基于联合稀疏性的高分辨全极化雷达成像研究
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摘要
针对频率步进体制高分辨全极化雷达,本文研究了基于稀疏信号表示的高分辨全极化雷达成像,并提出了一种基于极化平滑l0范数算法的成像方法.算法中的联合稀疏性度量综合利用了目标在全极化下的散射特性,因而成像结果兼具全极化处理和稀疏优化算法的优点,不仅能以较少的观测回波获得高分辨距离像,还能全面准确反映目标全极化散射特性,有利于目标识别等进一步应用.仿真和暗室实测数据实验结果验证了本文方法的有效性.
For the stepped frequency high resolution full polarization radar, high resolution full polarization imaging method using spare signal representation is studied, and a novel imaging method based on polarization smoothed l0-norm algo- rithm is proposed in this paper.A new joint-sparsity is defined by exploiting the scattering characteristics of target in fully polarimetric channels synthetically in the presented algorithm, thus the imaging results combine the merits of fully polarimetric processing technique and sparse optimization algorithm, and can not only provide high resolution range profiles using limited measurements, but also indicate the true polarimetric scattering characteristics of the target, which are beneficial for further applications such as target recognition.Finally, the validity of the proposed approach is demonstrated using both simulated data and real data measured in an anechoic chamber.
For the stepped frequency high resolution full polarization radar, high resolution full polarization imaging method using spare signal representation is studied, and a novel imaging method based on polarization smoothed l0-norm algo- rithm is proposed in this paper.A new joint-sparsity is defined by exploiting the scattering characteristics of target in fully polarimetric channels synthetically in the presented algorithm, thus the imaging results combine the merits of fully polarimetric processing technique and sparse optimization algorithm, and can not only provide high resolution range profiles using limited measurements, but also indicate the true polarimetric scattering characteristics of the target, which are beneficial for further applications such as target recognition.Finally, the validity of the proposed approach is demonstrated using both simulated data and real data measured in an anechoic chamber.
引文
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[14]周剑雄,石志广,胡磊,等.基于频域稀疏非均匀采样的雷达目标一维高分辨成像[J].电子学报,2012,40 (5 ):926 -934.Zhou Jian Xiong,Shi Zhi Guang,Hu Lei,et al.Radar target one dimensional high resolution imaging based on sparse and non-uniform samplings in frequency domain[J].Acta Electronica Sincia,2012,40 (5 ):926 -934.(in Chinese)
[2]Martorella M,Giusti E,Capria A,et al.Automatic target recognition by means of polarimetric ISAR images and neural networks[J].IEEE Transactions on Geoscience and Remote Sensing,2009,47(11):3786-3794.
[3]Uhlmann S,Kiranyaz S,Gabbouj M,et al.Polarimetric SAR images classification using collective network of binary classifier[A].IEEE Joint Urban Remote Sensing Event(JURSE)[C].Munich,Germany:IEEE Press,2011.245-248.
[4]Babu P,Stoica P.Spectral analysis of nonuniformly sampled data-A review[J].Digital Signal Processing,2010,20 (2 ):359 -378.
[5]Potter L C,Parker J T,Ertin E,et al.Sparsity and compressed sensing in radar imaging[J].Proceedings of the IEEE,2010,96 (6 ):1010-1020.
[6]Samadi S,Cetin M,Masnadi-Shirazi.Sparse representationbased synthetic aperture radar imaging[J].IET Radar,Sonar and Navigation,2011,5 (2 ):182 -193.
[7]Wang H,Quan Y,Xing M,et al.ISAR imaging via sparse probing frequencies[J].IEEE Transactions on Geoscience and Remote Sensing Letters,2011,8 (3 ):451 -455.
[8]臧博,郭睿,张磊,等.基于ISAIL稀疏性的相位校正算法[J].电子学报,2011,39 (6 ):1272-1277.Zang Bo,Guo Rui,Zhang Lei,et al.A phase adjustment algorithm for ISAL based on sparsity[J].Acta Electronica Sincia,2011,39 (6 ):1272-1277.(in Chinese)
[9]Chen S S,Donoho D L,Sauders M A.Atomic decomposition by basis pursuit[J].SIAM Journal on Scientific Computing,1999,20 (1 ):33 -61.
[10]Mallat S,Zhang Z.Matching pursuit with time-frequency dictionary[J].IEEE Transactions on Signal Processing,1993,41 (12 ):3397-3415.
[11]Mohimani G H,Babaie-Zadeh M,Jutten C.A fast approachfor overcomplete sparse decomposition based on smoothed l0 norm[J].IEEE Transactions on Signal Processing,2009,57 (1 ):289 -301.
[12]Mohimani G H,Babaie-Zadeh M,Jutten C.Complex-valued sparse representation based on smoothed l0norm[A].International Conference on Acoustics,Speech and Signal Processing(ICASSP)2008[C].Las Vegas,USA:IEEE Press,2008.3881-3884.
[13]Patel V M,Easley G R,Healy D M,et al.Compressed synthetic aperture radar[J].IEEE Journal of Selected Topics in Signal Processing,2010,4 (2 ):244 -254.
[14]周剑雄,石志广,胡磊,等.基于频域稀疏非均匀采样的雷达目标一维高分辨成像[J].电子学报,2012,40 (5 ):926 -934.Zhou Jian Xiong,Shi Zhi Guang,Hu Lei,et al.Radar target one dimensional high resolution imaging based on sparse and non-uniform samplings in frequency domain[J].Acta Electronica Sincia,2012,40 (5 ):926 -934.(in Chinese)