaoyang,et al.Research progress and trend analysis of non-scanning laser 3Dimaging radar[J].Chinese Optics,2018,11(5):711-727.(in Chinese)
[8]Zhang B,Pi Y,Min R.A CGRT-CLEAN Method for Circular SAR Three Dimensional Imaging[M]//Signal Processing,and Systems.New York:Springer,2012:41-52.
[9]Wang Baoping,Guo Junjie,Sun Chao,et al.ISAR imaging algorithm based on SRMF and sequence CLEAN[J].Infrared and Laser Engineering,2013,42(12):3410-3416.(in Chinese)王保平,郭俊杰,孙超,等.基于SRMF和序列CLEAN的空间碎片ISAR成像算法[J].红外与激光工程,2013,42(12):3410-3416.
[10]Wang Hao,Zhang Ye,Shen Honghai,et al.Review of image enhancement algorithms[J].Chinese Optics,2017,10(4):438-448.(in Chinese)
[11]Zhao Ning,Lu Jiaguo,Ge Jialong,et al.Research of P band circular polarization SAR[C]//2016 CIE International Conference on Radar(RADAR).IEEE,2017.
[12]Dupuis X,Martineau P.Very high resolution circular SARimaging at X band[C]//IEEE International Geoscience&Remote Sensing Symposium.IEEE,2014:930-933.
[13]Jia G,Buchroithner M F,Chang W,et al.Fourier-based 2-D imaging algorithm for circular synthetic aperture radar:analysis and application[J].IEEE Journal of Selected Topics in Applied Earth Observations&Remote Sensing,2016,9(1):475-489.
[14]Fan Zhiguo,Song Qiang,Qai Qingqing,et al.Underwater target polarization recovery method based on global parameter estimation[J].Optics and Precision Engineering,2018,26(7):1621-1632.
[15]Chen L,An D,Huang X.A back projection-based imaging for circular synthetic aperture radar[J].IEEE Journal of Selected Topics in Applied Earth Observations&Remote Sensing,2017,10(8):3547-3555.