In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes consid...In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns.This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning.In the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation.Online dictionary learning is followed to separate real signals from jamming slices.Under the learned representation,time-varying MISRJs are suppressed effectively.Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.展开更多
Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotio...Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.展开更多
Based on the squint mode, a high resolution wide swath revisit synthetic aperture radar （SAR） imaging mode is pro- posed. The transmitting antennas are configured as the single phase center multiple azimuth beams （...Based on the squint mode, a high resolution wide swath revisit synthetic aperture radar （SAR） imaging mode is pro- posed. The transmitting antennas are configured as the single phase center multiple azimuth beams （SPC MAB）. The formed two beams point to two different directions to obtain two images of the observed scenario. The receiving antennas are configured as displaced phase center multiple azimuth beams （DPC MAB） to decrease the required pulse repetition frequency （PRF）. The de- creased PRF can ensure the high resolution wide swath imaging. Based on the analysis of the character of the return signal, a pro- cessing method named multiple beam multiple channel algorithm （MBMCA） is proposed to separate the aliased sub-beams＇ echoes. The separated echoes are focused respectively to get the revisit imaging to the observed scenario. The simulation experiments ve- rify the validity and correctness of the proposed imaging mode and processing algorithm.展开更多
Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its ...Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.展开更多
Not confined to a certain point,such as waveform,this paper systematically studies the low-intercept radio frequency(RF)stealth design of synthetic aperture radar(SAR)from the system level.The study is carried out fro...Not confined to a certain point,such as waveform,this paper systematically studies the low-intercept radio frequency(RF)stealth design of synthetic aperture radar(SAR)from the system level.The study is carried out from two levels.In the first level,the maximum low-intercept range equation of the conventional SAR system is deduced firstly,and then the maximum low-intercept range equation of the multiple-input multiple-output SAR system is deduced.In the second level,the waveform design and imaging method of the low-intercept RF SAR system are given and verified by simulation.Finally,the main technical characteristics of the lowintercept RF stealth SAR system are given to guide the design of low-intercept RF stealth SAR system.展开更多
The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the syn...The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.展开更多
近年来,卷积神经网络在合成孔径雷达(synthetic aperture radar,SAR)图像船舶检测中取得突出成就,但小目标检测方面仍然存在较大不足。对此,提出一种基于YOLO(you only look once)v5的改进检测网络,结合空间感知通道注意力、自注意力机...近年来,卷积神经网络在合成孔径雷达(synthetic aperture radar,SAR)图像船舶检测中取得突出成就,但小目标检测方面仍然存在较大不足。对此,提出一种基于YOLO(you only look once)v5的改进检测网络,结合空间感知通道注意力、自注意力机制和上下文特征融合策略,以提高小型船舶的检测性能。首先,通道注意力机制抑制了背景信息并强调目标特征,显著提高检测精度。其次,在YOLOv5的骨干网络和检测层中引入自注意力模块,以捕获全局信息,增强定位能力。最后,通过融合浅层和深层特征,补充特征提取中丢失的小目标信息,进一步提高检测精度。基于大规模SAR船舶监测数据集(large-scale SAR ship detection dataset version 1.0 LSSSDDv1.0)数据集的实验结果表明,改进后的网络的全类平均精度(mean average precision,mAP)0.5指标达78.9%,显著优于现有方法。展开更多
基金supported by the National Natural Science Foundation of China(61771372,61771367,62101494)the National Outstanding Youth Science Fund Project(61525105)+1 种基金Shenzhen Science and Technology Program(KQTD20190929172704911)the Aeronautic al Science Foundation of China(2019200M1001)。
文摘In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns.This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning.In the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation.Online dictionary learning is followed to separate real signals from jamming slices.Under the learned representation,time-varying MISRJs are suppressed effectively.Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.
基金supported by the National Natural Science Foundation for Young Scientists of China (61101182)
文摘Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.
基金supported by the National Natural Science Foundation of China(61271287)
文摘Based on the squint mode, a high resolution wide swath revisit synthetic aperture radar （SAR） imaging mode is pro- posed. The transmitting antennas are configured as the single phase center multiple azimuth beams （SPC MAB）. The formed two beams point to two different directions to obtain two images of the observed scenario. The receiving antennas are configured as displaced phase center multiple azimuth beams （DPC MAB） to decrease the required pulse repetition frequency （PRF）. The de- creased PRF can ensure the high resolution wide swath imaging. Based on the analysis of the character of the return signal, a pro- cessing method named multiple beam multiple channel algorithm （MBMCA） is proposed to separate the aliased sub-beams＇ echoes. The separated echoes are focused respectively to get the revisit imaging to the observed scenario. The simulation experiments ve- rify the validity and correctness of the proposed imaging mode and processing algorithm.
文摘Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.
基金supported by the National Key R&D Program of China(2017YFC1405600)the Fundamental Research Funds for the Central Universities(JB180213)
文摘Not confined to a certain point,such as waveform,this paper systematically studies the low-intercept radio frequency(RF)stealth design of synthetic aperture radar(SAR)from the system level.The study is carried out from two levels.In the first level,the maximum low-intercept range equation of the conventional SAR system is deduced firstly,and then the maximum low-intercept range equation of the multiple-input multiple-output SAR system is deduced.In the second level,the waveform design and imaging method of the low-intercept RF SAR system are given and verified by simulation.Finally,the main technical characteristics of the lowintercept RF stealth SAR system are given to guide the design of low-intercept RF stealth SAR system.
基金Project(61105020)supported by the National Natural Science Foundation of ChinaProject(13zxtk08)supported by the Key Research Platform for Research Projects of Southwest University of Science and Technology,China
文摘The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.
文摘近年来,卷积神经网络在合成孔径雷达(synthetic aperture radar,SAR)图像船舶检测中取得突出成就,但小目标检测方面仍然存在较大不足。对此,提出一种基于YOLO(you only look once)v5的改进检测网络,结合空间感知通道注意力、自注意力机制和上下文特征融合策略,以提高小型船舶的检测性能。首先,通道注意力机制抑制了背景信息并强调目标特征,显著提高检测精度。其次,在YOLOv5的骨干网络和检测层中引入自注意力模块,以捕获全局信息,增强定位能力。最后,通过融合浅层和深层特征,补充特征提取中丢失的小目标信息,进一步提高检测精度。基于大规模SAR船舶监测数据集(large-scale SAR ship detection dataset version 1.0 LSSSDDv1.0)数据集的实验结果表明,改进后的网络的全类平均精度(mean average precision,mAP)0.5指标达78.9%,显著优于现有方法。
