基于广义旁瓣相消的机载雷达抗密集转发式干扰方法

密集转发式干扰不仅会引起雷达虚警,而且会抬高其附近单元的恒虚警率检测门限进而导致目标检测性能下降。另外,它还会污染空时自适应处理的训练样本,导致杂波抑制性能下降。针对这些问题,该文提出一种机载雷达抗密集转发式干扰算法。该算法首先估计干扰方向,然后用广义旁瓣相消技术在空域滤除干扰。广义旁瓣相消中的辅助通道为指向干扰方向的和波束,而其协方差矩阵则利用清晰区中挑选的干扰样本估计得到。该算法可以有效抑制密集转发式干扰,减少由其引起的虚警,改善雷达目标检测性能,同时该算法还具有结构简单,易于实现的优点。实验结果验证了该算法的有效性。     

极化-空域联合抗机载雷达欺骗式主瓣干扰

机载雷达欺骗式主瓣干扰不仅会引起大量虚警,还会污染空时自适应处理(STAP)器的训练样本,引起自适应方向图畸变,导致期望信号相消和杂波抑制性能下降。针对此问题,利用目标信号与干扰信号极化特性的差异,该文提出一种极化-空域联合自适应波束形成的方法来抑制欺骗式主瓣干扰。该方法首先在多普勒清晰区挑选干扰样本,并采用特征融合技术估计干扰协方差矩阵,然后采用重叠滑窗的子阵合成方式进行极化-空域联合自适应波束形成,在抑制主瓣干扰的同时为后续杂波抑制保留了空域自由度,最后通过STAP抑制剩余的杂波。该算法可以有效滤除密集欺骗式干扰,减少由其引起的虚警,改善机载STAP雷达的杂波抑制性能。仿真结果验证了该方法的有效性。     

一种高分辨率雷达海上目标自适应检测器

针对海上目标因波浪起伏和转向等导致的姿态变化引起的散射点起伏问题,在未知协方差矩阵的复高斯噪声背景下,研究了高距离分辨率雷达的距离扩展目标自适应检测问题.利用与待检测单元具有相同协方差矩阵结构的辅助教据估计未知噪声协方差矩阵,基于两步法检测策略获得了自适应检测器.恒虚警率特性分析表明,该检测器对不同噪声背景均具有很好的自适应特性.检测性能分析表明,该检测器对不同的目标模型具有很好的鲁棒性,且能有效避免“坍塌损失”.另外,通过增加传感器个数,可有效提高检测器性能.     

严重拖尾复合高斯杂波中目标的自适应极化检测

该文研究极化高分辨雷达在动态变化的杂波场景中自适应检测小目标的问题.将统计特性严重拖尾的杂波建模为纹理分量为逆伽马分布的复合高斯过程,借助于广义似然比检验和辅助数据得到了自适应极化检测器,并推导了该检测器的虚警概率表达式,证明了该检测器对协方差矩阵结构具有恒虚警特性.最后,利用仿真杂波数据验证了检测器检测性能的有效性.     

非高斯海杂波背景最优相干检测性能分析

非高斯海杂波背景下雷达目标检测一直是研究的重点。海杂波分布参数形式的多样化使得检测器对杂波平均功率的恒虚警特性无法保证,因此文中对描述非高斯海杂波的K分布、广义Pareto分布和逆高斯纹理复合高斯分布的参数形式进行了规范化,得到了规范化后的三种杂波分布对应的最优相干检测器。理论分析和实验验证了三个自适应检测器分别对杂波平均功率、目标多普勒频率和散斑协方差矩阵具有恒虚警特性。仿真实验表明:散斑协方差矩阵估计方法和辅助数据的数量均影响着自适应检测器的检测概率和虚警概率。     

Fast converging adaptive detection of Doppler-shifted,range-distributed targets

A generalized likelihood ratio test (GLRT) for the adaptive detection of a target or targets that are Doppler-shifted and distributed in range is derived. The unknown parameters associated with the hypothesis test are the complex amplitudes in range of the desired target and the unknown covariance matrix of the additive interference, which is assumed to be characterized as complex zero-mean correlated Gaussian random variables. The target's or targets' complex amplitudes are assumed to be distributed across the entire input data block (sensor × range). The unknown covariance matrix is constrained to have the reasonable form of the identity matrix (the internal noise contribution) plus an unknown positive semidefinite (psdh) matrix (the external interference contribution). It is shown via simulation for a variety of interference scenarios that the new detector has the characteristic of having a bounded constant false alarm rate (CFAR), i.e., for our problem, the probability of false alarm P_F for a given detection threshold is bounded by the P_F that results when no external interference is present. It is also shown via simulation that the new detector converges relatively fast with respect to the number of sample vectors K necessary in order to achieve a given probability of detection P_D     

改进的杂波协方差矩阵结构估计方法

在球不变随机向量建模的非高斯杂波背景下,针对现有协方差矩阵估结构计方法对杂波不具备完全自适应性以及计算复杂度高等问题,本文利用经验信息,提出了基于经验的自适应估计方法(E-AE),并将其作为初始化矩阵,再次利用经验信息进行迭代估计,得到了基于经验的自适应迭代估计方法(E-ARE)。E-AE和E-ARE只需要进行实数运算,减小了计算复杂度。从理论上证明了所提方法对应的ANMF对杂波纹理分量和协方差矩阵结构都具有CFAR特性,并通过仿真实验对其有效性进行了验证。最后,利用匹配滤波器的输出信杂比损失及相应的ANMF检测性能,对所提方法和已有方法进行效果评估,结果表明,本文方法具有收敛速度快、所需的辅助单元数少、信杂比损失小和对应的ANMF检测性能优等特点。      

The CFAR adaptive subspace detector is a scale-invariant GLRT

The constant false alarm rate (CFAR) matched subspace detector (CFAR MSD) is the uniformly most-powerful-invariant test and the generalized likelihood ratio test (GLRT) for detecting a target signal in noise whose covariance structure is known but whose level is unknown. Previously, the CFAR adaptive subspace detector (CFAR ASD), or adaptive coherence estimator (ACE), was proposed for detecting a target signal in noise whose covariance structure and level are both unknown and whose covariance structure is estimated with a sample covariance matrix based on training data. We show here that the CFAR ASD is GLRT when the test measurement is not constrained to have the same noise level as the training data, As a consequence, this GLRT is invariant to a more general scaling condition on the test and training data than the well-known GLRT of Kelly (1986)     

Performance of a class of adaptive detection algorithms innonhomogeneous environments

A two-dimensional (2-D) adaptive sidelobe blanker (ASB) detection algorithm was developed through experimentation as an extenuate for false alarms caused by undernulled interference encountered when applying the adaptive matched filter (AMF) in nonhomogeneous environments. The algorithm's utility has been demonstrated empirically. Considering theoretic performance analyses of the ASB detection algorithm as well as the AMF generalized likelihood ratio test (GLRT), and the adaptive cosine estimator (ACE), under nonideal conditions, can become fairly intractable rather quickly, especially in an adaptive processing context involving covariance estimation. In this paper, however, we have developed and exploited a theoretic framework through which the performance of these algorithms under nonhomogeneous conditions can be examined theoretically. It is demonstrated through theoretic analysis that in the presence of undernulled interference, the ASB is a pliable false alarm regulatory (FAR) detector that maintains good target sensitivity. A viable method of ASB threshold selection is also presented and demonstrated     

A CFAR adaptive subspace detector for second-order Gaussian signals

We study the problem of detecting subspace signals described by the Second-Order Gaussian (SOG) model in the presence of noise whose covariance structure and level are both unknown. Such a detection problem is often called Gauss-Gauss problem in that both the signal and the noise are assumed to have Gaussian distributions. We propose adaptive detectors for the SOG model signals based on a single observation and multiple observations. With a single observation, the detector can be derived in a manner similar to that of the generalized likelihood ratio test (GLRT), but the unknown covariance structure is replaced by sample covariance matrix based on training data. The proposed detectors are constant false alarm rate (CFAR) detectors. As a comparison, we also derive adaptive detectors for the First-Order Gaussian (FOG) model based on multiple observations under the same noise condition as for the SOG model. With a single observation, the seemingly ad hoc CFAR detector for the SOG model is a true GLRT in that it has the same form as the GLRT CFAR detector for the FOG model. We give an approximate closed form of the probability of detection and false alarm in this case. Furthermore, we study the proposed CFAR detectors and compute the performance curves.     

极化空时自适应匹配滤波检测器

针对极化空时自适应处理时目标极化状态和杂波协方差矩阵未知等实际瓶颈问题,提出了一种适应于机载极化阵列雷达的极化空时自适应匹配滤波(PST-AMF)检测算法.该检测算法先利用回波数据估计目标的极化状态,然后再将估值代入似然比得到了新的检验统计量,进一步推导了检测器虚警概率和检测概率的解析表达式,从理论上证明了该检测方法具备恒虚警(CFAR)特性.该检测器计算量比极化空时广义似然比检测器(PST-GLRT)少,易于工程实现.最后,仿真验证了在检测慢速运动目标时,其性能优于单个通道的空时自适应匹配滤波检测器(ST-AMF),具备较强的稳健性.     

Exact performance of STAP algorithms with mismatched steering andclutter statistics

Adaptive algorithms for receivers employing antenna arrays have received significant attention for radar systems applications. In the majority of these algorithms, the covariance matrix for the clutter-plus-noise is characterized by using samples taken from range cells surrounding the test cell. If the underlying covariance matrix of the test cell is different from the average covariance matrix of the surrounding range cells, significant performance degradation may result. Exact expressions for performance are derived for such cases, when any of a set of popular space-time adaptive processing (STAP) algorithms are used. Numerical evaluation of these expressions illustrates how variations in the parameters of these equations affect probability of detection and probability of false alarm. The equations are utilized to determine an upper bound an the performance of this class of STAP algorithms     

An Improved Adaptive Sidelobe Blanker

We propose a two-stage detector consisting of a subspace detector followed by the whitened adaptive beamformer orthogonal rejection test. The performance analysis shows that it possesses the constant false alarm rate property with respect to the unknown covariance matrix of the noise and that it can guarantee a wider range of directivity values with respect to previously proposed two-stage detectors. The probability of false alarm and the probability of detection (for both matched and mismatched signals) have been evaluated by means of numerical integration techniques.      

分布式目标的子空间双门限GLRT CFAR检测

 研究了分布式目标在球不变随机变量杂波中的检测问题,提出了一种具有恒虚警特性的双门限广义似然比检测器。分布式目标建模为子空间信号,在距离维和多普勒频率维同时扩展.第一门限的作用是筛选信杂比高的待检测距离单元.将选出的距离单元进行能量积累并与第二门限进行比较做出判决.假设杂波协方差矩阵已知,构造了双门限检测器,并通过推导检测器虚警概率说明其具有恒虚警特性.将基于辅助通道数据的杂波协方差矩阵的估计值替换假设已知的杂波协方差矩阵,得到一个自适应检测器.通过Monte Carlo仿真进行性能分析,说明检测器的有效性和鲁棒性.     

A Subspace-Based Adaptive Sidelobe Blanker

We propose a modified version of the adaptive sidelobe blanker (ASB) consisting of a generalized likelihood ratio test (GLRT)-based subspace detector followed by the adaptive coherence estimator. The performance analysis shows that it possesses the constant false alarm rate property with respect to the unknown covariance matrix of the noise in homogeneous environment and that it guarantees a wider range of “directivity” values with respect to the plain ASB. The probability of false alarm and the probability of detection (the latter for matched signals only) have been evaluated in closed form in homogeneous environment and by resorting to Monte Carlo simulation for the other considered cases.      

部分均匀海杂波中分组加权的协方差矩阵估计

本文主要研究空间部分均匀海杂波背景下协方差矩阵的估计问题。海杂波的空间部分均匀性和假目标干扰的不可避免性导致利用传统算法来估计海杂波协方差矩阵时存在较大的估计误差。为了减小该估计误差,本文对海杂波的参考样本进行分组处理,利用纹理的最大后验估计值作为加权系数,提出了分组加权样本协方差矩阵估计算法。考虑到假目标干扰的存在,利用协方差矩阵之间的差异提出了一致性因子,以确定干扰所在的分组,并剔除干扰。实测数据的实验结果表明,在存在假目标干扰的空间部分均匀海杂波背景下,本文提出的分组加权协方差矩阵估计算法不仅能有效剔除假目标,而且优于不分组算法约3dB。      

GLRT-based adaptive detection algorithms for range-spread targets

We address adaptive detection of a range-spread target or targets embedded in Gaussian noise with unknown covariance matrix. To this end, we assume that cells (referred to in the following as secondary data) that are free of signal components are available. Those secondary data are supposed to possess either the same covariance matrix or the same structure of the covariance matrix of the cells under test. In this context, we design detectors relying on the generalized likelihood ratio test (GLRT) and on a two-step GLRT-based design procedure. Remarkably, both criteria lead to receivers ensuring the constant false alarm rate (CFAR) property with respect to the unknown quantities. A thorough performance assessment of the proposed detection strategies, together with the evaluation of their processing cost, highlights that the two-step design procedure is to be preferred with respect to the plain GLRT. In fact, the former leads to detectors that achieve satisfactory performance under several situations of practical interest and are simpler to implement than those designed resorting to the latter     

复合高斯杂波中距离扩展目标的参数化Wald检测

本文研究复合高斯杂波环境中的距离扩展目标的自适应检测问题。有色杂波采用参数未知的自回归（AR）过程描述。结合Wald检测准则,仅需对H1假设条件下的未知参数进行最大似然估计,给出了一种新的基于参数化模型的扩展目标检测器——参数化Wald检测器。该检测器的检验统计量可解释为首先针对各个待测单元分别计算检验统计量,然后将所有待测单元的输出进行非相参累加,其对杂波的随机功率起伏具有恒虚警率(CFAR)特性。相比于常规的基于协方差矩阵的检测方法,参数化检测算法的执行过程不需要依赖辅助数据,仅利用待测扩展目标数据即可实现自适应处理,有效缓解了训练压力并降低了计算量。仿真实验表明,所提出的参数化Wald检测器的检测性能优于之前提出的参数化广义似然比检测器的性能。      

Performance Analysis of Multi-Antenna TD-CDMA Receivers with Estimation and Consideration of the Interference Covariance Matrix

The use of adaptive antennas in cellular mobileradio systems is considered to be one of the mostimportant measures to increase capacity. The consideredadaptive antenna concept is applied to the well-known TD-CDMA mobile radio air interface. TD-CDMA isadopted by ETSI for the UTRA TDD mode and is one of thecandidates considered by ITU for IMT-2000. In thereceivers of a TD-CDMA system the intracell multiple access interference (MAI) is eliminated byjoint detection. This detection algorithm also offersthe advantageous possibility of considering theintercell interference covariance matrix in order toenhance system performance. In this paper, amulti-antenna receiver structure with the capability toestimate the covariance matrix of the received intercellmultiple access interference (MAI) is presented. The benefits of taking into account theinterference covariance matrix both in channelestimation and data detection are shown by simulations.The directional channel models applied in thesimulations are derived from measured channel impulseresponses.     

复合高斯杂波下距离扩展目标的自适应检测

 研究了复合高斯杂波下的距离扩展目标自适应检测问题.基于辅助数据,利用采样协方差矩阵(SCM)和迭代(RE)估计矩阵,建立了自适应检测器AMSDD和基于动态阈值的ADT检测器,并分析了检测器的恒虚警率(CFAR)特性.理论分析表明,基于SCM的检测器只能保持对杂波协方差矩阵结构的自适应特性;而基于RE的检测器能同时获得对杂波协方差矩阵结构和纹理分量的CFAR特性.性能分析表明,对于AMSDD和ADT来说,与采用SCM估计器相比,采用RE估计器能使检测器获得更好的CFAR特性和检测性能.另外,基于RE的ADT检测器在目标散射点个数失配时具有很好的鲁棒性.