分布式星载SAR-GMTI系统仿真

仿真是进行分布式星载SAR地面动目标检测(GMTI)研究的重要方式。对分布式星载SAR-GMTI的系统仿真进行了全面讨论,内容包括地杂波建模\,动目标建模\,回波仿真方法、信号处理流程和方法,搭建了一个完整的仿真系统,用实验结果验证了该系统的可靠性。     

一种鲁棒的三通道SAR慢动目标检测、定位算法研究

该文研究三通道合成孔径雷达(SAR)在通道不平衡条件下的慢动目标检测、定位问题。实际系统中,由于雷达系统存在通道幅相不一致等误差,干涉SAR/GMTI技术的杂波抑制性能急剧下降,无法检测慢动目标并进行定位。本文提出了一种分块SAR图像通道误差校正算法,进而采用空域自适应处理对慢动目标进行检测及定位。仿真实验表明该方案对系统误差的敏感度显著下降,具有很好的鲁棒性,非常适合实际工程实施。     

极化MIMO雷达隐身目标检测性能研究*

多输入多输出(MIMO)雷达使用了远距分布的阵元,它利用了信号的空间分集增益来获取更多的目标信息。极化是另一种可以提高雷达系统性能的分集方式。当应对隐身目标时,传统的极化雷达在某些观测角度会遭受到较大的目标雷达截面积(RCS)衰减,而无法获得较好的检测性能。而在一个雷达系统中同时利用这两种分集增益,可以得到一种比传统极化雷达更具优势的新雷达检测系统——极化统计MIMO雷达,它可以更好地应对隐身目标检测。给出了相应的模型,并推导出了该雷达系统的检测性能解析式。将其与传统相控阵及非极化统计MIMO雷达比较,可以看到极化统计MIMO雷达的检测性能更佳。联系到隐身目标的特性,极化MIMO雷达的检测器特性应对它时具有显著优势。最后,以上方法通过仿真得到了验证。     

顶端优势在分布式系统中控制方面的探讨

本文在对现有的分布式入侵检测系统在控制方面特点的分析,提出了一个新的分布式入侵检测系统模型(DIDS)。在控制方面采用植物的顶端优势方法,通过生长素信息确立分布式入侵检测系统的主控模块,当主控模块遭到破坏后,迅速再次确立主控模块,当原主控模块恢复后再次获得主控地位。这样提高了入侵检测系统的性能,更好的保证系统的安全性。     

双通道机载雷达STAP紧凑系统设计

大数据流下的高精度实时处理是空时自适应处理(Space-time adaptive processing,STAP)系统实现的难题之一.在机载平台对尺寸、重量和功率(size,weight and power,SWAP)的约束条件下,STAP系统设计的目标是减少系统时延的同时增加数据吞吐率,本文对实测双通道机栽雷达采样数据进行了STAP并行系统的紧凑设计研究.基于选型平台设计了狭义局部并行全局串行(Restricted local-parallel-and-global-serial,RLPGS)结构与狭义局部串行全局并行(Restricted local-seiral-and-global-parallel,RLSGP)结构,并验证了任务数据不同调度方法的性能.该设计在单处理板上成功完成STAP处理的测试,结果满足设计要求.     

基于星载双天线的月球表面杂波抑制方法研究

研究星载双天线优化问题,针对更好地提取地下分层结构的回波,星载射频回波探测仪RES(Radio Echo Sounder)在行星内部结构探测.为了对表面杂波进行抑制,利用双天线抑制月球表面杂波的数学模型.对于星载RES系统,接收信号包括表面杂波和地下分层结构产生的回波.对杂波要进行有效地抑制.根据ESA火星快车MARSIS高频雷达系统中使用的双天线技术进行仿真.数值计算表明采用双天线杂波抑制法可以显著提高回波的信杂比,可以应用到月球探测中.     

星载差分吸收气压雷达的系统仿真与性能分析

提出一种工作在65~70 GHz强氧气吸收波段的星载差分吸收气压雷达,用以连续获取全球高时空分辨率的海面气压数据。通过对星载差分吸收气压雷达系统设计需求的分析,利用大气廓线数据和大气吸收系数模型,对海面气压差分吸收的性能进行了仿真及性能分析。仿真结果表明：通过强氧气吸收波段下的海面气压和差分吸收指数之间存在线性关系,星载差分吸收气压雷达在66 GHz与69 GHz的工作频率下晴空时得到的海面气压估计的均方根误差在2.6 mbar,不同云况下得到的海面气压估计的均方根误差在3~4 mbar,为后续雷达系统的设计与工程实现提供了参考与依据。     

PeerIDS系统的分析与优化

随着入侵检测系统(IDS)的地位日益重要.其分布式实现及其性能的提高,成为研究热点之一.为此,近来提出了基于对等模型(Peer-To-Peer)的一种分布式网络入侵检测系统--PeerIDS.该系统没有诸如单点失效一类的问题,可以实现公平高效的分布式处理.具有良好的可扩展性与自治性等.本文在详细分析其工作原理的基础上,讨论了其原型系统存在的若干不足.进而给出了优化系统性能的相应策略.     

针对地球自转影响的星载正侧面阵雷达杂波补偿方法

对于星载正侧面阵雷达,地球自转会导致地面杂波的多普勒分布发生展宽,使得杂波协方差矩阵估计不准确,致使空时自适应处理(STAP)的杂波抑制性能下降.针对该问题,本文提出了一种杂波补偿方法.该方法利用星载雷达的轨道参数对地球自转分量进行估计,然后对杂波数据进行多普勒补偿.该方法能够减轻由于地球自转引起的杂波多普勒分布展宽,...     

基于TS201的STAP并行处理系统实现

空时自适应处理(STAP)是新一代机载信号处理机的关键技术之一,它对系统的实时性有严格的要求.在分析实时STAP性能需求的基础上,利用基于TS201的高性能数字信号处理板,实现了一个STAP并行处理系统.结合STAP处理特点和系统体系结构,提出了一个局部串行全局并行的系统算法模型,并在模型实现中采用了高效的通信与同步方法.该模型有效的增强了系统的负载平衡特性.实测结果表明,系统满足STAP处理实时要求,并且有很好的可扩展特性.     

一种有效的直接数据域地面动目标检测方法

直接数据域(Direct data domain, DDD)方法利用子孔径平滑来从单个距离门中获得足够样本,但空域、时域孔径损失严重,使得空时自适应处理的地面动目标检测性能下降严重.针对该问题提出了一种不需要协方差矩阵估计和求逆的DDD方法,该方法将多级维纳滤波器引入到DDD的最优权求解过程中,在低的空时孔径损失下仍然能够获得好的性能.某机载实测雷达数据的实验结果验证了该方法的有效性.     

Robust and fast iterative sparse recovery method for space-time adaptive processing

Conventional space-time adaptive processing (STAP) requires large numbers of independent and identically distributed (i.i.d) training samples to ensure the performance of clutter suppression, which is hard to be achieved in practical complex nonhomogeneous environment. In order to improve the performance of clutter suppression with small training sample support, a robust and fast iterative sparse recovery method for STAP is proposed in this paper. In the proposed method, the sparse recovery of clutter spatial-temporal spectrum and the calibration of space-time overcomplete dictionary are achieved iteratively. Firstly, the robust solution of sparse recovery is derived by regularized processing, which can be calculated recursively based on the block Hermitian matrix property, afterwards the mismatch of space-time overcomplete dictionary is calibrated by minimizing the cost function. The proposed method can not only alleviate the effect of noise and dictionary mismatch, but also reduce the computational cost caused by direct matrix inversion. Finally, the proposed method is verified based on the simulated and the actual airborne phased array radar data, which shows that the proposed method is suitable for practical complex nonhomogeneous environment and provides better performance compared with conventional STAP methods.     

知识辅助的机载MIMO雷达降秩STAP算法

研究机载平台下的MIMO雷达空时自适应处理技术(STAP),基于广义旁瓣相消结构的多级维纳滤波器,提出了一种利用先验知识约束的MIMO雷达降秩STAP算法。通过利用干扰方向知识以及基于扁长椭球波函数估计的杂波子空间知识,在保证杂波抑制性能的基础上,大大降低了机载MIMO雷达STAP算法的运算量和样本需求量。同时,考虑了知识不匹配情况下,知识辅助对算法收敛性能的影响。仿真结果表明,当知识存在一定误差时,该算法仍能有效地改善STAP算法的收敛性能。     

Label-dependent sparse representation for synthetic aperture radar target configuration recognition

Synthetic aperture radar (SAR) target images suffer from target aspect angle sensitivity. To overcome the obstacle that seriously influences recognition performance, a label-dependent sparse representation (LSR) algorithm is proposed to realize SAR target configuration recognition in the sparse domain. The label of the training sample is embedded into the sparse representation (SR) model, and dictionaries are constructed individually to eliminate disturbances. LSR is implemented according to a statistical model based on the Gaussian mixture distribution (GMD). Experiments are conducted on a wide range of moving and stationary target acquisition and recognition (MSTAR) databases. The experimental results demonstrate the effectiveness of the proposed algorithm, which outperforms other existing algorithms in terms of recognition accuracy.     

Sparse microwave imaging:Principles and applications

This paper provides principles and applications of the sparse microwave imaging theory and technology.Synthetic aperture radar(SAR) is an important method of modern remote sensing.During decades microwave imaging technology has achieved remarkable progress in the system performance of microwave imaging technology,and at the same time encountered increasing complexity in system implementation.The sparse microwave imaging introduces the sparse signal processing theory to radar imaging to obtain new theory,new system and new methodology of microwave imaging.Based on classical SAR imaging model and fundamental theories of sparse signal processing,we can derive the model of sparse microwave imaging,which is a sparse measurement and recovery problem and can be solved with various algorithms.There exist several fundamental points that must be considered in the efforts of applying sparse signal processing to radar imaging,including sparse representation,measurement matrix construction,unambiguity reconstruction and performance evaluation.Based on these considerations,the sparse signal processing could be successfully applied to radar imaging,and achieve benefits in several aspects,including improvement of image quality,reduction of data amount for sparse scene and enhancement of system performance.The sparse signal processing has also been applied in several specific radar imaging applications.     

Design and performance analysis of orthogonal coding signal in MIMO-SAR

Multi-input multi-output (MIMO) radar which has evident advantages in many applications is a new radar system.Applying the MIMO technique to the earth observing synthetic aperture radar (SAR) system offers effective ways for the improvement of high resolution and wide swath imaging and ground moving target indication (GMTI) systems.Designing the optimal orthogonal waveform is a crucial problem in the research on MIMO radar.First,the index definition of synthetic integrated side-lobe level ratio (ISLR) is pr...     

多发多收SAR编码正交信号设计及性能分析

多发多收(MIMO)雷达是一种新的雷达体制,具有许多突出的优点.将MIMO技术应用于对地观测的SAR系统,将为高性能地完成高分辨率、宽测绘带成像和GMTI等功能提供有效途径.正交波形优化设计是MIMO雷达研究中的基础性关键问题.首先针对SAR应用的特点,考虑同频编码正交信号之间互相关能量影响,提出了综合积分旁瓣比指标定义.然后通过理论分析和一维数值仿真论证了同频编码正交信号综合积分旁瓣比性能无法满足SAR成像的要求;再通过数值仿真验证了失配滤波处理仍然无法改善同频编码正交信号的综合积分旁瓣比性能.最后优化设计了一组相位编码正交信号作为MIMO-SAR发射信号,通过MIMO-SAR成像和InSAR仿真试验,进一步验证了分析结论的有效性.     

基于迭代加权L1范数的稀疏阵列综合

针对阵列天线在相控阵雷达、卫星通信以及MIMO雷达系统等实际应用中重量、尺寸和成本受限的问题,提出了一种基于迭代加权[L1]范数的稀疏阵列综合方法。通过对稀疏阵列综合理论的分析,提出使用加权[L1]范数代替[L0]范数,避免了NP问题的求解;通过复数求导结合启发式近似方法对阵列激励进行优化选择,即可得到一个其辐射波形逼近给定的期望值的稀疏阵列。仿真结果表明,与现有的稀疏阵列综合方法相比,该方法可以在满足辐射特性的前提下得到阵元数目更少同时孔径更短的阵列。     

机载MIMO STAP收发天线联合设计研究

针对机载多输入多输出雷达进行动目标检测时,天线稀疏出现栅瓣导致盲速、天线密布导致冗余及布阵需考虑平台尺寸等问题,对天线结构进行研究.首先基于相位中心等效原理,讨论一定收发阵元数目下如何实现最大自由度和最大孔径;然后根据机载平台结构,设计更合理的收发天线布阵结构;最后结合多相编码进行空时自适应处理,实现动目标检测和杂波抑制.仿真实验表明,与其他天线结构相比,本文方法可获得更好的动目标检测性能.     

Clutter suppression and ground moving target imaging approach for hypersonic vehicle borne multichannel radar based on two-step focusing method

In this paper, a novel clutter suppression and ground moving target imaging approach is proposed for hypersonic vehicle (HSV) borne multichannel (MC) synthetic aperture radar (SAR) system. Compared with the traditional MC SAR ground moving target indication (GMTI) methods, the proposed algorithm can suppress clutter and decrease the moving target energy loss based on the improved MC clutter suppression method in the chirp Fourier transform (CFT) domain. Moreover, the moving target can be accurately focused by compensating the range curvature and the third order phase item. In addition, the motion parameters can be estimated precisely and the moving target can be focused accurately. Finally, the effectiveness of the proposed method is validated by the simulation examples.