The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition...The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be influenced.For addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is pro-posed.First,the scatterers of ship targets are obtained via the target detection technique.Then,the EM algorithm is applied to extract the scatterers of a single ship target with a single IPP.Afterwards,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be generated.The proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most possibly.Results of simulated and real mea-sured data demonstrate the effectiveness of the proposed method.展开更多
Objectives:When detecting changes in synthetic aperture radar(SAR)images,the quality of the difference map has an important impact on the detection results,and the speckle noise in the image interferes with the extrac...Objectives:When detecting changes in synthetic aperture radar(SAR)images,the quality of the difference map has an important impact on the detection results,and the speckle noise in the image interferes with the extraction of change information.In order to improve the detection accuracy of SAR image change detection and improve the quality of the difference map,this paper proposes a method that combines the popular deep neural network with the clustering algorithm.Methods:Firstly,the SAR image with speckle noise was constructed,and the FFDNet architecture was used to retrain the SAR image,and the network parameters with better effect on speckle noise suppression were obtained.Then the log ratio operator is generated by using the reconstructed image output from the network.Finally,K-means and FCM clustering algorithms are used to analyze the difference images,and the binary map of change detection results is generated.Results:The experimental results have high detection accuracy on Bern and Sulzberger’s real data,which proves the effectiveness of the method.展开更多
SAR图像舰船目标检测时,因近海岸港口存在着复杂背景的问题,以至于重叠舰船目标无法被准确提取特征信息,造成近海岸的舰船目标出现漏检、误检的情况.针对以上问题,提出一种复杂场景下的SAR图像舰船检测算法,该算法基于YOLOv5进行改进,采...SAR图像舰船目标检测时,因近海岸港口存在着复杂背景的问题,以至于重叠舰船目标无法被准确提取特征信息,造成近海岸的舰船目标出现漏检、误检的情况.针对以上问题,提出一种复杂场景下的SAR图像舰船检测算法,该算法基于YOLOv5进行改进,采用SPPF结构加强提取特征信息,并融合原YOLOv5的SPP结构提取的特征信息,这种多级金字塔模块并列融合的方式能有效的检测多尺度舰船目标,使特征信息更好的表达;然后将原模型中的GIOU改进为CIOU,使其可以准确的回归出预测框的位置;最终为了更合理的筛选高于阈值的预测框,改进NMS(Non-Maximum-Suppression),采用Soft-NMS方法去惩罚衰减高于阈值的边框得分,合理的去除预测框.试验结果表明,该文改进的模型相比于原模型在SSDD、SAR-Ship-Dataset数据集上的mAP(mean Average Precision)提高了5.15%和5.06%,改进模型能有效检测近海岸中复杂背景下的SAR图像舰船目标.展开更多
This paper presents a modified frequency scaling algorithm for frequency modulated continuous wave synthetic aperture radar （FMCW SAR） data processing. The relative motion between radar and target in FMCW SAR during...This paper presents a modified frequency scaling algorithm for frequency modulated continuous wave synthetic aperture radar （FMCW SAR） data processing. The relative motion between radar and target in FMCW SAR during reception and between transmission and reception will introduce serious dilation in the received signal. The dilation can cause serious distortions in the reconstructed images using conventional signal processing methods. The received signal is derived and the received signal in range-Doppler domain is given. The relation between the phase resulting from antenna motion and the azimuth frequency is analyzed. The modified frequency scaling algorithm is proposed to process the received signal with serious dilation. The algorithm can effectively eliminate the impact of the dilation. The algorithm performances are shown by the simulation results.展开更多
Target micromotion not only plays an important role in target recognition but also leads to esoteric characteristics in synthetic aperture radar （SAR） imaging. This paper finds out an interesting phenomenon, i.e. th...Target micromotion not only plays an important role in target recognition but also leads to esoteric characteristics in synthetic aperture radar （SAR） imaging. This paper finds out an interesting phenomenon, i.e. the angular extent effect, in micro-motion target images formulated by the polar format algorithm. A micromotion target takes on multiple pairs of paired echoes （PEs） around the true point, and each PE extends for an angle which is exactly equal to the angular extent of the synthetic aperture, regardless of the micromotion frequency. The effect is derived and interpreted by using the characteristics of Bessel functions. Then it is demonstrated by simulation experiments of a target with different micromotion frequencies. The revelation and interpretation of the effect is highly beneficial to micromotion-target SAR image understanding as wel as target recognition.展开更多
基金This work was supported by the National Science Fund for Distinguished Young Scholars(62325104).
文摘The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be influenced.For addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is pro-posed.First,the scatterers of ship targets are obtained via the target detection technique.Then,the EM algorithm is applied to extract the scatterers of a single ship target with a single IPP.Afterwards,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be generated.The proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most possibly.Results of simulated and real mea-sured data demonstrate the effectiveness of the proposed method.
文摘Objectives:When detecting changes in synthetic aperture radar(SAR)images,the quality of the difference map has an important impact on the detection results,and the speckle noise in the image interferes with the extraction of change information.In order to improve the detection accuracy of SAR image change detection and improve the quality of the difference map,this paper proposes a method that combines the popular deep neural network with the clustering algorithm.Methods:Firstly,the SAR image with speckle noise was constructed,and the FFDNet architecture was used to retrain the SAR image,and the network parameters with better effect on speckle noise suppression were obtained.Then the log ratio operator is generated by using the reconstructed image output from the network.Finally,K-means and FCM clustering algorithms are used to analyze the difference images,and the binary map of change detection results is generated.Results:The experimental results have high detection accuracy on Bern and Sulzberger’s real data,which proves the effectiveness of the method.
文摘SAR图像舰船目标检测时,因近海岸港口存在着复杂背景的问题,以至于重叠舰船目标无法被准确提取特征信息,造成近海岸的舰船目标出现漏检、误检的情况.针对以上问题,提出一种复杂场景下的SAR图像舰船检测算法,该算法基于YOLOv5进行改进,采用SPPF结构加强提取特征信息,并融合原YOLOv5的SPP结构提取的特征信息,这种多级金字塔模块并列融合的方式能有效的检测多尺度舰船目标,使特征信息更好的表达;然后将原模型中的GIOU改进为CIOU,使其可以准确的回归出预测框的位置;最终为了更合理的筛选高于阈值的预测框,改进NMS(Non-Maximum-Suppression),采用Soft-NMS方法去惩罚衰减高于阈值的边框得分,合理的去除预测框.试验结果表明,该文改进的模型相比于原模型在SSDD、SAR-Ship-Dataset数据集上的mAP(mean Average Precision)提高了5.15%和5.06%,改进模型能有效检测近海岸中复杂背景下的SAR图像舰船目标.
文摘This paper presents a modified frequency scaling algorithm for frequency modulated continuous wave synthetic aperture radar （FMCW SAR） data processing. The relative motion between radar and target in FMCW SAR during reception and between transmission and reception will introduce serious dilation in the received signal. The dilation can cause serious distortions in the reconstructed images using conventional signal processing methods. The received signal is derived and the received signal in range-Doppler domain is given. The relation between the phase resulting from antenna motion and the azimuth frequency is analyzed. The modified frequency scaling algorithm is proposed to process the received signal with serious dilation. The algorithm can effectively eliminate the impact of the dilation. The algorithm performances are shown by the simulation results.
基金supported by the National Natural Science Foundationof China(6130214861101182)
文摘Target micromotion not only plays an important role in target recognition but also leads to esoteric characteristics in synthetic aperture radar （SAR） imaging. This paper finds out an interesting phenomenon, i.e. the angular extent effect, in micro-motion target images formulated by the polar format algorithm. A micromotion target takes on multiple pairs of paired echoes （PEs） around the true point, and each PE extends for an angle which is exactly equal to the angular extent of the synthetic aperture, regardless of the micromotion frequency. The effect is derived and interpreted by using the characteristics of Bessel functions. Then it is demonstrated by simulation experiments of a target with different micromotion frequencies. The revelation and interpretation of the effect is highly beneficial to micromotion-target SAR image understanding as wel as target recognition.
