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CROSS-TRACK THREE APERTURES MILliMETER WAVE SAR SIDE-LOOKING THREE-DIMENSIONAL IMAGING

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Journal of Electronics(China) 2012年第5期29卷 375-382页

作者： Teng Xiumin li Daojing li liechen liu Bo Pan Zhouhao Science and Technology on Microwave Imaging Laboratory Institute of Electronics Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences

The airborne cross-track three apertures MilliMeter Wave (MMW) Synthetic Aperture Radar (SAR) side-looking three-Dimensional (3D) imaging is investigated in this paper. Three apertures are distributed along the cross-track direction, and three virtual phase centers will be obtained through one-input and three-output. These three virtual phase centers form a sparse array which can be used to obtain the cross-track resolution. Because the cross-track array is short, the cross-track resolution is low. When the system works in side-looking mode, the cross-track resolution and height resolution will be coupling, and the low cross-track resolution will partly be transformed into the height uncertainty. The beam pattern of the real aperture is used as a weight to improve the Peak to SideLobe Ratio (PSLR) and Integrated SideLobe Ratio (ISLR) of the cross-track sparse array. In order to suppress the high cross-track sidelobes, a weighting preprocessing method is proposed. The 3D images of a point target and a simulation scene are achieved to verify the feasibility of the proposed method. And the imaging result of the real data obtained by the cross-track three-baseline MMW InSAR prototype is presented as a beneficial attempt.

关键词： Synthetic Aperture Radar (SAR) Sparse array Side-looking imaging Three-Dimensional (3D) imaging

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基于压缩感知的干涉逆合成孔径雷达成像研究

电波科学学报 2014年第1期29卷 19-25页

作者：刘波李道京李烈辰中国科学院电子学研究所微波成像技术重点实验室北京100190 中国科学院大学北京100190

为解决传统运动目标逆合成孔径雷达图像不能对目标定位的问题,提出了一种基于压缩感知技术的干涉逆合成孔径雷达运动目标成像方法.介绍了将压缩感知理论引入到运动目标逆合成孔径雷达成像模型中的方法,研究了压缩感知逆合成孔径雷达复... 详细信息

为解决传统运动目标逆合成孔径雷达图像不能对目标定位的问题,提出了一种基于压缩感知技术的干涉逆合成孔径雷达运动目标成像方法.介绍了将压缩感知理论引入到运动目标逆合成孔径雷达成像模型中的方法,研究了压缩感知逆合成孔径雷达复图像的相位误差和信噪比的关系,在此基础上,给出了基于压缩感知的干涉逆合成孔径雷达运动目标干涉测角定位方法实施流程.通过计算机仿真和实际数据处理结果验证了所提方法对运动目标成像定位的有效性.本文的研究成果扩展了压缩感知理论在逆合成孔径雷达中的应用前景。

关键词：压缩感知逆合成孔径雷达干涉逆合成孔径雷达保相性

基于变换域稀疏压缩感知的艇载稀疏阵列天线雷达实孔径成像

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雷达学报（中英文） 2016年第1期5卷 109-117页

作者：李烈辰李道京黄平平中国科学院电子学研究所微波成像技术重点实验室北京100190 中国科学院大学北京100049 内蒙古工业大学雷达技术研究所呼和浩特010051

该文针对飞艇平台,设计了基于组合巴克码的共形稀疏阵列,并对稀疏阵列的探测性能进行了分析。利用飞艇悬停的特点,可对前后不同时刻脉冲的实孔径成像结果进行干涉处理,去除散射单元的随机初相位,使图像在变换域稀疏。引入压缩感知方法,... 详细信息

该文针对飞艇平台,设计了基于组合巴克码的共形稀疏阵列,并对稀疏阵列的探测性能进行了分析。利用飞艇悬停的特点,可对前后不同时刻脉冲的实孔径成像结果进行干涉处理,去除散射单元的随机初相位,使图像在变换域稀疏。引入压缩感知方法,建立回波与变换域系数的关系,完成对地成像,可获得接近满阵阵列成效的图像质量。仿真数据处理结果验证了该方法的有效性。

关键词：压缩感知(CS) 变换域稀疏共形稀疏阵列实孔径成像

Observed and modelled snow and ice thickness in the Arctic Ocean with CHINARE buoy data

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Acta Oceanologica Sinica 2017年第8期36卷 66-75页

作者： TIAN Zhongxiang CHENG Bin ZHAO liechen VIHMA Timo ZHANG Wenliang li Zhijun ZHANG Zhanhai Ocean University of China(OUC) Qingdao 266100China Finnish Meteorological Institute(FMI) Helsinki F100931Finland National Marine Environmental Forecasting Centre(NMEFC) Beijing 100081China National Ocean Technology Center(NOTC) Tianjin 300112China Dalian University of Technology(DUT) Dalian 116024China Key Laboratory for Polar Science of the State Oceanic Administration Polar Research Institute of ChinaShanghai 200136China

Sea ice and the snow pack on top of it were investigated using Chinese National Arctic Research Expedition （CHINARE） buoy data. Two polar hydrometeorological drifters, known as Zeno ice stations, were deployed during CHINARE 2003. A new type of high-resolution Snow and Ice Mass Balance Arrays, known as SIMBA buoys, were deployed during CHINARE 2014. Data from those buoys were applied to investigate the thickness of sea ice and snow in the CHINARE domain. A simple approach was applied to estimate the average snow thickness on the basis of Zeno temperature data. Snow and ice thicknesses were also derived from vertical temperature profile data based on the SIMBA buoys. A one-dimensional snow and ice thermodynamic model （HIGHTSI） was applied to calculate the snow and ice thickness along the buoy drift trajectories. The model forcing was based on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts （ECMWF）. The Zeno buoys drifted in a confined area during 2003-2004. The snow thickness modelled applying HIGHTSI was consistent with results based on Zeno buoy data. The SIMBA buoys drifted from 81. 1°N, 157.4°W to 73.5°N, 134.9°W in 15 months during 2014-2015. The total ice thickness increased from an initial August 2014 value of 1.97 m to a maximum value of 2.45 in before the onset of snow melt in May 2015; the last observation was approximately 1 m in late November 2015. The ice thickness based on HIGHTSI agreed with SIMBA measurements, in particular when the seasonal variation of oceanic heat flux was taken into account, but the modelled snow thickness differed from the observed one. Sea ice thickness derived from SIMBA data was reasonably good in cold conditions, but challenges remain in both snow and ice thickness in summer.

关键词： temperature snow sea ice thickness ice mass balance buoy Arctic Ocean