In order to solve the problems that the current synthetic aperture radar(SAR)image target detection method cannot adapt to targets of different sizes,and the complex image background leads to low detection accuracy,an...In order to solve the problems that the current synthetic aperture radar(SAR)image target detection method cannot adapt to targets of different sizes,and the complex image background leads to low detection accuracy,an improved SAR image small target detection method based on YOLOv7 was proposed in this study.The proposed method improved the feature extraction network by using Switchable Around Convolution(SAConv)in the backbone network to help the model capture target information at different scales,thus improving the feature extraction ability for small targets.Based on the attention mechanism,the DyHead module was embedded in the target detection head to reduce the impact of complex background,and better focus on the small targets.In addition,the NWD loss function was introduced and combined with CIoU loss.Compared to the CIoU loss function typically used in YOLOv7,the NWD loss function pays more attention to the processing of small targets,so as to further improve the detection ability of small targets.The experimental results on the HRSID dataset indicate that the proposed method achieved mAP@0.5 and mAP@0.95 scores of 93.5%and 71.5%,respectively.Compared to the baseline model,this represents an increase of 7.2%and 7.6%,respectively.The proposed method can effectively complete the task of SAR image small target detection.展开更多
When the synthetic aperture focusing technology （SAFT） is used for the detection of the concrete, the signal-to-noise ratio （SNR） and detection depth are not satisfactory. Therefore, the application of SAFT is usu...When the synthetic aperture focusing technology （SAFT） is used for the detection of the concrete, the signal-to-noise ratio （SNR） and detection depth are not satisfactory. Therefore, the application of SAFT is usually limited. In this paper, we propose an improved SAFT technique for the detection of concrete based on the pulse compression technique used in the Radar domain. The proposed method first transmits a linear frequency modulation （LFM） signal, and then compresses the echo signal using the matched filtering method, after which a compressed signal with a narrower main lobe and higher SNR is obtained. With our improved SAFT, the compressed signals are manipulated in the imaging process and the image contrast is improved. Results show that the SNR is improved and the imaging resolution is guaranteed compared with the conventional short-pulse method. From theoretical and experimental results, we show that the proposed method can suppress noise and improve imaging contrast, and can also be used to detect multiple defects in concrete.展开更多
Open-celled porous NiAl intermetallics with adjustable pore characteristics and mechanical properties were successfully prepared by using spherical carbamide as space-holders via combustion synthesis.Examinations of m...Open-celled porous NiAl intermetallics with adjustable pore characteristics and mechanical properties were successfully prepared by using spherical carbamide as space-holders via combustion synthesis.Examinations of macroscopic and microscopic morphologies as well as the quasi-static compressive test for the resultant materials were carried out.Depending on the volume fraction and particle size of the carbamide,the porosity and pore size of the porous NiAl intermetallics can be controlled freely in a range of 57.57%-84.58% and 0.4-2.0 mm,respectively.Furthermore,quasi-static compressive tests indicate that the mechanical behavior of the present porous materials is in good agreement with the Gibson-Ashby model.展开更多
Synthetic Aperture Radar（SAR） is a more effective remote sensing data source for rice recognition and monitoring than optical remote sensing in the regions with more wet and cloudy sky due to its all-weather, all-ti...Synthetic Aperture Radar（SAR） is a more effective remote sensing data source for rice recognition and monitoring than optical remote sensing in the regions with more wet and cloudy sky due to its all-weather, all-time, high resolution and wide covering characteristics. This paper summarizes SAR types and their feature used for rice study, introduces the backscattering model for rice monitoring, and analyses the main factors influencing backscattering coefficient. The studies of rice recognition and monitoring based on SAR in domestic and abroad are reviewed and the futures in the related areas are prospected.展开更多
As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A ph...As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.展开更多
文摘In order to solve the problems that the current synthetic aperture radar(SAR)image target detection method cannot adapt to targets of different sizes,and the complex image background leads to low detection accuracy,an improved SAR image small target detection method based on YOLOv7 was proposed in this study.The proposed method improved the feature extraction network by using Switchable Around Convolution(SAConv)in the backbone network to help the model capture target information at different scales,thus improving the feature extraction ability for small targets.Based on the attention mechanism,the DyHead module was embedded in the target detection head to reduce the impact of complex background,and better focus on the small targets.In addition,the NWD loss function was introduced and combined with CIoU loss.Compared to the CIoU loss function typically used in YOLOv7,the NWD loss function pays more attention to the processing of small targets,so as to further improve the detection ability of small targets.The experimental results on the HRSID dataset indicate that the proposed method achieved mAP@0.5 and mAP@0.95 scores of 93.5%and 71.5%,respectively.Compared to the baseline model,this represents an increase of 7.2%and 7.6%,respectively.The proposed method can effectively complete the task of SAR image small target detection.
基金supported by the National Natural Science Foundation of China(No.11074273)the ministry of water resources'special funds for scientific research on public causes(No.201301061)
文摘When the synthetic aperture focusing technology （SAFT） is used for the detection of the concrete, the signal-to-noise ratio （SNR） and detection depth are not satisfactory. Therefore, the application of SAFT is usually limited. In this paper, we propose an improved SAFT technique for the detection of concrete based on the pulse compression technique used in the Radar domain. The proposed method first transmits a linear frequency modulation （LFM） signal, and then compresses the echo signal using the matched filtering method, after which a compressed signal with a narrower main lobe and higher SNR is obtained. With our improved SAFT, the compressed signals are manipulated in the imaging process and the image contrast is improved. Results show that the SNR is improved and the imaging resolution is guaranteed compared with the conventional short-pulse method. From theoretical and experimental results, we show that the proposed method can suppress noise and improve imaging contrast, and can also be used to detect multiple defects in concrete.
基金Project (51072104) supported by the National Natural Science Foundation of ChinaProject (BS2010CL038) supported by the Research Award Fund for Outstanding Young and Middle-aged Scientists of Shandong Province,China
文摘Open-celled porous NiAl intermetallics with adjustable pore characteristics and mechanical properties were successfully prepared by using spherical carbamide as space-holders via combustion synthesis.Examinations of macroscopic and microscopic morphologies as well as the quasi-static compressive test for the resultant materials were carried out.Depending on the volume fraction and particle size of the carbamide,the porosity and pore size of the porous NiAl intermetallics can be controlled freely in a range of 57.57%-84.58% and 0.4-2.0 mm,respectively.Furthermore,quasi-static compressive tests indicate that the mechanical behavior of the present porous materials is in good agreement with the Gibson-Ashby model.
基金Supported by a Grant from the Spatial Sample Selection and ManagementSystem for the Sample Survey in Rural Areas(2006AA120103)~~
文摘Synthetic Aperture Radar（SAR） is a more effective remote sensing data source for rice recognition and monitoring than optical remote sensing in the regions with more wet and cloudy sky due to its all-weather, all-time, high resolution and wide covering characteristics. This paper summarizes SAR types and their feature used for rice study, introduces the backscattering model for rice monitoring, and analyses the main factors influencing backscattering coefficient. The studies of rice recognition and monitoring based on SAR in domestic and abroad are reviewed and the futures in the related areas are prospected.
基金Supported by the National Natural Science Foundation of China(61071165)the Program for NewCentury Excellent Talents in University(NCET-09-0069)the Defense Industrial Technology Development Program(B2520110008)~~
文摘As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.
