高频地波雷达的"距离-多普勒"(Range-Doppler,R-D)数据与"恒虚警率"(Constant False-AlarmRate,CFAR)检测结果数据存在非直观性的问题,本文针对此问题,分析了地波雷达回波数据特点以及结果形式,研究了采用地理信息...高频地波雷达的"距离-多普勒"(Range-Doppler,R-D)数据与"恒虚警率"(Constant False-AlarmRate,CFAR)检测结果数据存在非直观性的问题,本文针对此问题,分析了地波雷达回波数据特点以及结果形式,研究了采用地理信息系统(Geographic Information System,GIS)技术对回波数据进行显示分析,对R-D与CFAR检测结果进行表达,实现高频数据在GIS环境下的表达处理与显示。本文采用GIS的栅格表达"距离-多普勒"数据,采用矢量数据结构表达CFAR检测结果,实现了地波雷达检测信息的直观显示;研究了高频地波雷达数据中特定距离一维谱信号的提取,实现了基于距离值的目标CFAR检测查询;针对雷达数据量大、处理时间长的问题,采用多线程处理机制实现了高效实时显示和分析。展开更多
Target recognition is a significant part of a Ballistic Missile Defense System(BMDS).However,most existing ballistic target recognition methods overlook the impact of data representation on recognition outcomes.This p...Target recognition is a significant part of a Ballistic Missile Defense System(BMDS).However,most existing ballistic target recognition methods overlook the impact of data representation on recognition outcomes.This paper focuses on systematically investigating the influences of three novel data representations in the Range-Doppler(RD)domain.Initially,the Radar Cross Section(RCS)and micro-Doppler(m-D)characteristics of a cone-shaped ballistic target are analyzed.Then,three different data representations are proposed:RD data,RD sequence tensor data,and RD trajectory data.To accommodate various data inputs,deep-learning models are designed,including a two-Dimensional Residual Dense Network(2D RDN),a three-Dimensional Residual Dense Network-Gated Recurrent Unit(3D RDN-GRU),and a Dynamic Trajectory Recognition Network(DTRN).Finally,an Electromagnetic(EM)computation dataset is collected to verify the performances of the networks.A broad range of experimental results demonstrates the effectiveness of the proposed framework.Moreover,several key parameters of the proposed networks and datasets are extensively studied in this research.展开更多
In the high speed target environment,there exists serious Doppler effect in the low pulse repetition frequency（LPRF） modulated frequency stepped frequency（MFSF） radar signal.The velocity range of the target is lar...In the high speed target environment,there exists serious Doppler effect in the low pulse repetition frequency（LPRF） modulated frequency stepped frequency（MFSF） radar signal.The velocity range of the target is large and the velocity is high ambiguous,so the single method is difficult to satisfy the velocity measurement requirement.For this problem,a novel method is presented,it is a combination of cross-correlation inner frame velocity measurement and range-Doppler coupling velocity measurement.The cross-correlation inner frame method,overcoming the low Doppler tolerance of the cross-correlation between frames,can obtain the coarse velocity of the high speed target,and then the precision velocity can be obtained with the range-Doppler coupling method.The simulation results confirm the method is effective,and also it is well real-time and easy to the project application.展开更多
Range-Doppler (RD) method and Reverse-Range-Doppler (RRD) method are combined together to achieve automatic geocoding of Synthetic Aperture Radar (SAR) image quickly and accurately in the paper. The RD method is first...Range-Doppler (RD) method and Reverse-Range-Doppler (RRD) method are combined together to achieve automatic geocoding of Synthetic Aperture Radar (SAR) image quickly and accurately in the paper. The RD method is firstly used to locate the four corners of the image, then the other pixels of the image can be located by Reverse-Range-Doppler (RRD) method. Resampling is performed at last. The approach has an advantage over previous techniques in that it does not require ground control points and is independent of spacecraft attitude knowledge or control. It can compensate the shift due to the assumed Doppler frequency in SAR image preprocessing. RRD simplifies the process of RD, therefore speeds up the computation. The experimental results show that a SAR image can be automated geocoded in 30 s using the single CPU (3 GHz) with 1 G memory and an accuracy of 10 m is attainable with this method.展开更多
A concept of space-surface bistatic synthetic aperture radar (SS-BSAR) passive imaging system is proposed,which is parasitic on the signal of COMPASS Navigation Satellite System (CNSS).The feasibility is demonstrated ...A concept of space-surface bistatic synthetic aperture radar (SS-BSAR) passive imaging system is proposed,which is parasitic on the signal of COMPASS Navigation Satellite System (CNSS).The feasibility is demonstrated by analyzing the signal ambiguity function and the range resolution as well as the system topology.Due to the multiple peaks of signal in the auto-correlation function,a new correlation is used to remove the side-peaks.A double-channel receiver is employed to receive the direct satellite signal and the ground reflected signal.The direct signal is a reference signal in range compression,and may also be used for transmitter-receiver signal synchronization.The reflected signal is raw data collected for imaging.Then,a modified range-Doppler imaging algorithm is derived based on the system geometric models and BSAR imaging principle.The proposed algorithm is verified via signal simulation.The work in this paper is of great value to the further use of COMPASS signal,as well as other global navigation satellite signals in passive imaging.展开更多
文摘高频地波雷达的"距离-多普勒"(Range-Doppler,R-D)数据与"恒虚警率"(Constant False-AlarmRate,CFAR)检测结果数据存在非直观性的问题,本文针对此问题,分析了地波雷达回波数据特点以及结果形式,研究了采用地理信息系统(Geographic Information System,GIS)技术对回波数据进行显示分析,对R-D与CFAR检测结果进行表达,实现高频数据在GIS环境下的表达处理与显示。本文采用GIS的栅格表达"距离-多普勒"数据,采用矢量数据结构表达CFAR检测结果,实现了地波雷达检测信息的直观显示;研究了高频地波雷达数据中特定距离一维谱信号的提取,实现了基于距离值的目标CFAR检测查询;针对雷达数据量大、处理时间长的问题,采用多线程处理机制实现了高效实时显示和分析。
基金supported by the Natural Science Basic Research Plan in Shaanxi Province of China(No.2023-JCYB-491).
文摘Target recognition is a significant part of a Ballistic Missile Defense System(BMDS).However,most existing ballistic target recognition methods overlook the impact of data representation on recognition outcomes.This paper focuses on systematically investigating the influences of three novel data representations in the Range-Doppler(RD)domain.Initially,the Radar Cross Section(RCS)and micro-Doppler(m-D)characteristics of a cone-shaped ballistic target are analyzed.Then,three different data representations are proposed:RD data,RD sequence tensor data,and RD trajectory data.To accommodate various data inputs,deep-learning models are designed,including a two-Dimensional Residual Dense Network(2D RDN),a three-Dimensional Residual Dense Network-Gated Recurrent Unit(3D RDN-GRU),and a Dynamic Trajectory Recognition Network(DTRN).Finally,an Electromagnetic(EM)computation dataset is collected to verify the performances of the networks.A broad range of experimental results demonstrates the effectiveness of the proposed framework.Moreover,several key parameters of the proposed networks and datasets are extensively studied in this research.
文摘In the high speed target environment,there exists serious Doppler effect in the low pulse repetition frequency（LPRF） modulated frequency stepped frequency（MFSF） radar signal.The velocity range of the target is large and the velocity is high ambiguous,so the single method is difficult to satisfy the velocity measurement requirement.For this problem,a novel method is presented,it is a combination of cross-correlation inner frame velocity measurement and range-Doppler coupling velocity measurement.The cross-correlation inner frame method,overcoming the low Doppler tolerance of the cross-correlation between frames,can obtain the coarse velocity of the high speed target,and then the precision velocity can be obtained with the range-Doppler coupling method.The simulation results confirm the method is effective,and also it is well real-time and easy to the project application.
文摘Range-Doppler (RD) method and Reverse-Range-Doppler (RRD) method are combined together to achieve automatic geocoding of Synthetic Aperture Radar (SAR) image quickly and accurately in the paper. The RD method is firstly used to locate the four corners of the image, then the other pixels of the image can be located by Reverse-Range-Doppler (RRD) method. Resampling is performed at last. The approach has an advantage over previous techniques in that it does not require ground control points and is independent of spacecraft attitude knowledge or control. It can compensate the shift due to the assumed Doppler frequency in SAR image preprocessing. RRD simplifies the process of RD, therefore speeds up the computation. The experimental results show that a SAR image can be automated geocoded in 30 s using the single CPU (3 GHz) with 1 G memory and an accuracy of 10 m is attainable with this method.
基金supported by the National Basic Research Program of China (Grant No.2011CB707001)
文摘A concept of space-surface bistatic synthetic aperture radar (SS-BSAR) passive imaging system is proposed,which is parasitic on the signal of COMPASS Navigation Satellite System (CNSS).The feasibility is demonstrated by analyzing the signal ambiguity function and the range resolution as well as the system topology.Due to the multiple peaks of signal in the auto-correlation function,a new correlation is used to remove the side-peaks.A double-channel receiver is employed to receive the direct satellite signal and the ground reflected signal.The direct signal is a reference signal in range compression,and may also be used for transmitter-receiver signal synchronization.The reflected signal is raw data collected for imaging.Then,a modified range-Doppler imaging algorithm is derived based on the system geometric models and BSAR imaging principle.The proposed algorithm is verified via signal simulation.The work in this paper is of great value to the further use of COMPASS signal,as well as other global navigation satellite signals in passive imaging.
