Frequency-Modulation Continuous-Wave Synthetic Aperture Radar(FMCW SAR)has shown great potential in the applications of civil and military fields because of its easy deployment and low cost.However,most of these work ...Frequency-Modulation Continuous-Wave Synthetic Aperture Radar(FMCW SAR)has shown great potential in the applications of civil and military fields because of its easy deployment and low cost.However,most of these work and analysis are concentrated on airborne FMCW SAR,where the characteristics of the imaging geometry and signal are much similar to that of traditional pulsed-SAR.As a result,a series of test campaigns of automobile-based FMCW SAR were sponsored by Institute of Electronics,Chinese Academy of Sciences(IECAS)in the autumn of 2012.In this paper,we analyze the imaging issues of FMCW SAR in automobile mode(named as near range mode),where a vehicle is used as moving platform and a large looking angle is configured.The imaging geometry and signal properties are analyzed in detail.We emphasize the difference of the near range mode from the traditional airborne SAR mode.Based on the analysis,a focusing approach is proposed in the paper to handle the data focusing in the case.Simulation experiment and real data of automobile FMCW SAR are used to validate the analysis.展开更多
When the classical constant false-alarm rate （CFAR） combined with fuzzy C-means （FCM） algorithm is applied to target detection in synthetic aperture radar （SAR） images with complex background, CFAR requires bloc...When the classical constant false-alarm rate （CFAR） combined with fuzzy C-means （FCM） algorithm is applied to target detection in synthetic aperture radar （SAR） images with complex background, CFAR requires block-by-block estimation of clutter models and FCM clustering converges to local optimum. To address these problems, this paper pro-poses a new detection algorithm： knowledge-based combined with improved genetic algorithm-fuzzy C-means （GA-FCM） algorithm. Firstly, the algorithm takes target region＇s maximum and average intensity, area, length of long axis and long-to-short axis ratio of the external ellipse as factors which influence the target appearing probabil- ity. The knowledge-based detection algorithm can produce preprocess results without the need of estimation of clutter models as CFAR does. Afterward the GA-FCM algorithm is improved to cluster pre-process results. It has advantages of incorporating global optimizing ability of GA and local optimizing ability of FCM, which will further eliminate false alarms and get better results. The effectiveness of the proposed technique is experimentally validated with real SAR images.展开更多
地基合成孔径雷达(Ground Based Synthetic Aperture Radar,GB-SAR)差分干涉技术可获得亚毫米级的测量精度,在人造大型建筑物和地表形变监测领域具有广泛的应用前景。在成像处理方面,地基SAR成像几何构型具有合成孔径极短、方位波束宽...地基合成孔径雷达(Ground Based Synthetic Aperture Radar,GB-SAR)差分干涉技术可获得亚毫米级的测量精度,在人造大型建筑物和地表形变监测领域具有广泛的应用前景。在成像处理方面,地基SAR成像几何构型具有合成孔径极短、方位波束宽、成像范围大的特点,与传统机载、星载SAR系统有很大差别,现有成像算法大都不能有效满足地基SAR实时成像处理需求。为此,本文提出一种基于子图像相干合成的地基SAR快速成像算法,能够实现地基SAR宽角度、近远场混合大场景数据的快速处理,得到伪极坐标系下成像结果。最后,利用仿真数据和实测数据对本算法进行了验证,证明了算法的有效性。展开更多
文摘Frequency-Modulation Continuous-Wave Synthetic Aperture Radar(FMCW SAR)has shown great potential in the applications of civil and military fields because of its easy deployment and low cost.However,most of these work and analysis are concentrated on airborne FMCW SAR,where the characteristics of the imaging geometry and signal are much similar to that of traditional pulsed-SAR.As a result,a series of test campaigns of automobile-based FMCW SAR were sponsored by Institute of Electronics,Chinese Academy of Sciences(IECAS)in the autumn of 2012.In this paper,we analyze the imaging issues of FMCW SAR in automobile mode(named as near range mode),where a vehicle is used as moving platform and a large looking angle is configured.The imaging geometry and signal properties are analyzed in detail.We emphasize the difference of the near range mode from the traditional airborne SAR mode.Based on the analysis,a focusing approach is proposed in the paper to handle the data focusing in the case.Simulation experiment and real data of automobile FMCW SAR are used to validate the analysis.
基金supported by the National Natural Science Foundation of China(6107113961171122)+1 种基金the Fundamental Research Funds for the Central Universities"New Star in Blue Sky" Program Foundation the Foundation of ATR Key Lab
文摘When the classical constant false-alarm rate （CFAR） combined with fuzzy C-means （FCM） algorithm is applied to target detection in synthetic aperture radar （SAR） images with complex background, CFAR requires block-by-block estimation of clutter models and FCM clustering converges to local optimum. To address these problems, this paper pro-poses a new detection algorithm： knowledge-based combined with improved genetic algorithm-fuzzy C-means （GA-FCM） algorithm. Firstly, the algorithm takes target region＇s maximum and average intensity, area, length of long axis and long-to-short axis ratio of the external ellipse as factors which influence the target appearing probabil- ity. The knowledge-based detection algorithm can produce preprocess results without the need of estimation of clutter models as CFAR does. Afterward the GA-FCM algorithm is improved to cluster pre-process results. It has advantages of incorporating global optimizing ability of GA and local optimizing ability of FCM, which will further eliminate false alarms and get better results. The effectiveness of the proposed technique is experimentally validated with real SAR images.
文摘提出了联合目标区域和阴影的合成孔径雷达(Synthetic Aperture Radar,SAR)目标识别方法。该方法采用椭圆傅里叶描述子描述目标区域和阴影的边界。根据目标区域和阴影的相对位置和大小关系,定义了描述其相对关系的特征矢量。采用稀疏表示分类器对目标区域和阴影的傅里叶描述子以及相对关系矢量分别进行分类,分类的结果利用决策层的线性加权方法进行科学融合。基于融合后的相似度判断目标类别,实现稳健的目标识别。采用MSTAR (Moving and Stationary Target Acquisition and Recognition)公共数据集进行了目标识别实验,验证了方法的有效性。
文摘地基合成孔径雷达(Ground Based Synthetic Aperture Radar,GB-SAR)差分干涉技术可获得亚毫米级的测量精度,在人造大型建筑物和地表形变监测领域具有广泛的应用前景。在成像处理方面,地基SAR成像几何构型具有合成孔径极短、方位波束宽、成像范围大的特点,与传统机载、星载SAR系统有很大差别,现有成像算法大都不能有效满足地基SAR实时成像处理需求。为此,本文提出一种基于子图像相干合成的地基SAR快速成像算法,能够实现地基SAR宽角度、近远场混合大场景数据的快速处理,得到伪极坐标系下成像结果。最后,利用仿真数据和实测数据对本算法进行了验证,证明了算法的有效性。
