一种简化的机载MIMO雷达杂波特征相消器

针对机载多输入多输出(MIMO)雷达杂波抑制问题,提出一种简化的杂波特征相消器(EC).根据杂波在空时二维平面的先验分布离线构造杂波子空间.以此替代由协方差矩阵特征值分解(EVD)得到的杂波子空间,从而将最优权简化为一个确知投影矩阵与目标信号空时二维导向矢量的乘积,避免了传统EC方法中复杂的协方差矩阵估计和EVD运算,...     

扫描模式航管监视雷达风电场杂波检测与抑制

近年来,全球风力发电装机容量呈指数增长。研究表明,风轮机对其附近的航管(ATC)监视雷达会产生严重影响。风轮机杂波的有效检测及抑制,对于保证空中交通安全具有重要意义。首先提出了基于回波谱宽特征的航管监视雷达的风轮机杂波检测方法。针对扫描模式下航管监视雷达频谱分辨率较低的问题,将基于自回归(AR)模型的超分辨率方法和质量中心的概念应用于雷达回波的快速谱宽和谱中心估计算法中,提高谱宽估计的精度。其次针对扫描模式下的风轮机回波数据不是一个完整周期数据的问题,基于缺省数据幅度和相位估计(GAPES)算法实现了扫描模式下风轮机雷达回波缺省数据的估计,而后利用风轮机杂波的周期性抑制风轮机杂波。该算法实现了风轮机杂波的有效检测和抑制,并且其不受限于风轮机与飞机目标在同一个距离单元的情况。仿真结果验证了所提方法的有效性。     

非高斯杂波下自适应雷达目标检测新方法

在球不变随机向量(SIRV)非高斯杂波背景下,研究了多脉冲相参雷达目标的自适应检测问题。假设杂波具有相同的协方差矩阵结构和可能相关的纹理分量,提出了新的协方差矩阵估计器,并获得了相应的自适应归一化匹配滤波器(ANMF)。理论分析表明,在估计杂波分组大小与实际情况匹配时,所获得的ANMF对杂波功率水平和协方差矩阵结构均具有恒虚警率(CFAR)特性。仿真结果表明:当估计的杂波分组大小失配时,所获得的ANMF具有近似CFAR特性,并进一步分析了不同参数变化对所提检测器性能的影响。与已有的ANMF相比,所获得的ANMF具有更好的检测性能,且迭代次数更小,其相对于已知杂波协方差矩阵的最优归一化匹配滤波器(NMF)的检测损失也更小,具有很好的实际应用前景。     

机载MIMO雷达空时自适应杂波对消器

针对机载多输入多输出(MIMO)雷达杂波分布呈现空时耦合特性,提出一种空时自适应杂波对消器.利用机载MIMO雷达的脉冲回波数据,构造杂波对消器的系数矩阵.通过空时自适应杂波对消器的预处理,可以有效地抑制杂波,并通过与常规空时处理算法的级联,最终可以有效提高动目标的检测性能.实现了由传统地基雷达杂波对消器向机载运动平台的推广.仿真结果表明,这种自适应杂波对消器不仅适用于正侧视雷达,对于非正侧视雷达也同样适用.     

基于杂波子空间估计的MIMO雷达降维STAP研究

 多输入多输出(MIMO)雷达是近年来出现的一种新体制雷达,针对MIMO体制的机载雷达开展空时自适应处理（STAP）技术研究是值得进一步努力的方向。本文研究了机载MIMO雷达STAP技术的降维算法,通过对STAP技术杂波抑制原理进行分析,推导并得到一种基于杂波子空间的降维算法。结合扁长椭球波函数（PSWF）的特点,提出了一种基于杂波子空间估计的降维算法,并与若干降维算法的杂波抑制性能进行比较。结果表明,当存在阵元幅相误差时,该算法在保持杂波抑制性能的同时能够有效地降低STAP算法的运算量。     

基于稀疏重建的MIMO-OTH雷达多模杂波抑制算法

针对由多模传播引起的多普勒扩展杂波(SDC)严重影响天波超视距雷达(OTHR)对慢速船舰目标的检测这一问题,在基于多输入多输出体制的新一代天波超视距(MIMO-OTH)雷达系统下,利用空域信息抑制多模SDC。传统处理方法需要目标角度先验信息,而在实际中,该信息往往很难获得。为此,提出一种新的基于稀疏重建的多模杂波抑制算法。该算法将二维的稀疏角度搜索转变为一维的角度搜索,使运算量大大降低,且估计出的收发角(DOA-DOD)自动配对,同时可获得各个传播路径下信号的时间多普勒信息,达到了理想的MIMO-OTH雷达多模杂波抑制效果。仿真结果证明了所提算法的有效性。     

冲击杂波下的MIMO雷达DOA估计方法

研究了对称α稳定分布(SαS)冲击杂波下的多输入多输出（MIMO）雷达目标波达方向（DOA）估计问题,分别提出基于分数低阶最小方差无畸变响应(FrMVDR)的MIMO雷达DOA估计算法和无穷范数归一化最小方差无畸变响应（Inf-MVDR)算法。FrMVDR算法,首先进行冲击杂波特征指数的估计,然后使MIMO雷达接收阵列的分数低阶输出功率最小,实现MIMO雷达的DOA估计。为了避免FrMVDR算法对杂波特征指数估计,提出Inf-MVDR算法,首先用无穷范数对接收信号进行归一化处理,使归一化后的阵列输出功率有界,继而采用传统MVDR算法进行DOA估计。计算机仿真验证了上述两种算法的有效性;同时仿真结果还表明在冲击杂波下,MIMO雷达的空间分集特性可显著提高DOA估计的精度。     

先验失配条件下的知识辅助检测器稳健性分析

充分利用探测环境的先验信息是提高雷达探测能力的有效途径之一。先验信息必须在雷达检测算法设计阶段确定下来,因此先验信息与当前探测环境之间可能存在不一致性。以复合高斯杂波中的、利用纹理分量先验信息的知识辅助(KA)检测器作为研究对象,首先建立了该检测器检测性能与先验分布参数失配之间的量化关系,然后根据给定的杂波探测环境模型参数,分析了先验模型失配对检测性能的影响。分析结果表明:知识辅助检测器的稳健性与当前探测环境模型参数有关。进一步给出了先验模型失配的容许区间,当先验模型参数在这个区间内,知识辅助检测器性能优于不使用先验信息的检测器性能。     

基于约束序贯M估计的时空域融合红外杂波抑制

针对红外弱小目标检测中的强背景杂波干扰抑制问题进行研究,提出了一种基于参数约束序贯M估计的时空域融合自适应杂波抑制算法.该算法首先在分析序列图像帧间失配的基础上建立了一种改进的时空域融合背景预测模型,结合二维离散傅里叶快速变换图像配准和双线性插值方法进行灰度值估计;然后,基于约束序贯M估计方法进行模型参数的自适应估计,...     

一种机载雷达两级降维空时二维自适应处理方法

 提出了一种机载相控阵雷达杂波抑制的两级降维空时自适应处理(STAP)方法,即：先根据杂波分布先验信息进行空时局域化(JDL)降维处理,然后对局域化输出进行多级维纳滤波(MWF),实现二次降维。该方法综合了固定结构和自适应结构降维技术的优点,将JDL处理引入到MWF中,从而有效降低MWF的杂波自由度。计算机仿真和理论分析表明本文方法比JDL自适应处理方法和全空时MWF方法具有更小的运算量,对阵元随机幅相误差具有很好的容差能力,是一种稳健的两级降维自适应处理方法。最后,基于仿真和实测数据的实验验证了算法的有效性。     

Airborne/spacebased radar STAP using a structured covariance matrix

It is shown that partial information about the airborne/spacebased (A/S) clutter covariance matrix (CCM) can be used effectively to significantly enhance the convergence performance of a block-processed space/time adaptive processor (STAP) in a clutter and jamming environment. The partial knowledge of the CCM is based upon the simplified general clutter model (GCM) which has been developed by the airborne radar community. A priori knowledge of parameters which should be readily measurable (but not necessarily accurate) by the radar platform associated with this model is assumed. The GCM generates an assumed CCM. The assumed CCM along with exact knowledge of the thermal noise covariance matrix is used to form a maximum likelihood estimate (MLE) of the unknown interference covariance matrix which is used by the STAP. The new algorithm that employs the a priori clutter and thermal noise covariance information is evaluated using two clutter models: 1) a mismatched GCM, and 2) the high-fidelity Research Laboratory STAP clutter model. For both clutter models, the new algorithm performed significantly better (i.e., converged faster) than the sample matrix inversion (SMI) and fast maximum likelihood (FML) STAP algorithms, the latter of which uses only information about the thermal noise covariance matrix.     

Stap using knowledge-aided covariance estimation and the fracta algorithm

In the airborne space-time adaptive processing (STAP) setting, a priori information via knowledge-aided covariance estimation (KACE) is employed in order to reduce the required sample support for application to heterogeneous clutter scenarios. The enhanced FRACTA (FRACTA.E) algorithm with KACE as well as Doppler-sensitive adaptive coherence estimation (DS-ACE) is applied to the KASSPER I & II data sets where it is shown via simulation that near-clairvoyant detection performance is maintained with as little as 1/3 of the normally required number of training data samples. The KASSPER I & II data sets are simulated high-fidelity heterogeneous clutter scenarios which possess several groups of dense targets. KACE provides a priori information about the clutter covariance matrix by exploiting approximately known operating parameters about the radar platform such as pulse repetition frequency (PRF), crab angle, and platform velocity. In addition, the DS-ACE detector is presented which provides greater robustness for low sample support by mitigating false alarms from undernulled clutter near the clutter ridge while maintaining sufficient sensitivity away from the clutter ridge to enable effective target detection performance     

Improved clutter mitigation performance using knowledge-aided space-time adaptive processing

This paper presents a framework for incorporating knowledge sources directly in the space-time beamformer of airborne adaptive radars. The algorithm derivation follows the usual linearly-constrained minimum-variance (LCMV) space-time beamformer with additional constraints based on a model of the clutter covariance matrix that is computed using available knowledge about the operating environment. This technique has the desirable property of reducing sample support requirements by "blending" the information contained in the observed radar data and the a priori knowledge sources. Applications of the technique to both full degree of freedom (DoF) and reduced DoF beamformer algorithms are considered. The performance of the knowledge-aided beam forming techniques are demonstrated using high-fidelity simulated X-band radar data     

无需辅助数据的分布式目标自适应检测器

在非高斯背景和没有辅助数据的条件下,研究了高分辨率雷达分布式目标的自适应检测问题.首先采用有序检测理论和协方差矩阵的迭代估计方法粗略估计散射点集合,进一步利用迭代估计方法获得协方差矩阵的近似最大似然估计,提出了无需辅助数据的自适应检测器(ADWSD).ADWSD在非高斯背景下具有近似恒虚警率特性,且检测性能远好于修正的...     

Spectral-domain covariance estimation with a priori knowledge

A knowledge-aided spectral-domain approach to estimating the interference covariance matrix used in space-time adaptive processing (STAP) is proposed. Prior knowledge of the range-Doppler clutter scene is used to identify geographic regions with homogeneous scattering statistics. Then, minimum-variance spectral estimation is used to arrive at a spectral-domain clutter estimate. Finally, space-time steering vectors are used to transform the spectral-domain estimate into a data-domain estimate of the clutter covariance matrix. The proposed technique is compared with ideal performance and to the fast maximum likelihood technique using simulated results. An investigation of the performance degradation that can occur due to various inaccurate knowledge assumptions is also presented     

Multiband coherent radar detection against compound-Gaussianclutter

A Multiband GLRT-LQ (Generalized Likelihood Ratio Test-Linear Quadratic), MBGLRT-LQ, detector is derived for the coherent radar target detection against a compound-Gaussian clutter background. This scheme is an extension to the multiband case of the Asymptotically Optimum Detector (AOD), also derived under the name of GLRT-LQ in. The proposed multiband version of the algorithm shows two main advantages with respect to the original single-band algorithm. 1) For the adaptive implementation, it requires a much smaller area of homogeneous clutter echoes to estimate the covariance matrix of the interference; 2) it provides an optimum processing of the radar echoes when the radar operates in frequency agility, as electronic counter-countermeasure (ECCM) strategy. A closed form performance analysis is provided for the MBGLRT-LQ detector, which is used to compare it with the single-band version. An application to live recorded data is also presented to validate the obtained results     

与空时二维自适应滤波兼容的单脉冲测角新方法

针对机载相控阵雷达系统提出了一种空时二维自适应单脉冲测角方法 ,当存在阵元和通道幅相误差时它仍具有较高的测角精度。还给出了一种稳健的自适应和、差波束增益归一化方法 ,并讨论了所提方法的简化兼容实现方案。最后给出了基于高保真雷达杂波模拟数据的仿真实验结果