小样本机载分布式雷达空时自适应处理方法

针对机载分布式雷达地杂波和干扰抑制的问题,提出一种基于小样本协方差重构的机载分布式雷达空时自适应处理（space-time adaptive processing,STAP）方法。该方法根据分布式雷达接收的杂波与干扰具有相关性不同的特点,首先利用小样本估计出各子雷达的杂波空时协方差矩阵和干扰全空域协方差矩阵,然后通过块对角延拓和时域拓展方法得到完整的空时协方差矩阵。所提方法利用全部空域自由度,在有效抑制杂波的同时抑制较多数量的干扰,克服了理想协方差矩阵估计时所面临的独立同分布（independent and identically distributed,i.i.d.）样本严重不足的问题。理论分析和仿真实验验证了所提方法的有效性。     

Doppler distributed clutter model of airborne radar and its parameters estimation

1 Introduction As a kind of effective active sensor, airborne radar may realize detecting, tracking and imaging of targets on the sea, ground or at low altitude[1—4], and it has been widely used both in civil and military areas. Since airborne radar normally works at the look-down mode, the ground clutter is commonly strong, e.g. the clutter-to-noise ratio (CNR) may reach 60—90 dB in some mountainous or urban areas. Meanwhile, the clut-ter Doppler spectrum is center-shifted and width-spre…     

机载双基地雷达STAP分析

空时自适应处理(STAP)是机载雷达信号处理中的一项关键技术,近年来机载双基地雷达STAP的研究成为热点.机载双基地雷达表现出复杂的杂波特性,即严重的杂波距离相关性,导致传统STAP方法杂波抑制性能严重下降.为此,本文首先对现有解决机载双基地雷达STAP面临的杂波距离相关性问题的典型方法的机理和特点进行了分析,然后对各...     

共形阵机载雷达杂波非平稳特性及抑制方法研究

分析了共形阵机载雷达的杂波非平稳特性,并结合该特性提出了一种非平稳杂波环境下的Doppler补偿方法.不同于传统的线阵天线,共形阵天线的三维空间结构决定了应在四维频域研究其杂波分布.针对这个特点,对共形阵机载雷达的杂波非平稳特性进行了理论分析,揭示了共形阵杂波非平稳现象的本质机理,并得出在任意摆放姿态下共形阵机载雷达均存在杂波非平稳现象这一结论.在此基础上,提出了在四维频域对主杂波进行联合补偿的空时自适应处理(space-time adaptive processing,STAP)方法.经仿真验证,在共形阵机载雷达非平稳杂波环境下,利用本文所提STAP方法的杂波抑制性能显著优于传统的Doppler补偿STAP方法.     

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.     

A novel STAP method for the detection of fast air moving targets from high speed platform

Space-time adaptive processing (STAP) is an effective method for detecting moving target in airborne/spaceborne radar.However,the detection of fast air moving targets from high speed platform is challenged by the range walk of both the clutter and moving targets.It is well known that keystone formatting can be used to compensate for the range walk of multiple moving targets simultaneously without using the knowledge of the motion parameters.However,in the presence of serious Doppler ambiguity of fast air moving targets,distribution of the clutter will be affected by the keystone formatting matched to the ambiguity number of targets,and as a result the STAP performance will degrade.In this paper,a novel STAP method is proposed for the detection of fast air moving targets from high speed platform,which can deal with the range walk of both clutter and targets.Effectiveness of the new method is verified via simulation examples.     

Efficient resource allocation scheme for multi-service based on interference mitigation in LTE-Advanced networks

The exponential growth of various services demands the increased capacity of the next-generation broadband wireless access networks, which is toward the deployment of femtocell in macrocell network based on orthogonal frequency division multiple access. However, serious time-varying interference obstructs this macro/femto overlaid network to realize its true potential. In this article, we present a macro services guaranteed resource allocation scheme, which can mitigate various dominant interferences and provide multiple services in macro/femto overlaid Third-Generation Partnership Project Long Term Evolution-Advanced networks. We model our multiple services resource allocation scheme into a multiobjective optimization problem, which is a non-deterministic polynomial-time （NP）-hard problem. Then, we give a low-complexity algorithm consisting of two layers based on chordal graph. Simulation results verify that the proposed scheme can achieve better efficiency than the previous works and raise the satisfaction ratio of Guaranteed Bit Rate （GBR） services while improving the average performance of non-GBR services.     

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。     

Enhanced knowledge-aided space–time adaptive processing exploiting inaccurate prior knowledge of the array manifold

The accuracy of the prior knowledge of the clutter environments is critical to the clutter suppression performance of knowledge-aided space–time adaptive processing (KA-STAP) algorithms in airborne radar applications. In this paper, we propose an enhanced KA-STAP algorithm to estimate the clutter covariance matrix considering inaccurate prior knowledge of the array manifold for airborne radar systems. The core idea of this algorithm is to incorporate prior knowledge about the range of the measured platform velocity and the crab angle, and other radar parameters into the assumed clutter model to obtain increased robustness against inaccuracies of the data. It first over-samples the space–time subspace using prior knowledge about the range values of parameters and the inaccurate array manifold. By selecting the important clutter space–time steering vectors from the over-sampled candidates and computing the corresponding eigenvectors and eigenvalues of the assumed clutter model, we can obtain a more accurate clutter covariance matrix estimate than directly using the prior knowledge of the array manifold. Some extensions of the proposed algorithm with existing techniques are presented and a complexity analysis is conducted. Simulation results illustrate that the proposed algorithms can obtain good clutter suppression performance, even using just one snapshot, and outperform existing KA-STAP algorithms in presence of the errors in the prior knowledge of the array manifold.     

利用高斯混合模型的SAR图像目标CFAR检测新方法

SAR（合成孔径雷达）图像杂波分布模型种类繁多且对实际地物的建模能力有限。在使用基于杂波统计模型的CFAR(恒虚警率)算法对SAR图像进行目标检测时,杂波统计模型的失配会导致检测结果产生较大的CFAR损失,算法精度不高。提出了一种基于高斯混合模型的CFAR检测新方法。该方法以理论上可以拟合任意形状概率密度分布的高斯混合模型对实际SAR图像的背景杂波进行拟合,利用拟合后得到的分布模型,根据CFAR检测的原理推导出目标检测阈值的计算公式完成目标的检测。新方法对服从不同分布模型的背景杂波,使用形式上统一的模型进行描述,克服了CFAR检测高度依赖背景杂波分布的缺点,提高了CFAR的通用性。实验结果表明,即使在背景杂波类型未知的情况下,新方法依然得到了良好的目标检测效果。     

Ground moving target detection and location based on SAR images for distributed spaceborne SAR

In recent years, a new concept of spaceborne SAR implementation has been propos- ed[1,2], i.e., the distributed (constellation) spaceborne SAR implementation in which sev-eral formation-flying small satellites (or micro-satellites) cooperates to perform multiple missions. The coherent combination of ground echoes acquired by all small satellites can significantly improve the performance of ground moving target indication (GMTI), SAR mapping, interferometric SAR (InSAR), etc. Since the …     

基于非均匀检测的机载雷达空时自适应处理方法

提出了一种新的非均匀杂波环境下的数据样本选取方法－－关联维数（ＣＤ）非均匀检测器,研究了非均匀杂波环境中改进干扰协方差矩阵的估计和自适应权的形成问题。仿真结果表明,非均匀检测器与空时自适应处理（ＳＴＡＰ）方法相结合,可显著地改进机载雷达的检测性能。     

Adaptive subspace detection of range-distributed target in compound-Gaussian clutter

This paper deals with high-resolution radar (HRR) adaptive detection of range-distributed target embedded in compound-Gaussian clutter which is modeled as a spherically invariant random process (SIRP). Using multiple dominant scattering (MDS) model of range-distributed target, we justify that range-distributed target can be modeled as a subspace random signal. The unknown deterministic parameters are replaced by their ML estimates and then the nonadaptive detector is proposed. A closed-form expression for the probability of false alarm of the nonadaptive detector is derived and it ensures CFAR property with respect to the unknown statistics of the clutter texture component. Moreover, an adaptive detector is obtained relying on a two-step GLRT-based design procedure. Performances of these proposed detectors are assessed through Monte Carlo simulations and are shown to have better detection performance compared with existing similar detector.     

Proposal-Copula-Based Fusion of Spaceborne and Airborne SAR Images for Ship Target Detection⁎⁎

In this paper, we consider the problem of fusion of synthetic aperture radar (SAR) images from spaceborne and airborne sensors and investigate its applications to inshore ship target detection. Existing SAR image fusion methods mainly focus on image denoising or texture enhancement, but show limited improvement of target-to-clutter ratios (TCRs) in composite images and lead to deteriorated target detection performance. To address this issue, we propose a new method for the fusion of spaceborne and airborne SAR images based on the target proposal and the copula theory (TPCT). In TPCT, target and clutter correspondence between different images are exploited to improve the TCRs of composite images. TPCT consists of three steps. First, target proposals are extracted from spaceborne and airborne SAR images and then fused to enhance the common ship target areas therein. Second, a new method to construct the joint probability density function (PDF) of clutter in spaceborne and airborne SAR images is presented to model the statistical dependence of clutter therein based on the copula theory. This copula-based joint PDF is used to suppress the clutter areas remained in the intersection of target proposals. Third, clues from the intersection of target proposals and the copula-based joint PDF of clutter are fused by the Hadamard product to generate the composite image with enhanced ship targets and the suppressed clutter. Experimental results based on measured spaceborne and airborne SAR data show that the proposed TPCT fusion method leads to higher TCRs of composite images and better performance in the ship detection task than other commonly used image fusion methods.     

基于相参脉冲串的多普勒雷达回波仿真

雷达回波是一切雷达信号处理和系统性能评估的基础,由于目标处于复杂的环境背景之下,所以雷达接收机端除了接收到真实目标的有用回波外,还将混入环境杂波以及接收机内部的噪声信号。利用Simulink工具箱丰富的信号发生及处理模块,对包括目标回波、噪声以及环境杂波等信号的脉冲多普勒雷达回波进行了仿真。通过在相参脉冲串雷达信号中加入目标RCS幅度起伏和延迟信息以及多普勒信息,进行仿真了目标的回波信号。同时,在对分布函数分析的基础上,由Simu-link基本模块产生的均匀分布信号作相应变换与处理,分别得到满足各种分布的典型雷达噪声。并对环境杂波和各种回波信号进行仿真。仿真结果与理论分析相一致,证明对雷达回波的有效性为信号的处理和分析提供了保障。     

机载前视风切变检测气象雷达的研究进展

机载气象雷达是商业飞机强制安装的机载电子设备,可以称得上是“双眼 ”,它对于保障飞行安全具有举足轻重的作用。目前,机载气象雷达关键技术尚掌握在国外 生 产厂商手中。本文从机载气象雷达系统和机载气象雷达涉及的信号处理技术（包括降水目标 检测、湍流检测和低空风切变检测、地杂波抑制等）两个方面论述了机载气象雷达的发展历 程,指出了其中的关键技术和尚待解决的问题。最后,本文针对下一代具有增强型检测能力的 机载气象雷达系统及其相关技术进行了评述。     

基于Stackelberg博弈的多输入多输出雷达信号与目标干扰优化

针对实际杂波环境中多输入多输出(MIMO)雷达与目标间检测与隐身的博弈问题,提出一种新的两步注水算法。首先建立时空编码模型;然后基于互信息量准则,用注水法分配目标干扰功率,用通用注水法分配雷达信号功率;最终得到强弱杂波环境Stackelberg博弈中目标占优和雷达占优的优化方案。仿真结果表明,雷达信号功率分配和通用注水水位变化规律均受杂波影响,两优化方案的互信息量在强杂波环境降低约50%,干扰影响系数分别降低0.2和0.25,互信息量受干扰影响程度降低,证明了所提算法的有效性。     

机载PD雷达模拟器目标检测仿真研究

在针对机载航电设备系统的飞行训练模拟器中，雷达模拟器与惯导、气象与地理、电子对抗模拟器构成一个分布式交互仿真系统。目标的检测模拟是雷达模拟器设计中的一个重要问题。该文讨论在一定的气象条件、地理环境等情况下，模拟机载PD雷达设备完成目标自动检测的方法。根据PD雷达回波频谱特点，将其划分为主杂波、旁瓣杂波区和热噪声区三个区间，分别计算目标的信噪(杂)比，采用加权形式的随机数与检测概率进行比较的方法进行判断。进行了仿真实验，结果表明该方法判断过程明确，具有实用性。     

星载GMTI 雷达系统及其空时自适应信号处理

地面动目标检测( GMTI) 是脉冲多普勒雷达的重要应用领域之一。星载GMTI 雷达系统比传统的机载系统具有更强的适应性和能够获得更好的检测性能而受到广泛关注。主要就星载分布式稀疏孔径GMTI 雷达系统的系统特点及其空时自适应信号处理( STAP) 方法作了较为深入的分析, 基于星载分布式均匀线性阵列( ULA ) GMTI 雷达系统参数获得了典型的STAP 算法信杂噪比( SINR) 损失特性和性能比较。     

Distributed target detection with polarimetric MIMO radar in compound-Gaussian clutter

This paper mainly deals with distributed targets detection with a polarimetric MIMO radar against compound-Gaussian clutter dominated scenario with unknown covariance matrix. First, the general polarimetric detecting problem of the distributed targets is developed to the MIMO radar, and then, the fully adaptive Generalized Likelihood Ratio Test (GLRT) is devised according to the well known two-step design procedure. Three covariance matrix estimation strategies using the secondary data are introduced to make derived receiver fully adaptive. A thorough performance assessment is given, and via several numerical examples, the results highlight that the spatial and polarization diversities can be exploited to improve the detection performance of the distributed targets in compound-Gaussian background, and it outperforms the phased-array counterpart, the adaptive loss is completely acceptable in practical applications. Meanwhile, the fixed-point estimation strategy is more suitable to implement the adaptive detection algorithm.