Performance Analysis of Colocated MIMO Radars with Randomly Distributed Arrays in Compound-Gaussian Clutter

This paper focuses on the target detection problem for colocated MIMO radar with randomly distributed arrays in the presence of compound-Gaussian clutter with unknown Power Spectral Density (PSD). First, we derive the Generalized Likelihood Ratio Test (GLRT) assuming known covariance structure, and then, three different covariance estimation strategies, i.e., Sampled Covariance Matrix (SCM), Normalized Sampled Covariance Matrix (NSCM), and Fixed Point Estimation (FPE) Matrix, are introduced in place of the exact one to make the derived GLRT fully adaptive. Thorough numerical evaluations of the detection performance are provided and discussed.     

The Rao and Wald Tests Designed for Distributed Targets with Polarization MIMO Radar in Compound-Gaussian Clutter

In high resolution radars, the distributed target is usually modeled as a few isolated points referred to multiple dominant scattering centers, while the clutter is a compound-Gaussian model. Additionally, the polarimetric diversity can be exploited to enhance detection performance. Motivated by extending the detection problem of multiple-input multiple-output (MIMO) radar to such cases, this paper mainly addresses distributed targets detection problem with polarization MIMO radar against a compound-Gaussian clutter dominated scenario with unknown covariance matrix. The adaptive detectors based on Rao and Wald criteria are studied, and a two-step design procedure is adopted. Specifically, the Rao and Wald tests are derived by assuming a known covariance matrix, and then a suitable estimation of the covariance matrix based on the secondary data is inserted into the derived detectors to make them fully adaptive. Some numerical results are presented together with a polarization generalized likelihood ratio test (GLRT), showing that the derived detectors provide excellent detection performance in spiky clutter for distributed targets, and that the polarimetric diversity can be exploited to improve detection performance. Overall, the Wald test performs the best.     

MIMO Radar Detection in Non-Gaussian and Heterogeneous Clutter

In this paper, the generalized likelihood ratio test-linear quadratic (GLRT-LQ) has been extended to the multiple-input multiple-output (MIMO) case where all transmit–receive subarrays are considered jointly as a system such that only one detection threshold is used. The GLRT-LQ detector has been derived based on the Spherically Invariant Random Vector (SIRV) model and is constant false alarm rate (CFAR) with respect to the clutter power fluctuations (also known as the texture). The new MIMO detector is then shown to be texture-CFAR as well. The theoretical performance of this new detector is first analytically derived and then validated using Monte Carlo simulations. Its detection performance is then compared to that of the well-known Optimum Gaussian Detector (OGD) under Gaussian and non-Gaussian clutter. Next, the adaptive version of the detector is investigated. The covariance matrix is estimated using the Fixed Point (FP) algorithm which enables the detector to remain texture- and matrix-CFAR. The effects of the estimation of the covariance matrix on the detection performance are also investigated.      

基于杂波模型的相干雷达极化自适应恒虚警检测算法

该文研究了高斯杂波背景下相干雷达极化自适应检测问题。利用雷达回波的极化信息来提高检测性能。提出了一种基于杂波模型的极化自适应恒虚警检测算法,该算法比极化自适应匹配滤波器算法有更小的估计损失,并推导出了虚警概率表达式。仿真结果表明,所提出的检测算法相对于杂波协方差矩阵都有恒虚警的性质。     

部分均匀杂波环境中极化自适应Rao检测器

研究了机载极化雷达在部分均匀杂波背景下对于低慢小目标的自适应检测问题。基于Rao准则设计得到了极化自适应Rao检测器,分析了极化自适应Rao检测器的性能,推导得到了虚警概率和检测概率的解析表达式,证明了极化自适应Rao检测器对于杂波协方差矩阵和杂波功率比因子具有恒虚警率特性。理论分析和数值仿真表明,与基于广义似然比检验准则得到的自适应子空间检测器和自适应匹配检测器相比,极化自适应Rao检测器具有更好的检测性能和更低的计算复杂度。      

机载MIMO雷达广义最大似然检测器

该文针对机载MIMO雷达在未知统计特性的杂波中目标检测问题,首先给出广义最大似然(GLRT)检测器(MIMO-GLRT),利用MIMO雷达的空间分集特性提高检测性能,并推导出检测概率和虚警概率表达式。然后,基于MIMO雷达杂波协方差矩阵的块对角特性,给出一种简化MIMO-GLRT检测器,大大减小算法的复杂度,同时降低对参考单元数目的要求,并在只有两个接收雷达单元的情形下,推导出简化GLRT检测性能的表达式。结果表明,上述两种检测器相对于杂波协方差矩阵都具有恒虚警特性,能够在未知杂波背景下有效地检测目标。     

机载相干MIMO雷达杂波自由度估计研究

针对任意发射波形合成结构影响下的机载相干MIMO雷达杂波自由度的估计问题。论文提出了一种机载相干MIMO雷达杂波自由度估计的构造法,该方法利用发射波形合成结构直接构造等效矩阵代替杂波协方差矩阵进行求秩。通过递推分解等效矩阵,提出并证明了一种杂波自由度快速估计准则,建立了机载相干MIMO雷达发射波形合成结构、阵列稀布构型与杂波自由度之间的定量关系。研究表明:该方法和准则能够准确预测任意发射波形合成结构下的机载MIMO雷达的杂波特征谱结构。该理论既保证了降秩STAP算法性能的最优又具有较小的计算量,并为最优发射波形合成方案和MIMO STAP算法的设计提供了依据。     

恒虚警极化自适应子空间检测器

本文研究了在未知统计特性的局部均匀高斯杂波环境中的相干雷达极化自适应目标检测问题.基于广义似然比检验提出极化自适应子空间检测器,并推导出虚警概率和检测概率的理论表达式.研究结果证明该算法在均匀杂波环境和局部均匀杂波环境都有恒虚警的性质.比较了均匀杂波环境下极化自适应子空间检测器、极化广义似然比检验和极化自适应匹配滤波器算法的检测性能,仿真分析了不同极化状态局部均匀杂波环境下极化自适应子空间检测器算法在的检测性能.     

Polarimetric adaptive detection of range-distributed targets

We address the problem of polarimetric adaptive detection of range-spread targets in Gaussian noise with unknown covariance matrix. At the design stage, we model the target echo from each polarimetric channel as a deterministic signal known up to a scaling factor (possibly varying from cell to cell), which accounts for the polarimetric scattering properties of the target. We first show the failure of the generalized likelihood ratio test (GLRT) procedure to deal with this kind of problem, and thus, we propose a fully adaptive detector based on the method of sieves. We also derive the analytical expression for the probability of false alarm and show that the newly introduced receiver can be made bounded constant false alarm rate (CFAR). Finally, we present simulation results highlighting the performance gain that can be achieved by resorting to polarization diversity in conjunction with high resolution.     

An Efficient Adaptive Polarimetric Processor with an Embedded CFAR

To improve the detection performance of surveillance radars with polarization diversity, we developed an adaptive polarimetric processor and compared it with other polarimetric processors. We derived our adaptive polarimetric processor, called the polarization discontinuity detector (PDD), from the generalized likelihood ratio (GLR) test principle for the unspecified target component. We derived closed‐form expressions of its probabilities of detection and false alarm, and compared its performance to that of the adaptive polarization canceller (APC) and Kelly's GLR processor. The PDD had a performance similar to Kelly's GLR in Gaussian clutter, and both the PDD and Kelly's GLR, which have embedded constant false alarm rates (CFARs), outperformed the APC, especially when the target polarization state was close to the clutter's polarization state. The important difference is that the PDD is much simpler than Kelly's GLR for hardware/software implementation, because the PDD does not require a costly two‐parameter filter bank to cover the unknown target polarization state as Kelly's GLR does.     

基于功率中值和归一化采样协方差矩阵的自适应匹配滤波检测器

在非均匀海杂波环境中,参考单元中的异常单元限制了采样协方差矩阵(SCM)的估计性能,从而影响了传统自适应匹配滤波(AMF)检测器的检测性能。而考虑删除异常单元的方法在参考单元数目有限时可能导致矩阵的奇异性。鉴于此,在保持参考单元数目不变条件下,该文设计一种基于功率中值与归一化采样协方差矩阵(MNSCM)的估计方法,并将其与匹配滤波器(MF)相结合,构造一种新型的自适应匹配滤波检测器。与传统的自适应匹配滤波相比,该文设计的检测器在实测和仿真海杂波数据条件下均具有明显的性能优势。     

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.     

MIMO雷达检测性能分析

多输入多输出(MIMO)雷达是最近所提出的一种新型的雷达体制。通过利用空间分集和角度分集,从而避免了雷达目标的多径衰落问题。这里主要分析了MIMO雷达基于似然比的检测性能。另外,这里也将MIMO雷达跟相控阵雷达的检测性能做了对比,仿真结果表明MIMO雷达相比传统雷达具有的优异的检测性能。     

MIMO系统中一种改进的盲MMSE空时多用户检测算法

针对MIMO系统,提出了一种改进的基于子空间的盲MMSE空时多用户检测算法。该算法结合MIMO系统的空间分集技术与Alamouti空时分组码方案,预估计MIMO信道信息并对信号子空间进行预处理,使用正交性能和稳态性能较好的NOOja算法跟踪信号子空间,在自适应过程中对特征值矩阵进行优化,去除迭代带来的噪声,解决了跟踪过程中信号特征值矩阵的近似估计会带来检测器性能恶化的问题。仿真结果表明这种算法,能有效地抑制多址干扰,抗远近效应能力强,尤其在低信噪比、远近效应明显的恶劣环境下,有稳定良好的性能表现。      

非完备杂波先验知识场景下MIMO-STAP稳健波形设计

本文考虑了色高斯干扰条件下MIMO STAP稳健波形优化问题以提高非完备杂波先验知识条件下多输入多输出（MIMO）雷达体制下空时自适应处理（STAP）最坏情况下探测性能。由于高斯干扰（包括杂波、干扰以及热噪声）场景下最大化系统输出信干噪比（SINR）等价于最大化MIMO STAP检测性能,因而在本文所建立杂波协方差估计误差的模型基础上,总功率发射以及参数不确定凸集约束下,经推导可得稳健波形优化问题。为求解得到的复杂非线性问题,本文提出了一种迭代算法以优化发射波形相关阵（WCM）从而最大化凸不确定集上最差情况下的输出SINR进而改善最差情况下MIMO STAP的检测性能。通过利用对角加载（DL）方法,所提算法中的每个迭代步骤皆可表示为能获得高效求解的半定规划（SDP）问题。与非稳健方法及非相关波形相比,数值实验验证了本文所提方法的有效性。      

观测通道相关时MIMO雷达的检测性能

针对MIMO雷达的各观测通道相关情况下单目标回波检测问题,通过对回波通道系数的协方差矩阵特征分解,利用特征函数与概率密度函数间的特性,得到通道相关时MIMO雷达检测方法。通过数值仿真表明：观测通道的相关性会降低MIMO空间分集能力,在高信噪比时,MIMO雷达的检测性能随着观测通道相关性的增强而恶化。而在低信噪比时,观测通道的相关性能够改善检测性能。     

非均匀杂波背景下双基地MIMO雷达距离扩展目标的GLRT检测

利用球不变随机矢量(Spherically Invariant Random Vector, SIRV)描述非均匀杂波, 建立了双基地多输入多输出(Multiple-Input Multiple-Qutput, MIMO)雷达距离扩展目标的信号检测模型, 提出了距离扩展目标的两步广义似然比检测(Generalized Likelihood Ratio Test, GLRT)算法.首先, 根据目标散射系数的两种假设模型, 分别推导确定型目标、高斯型目标GLRT检测器的解析表达式, 然后利用固定点迭代算法估计杂波协方差矩阵, 获得自适应GLRT(AD-GLRT和AG-GLRT)检测器.仿真实验表明:AD-GLRT和AG-GLRT检测器的检测性能均优于非均匀杂波背景、高斯杂波背景下点目标的检测性能, 且两者的检测性能相当, 并且虚拟阵元数、目标分布的距离单元数, 以及信杂比越大, 两者的检测性能越好.     

Achievable Performance of Orthogonal STBC Over Spatially Correlated Rician Channels

The effect of spatial correlation on the performance of orthogonal space-time block codes (OSTBCs) over multiple-input-multiple-output (MIMO) Rician fading channels is studied. Asymptotic error-rate formulas for OSTBC with high average signal-to-noise ratios (ASNRs) over arbitrarily correlated Rician MIMO channels are derived in terms of the diversity and coding gains. Our results show that, in correlated fading, the phase vector phi of the channel line-of-sight (LOS) components affects the effective Rice K-factor at the OSTBC receiver output and, hence, may result in a coding gain that is significantly higher than that for independent Rician MIMO channels. Furthermore, when the channel covariance matrix is rank deficient and under some additional mild conditions, the error and outage probabilities of OSTBC achieve those in a nonfading additive-white-Gaussian-noise channel. For both cases of full-rank and rank-deficient channel covariance matrices, analytical expressions of optimal and worst case phase vectors phi, and exact upper and lower bounds of OSTBC performance are derived. These results provide new insights into the achievable performance of OSTBC over correlated Rician MIMO channels and, if incorporated into future multiple antenna systems design, will bring about significant performance enhancement     

Variable-rate multiuser diversity in correlated MIMO channel via virtual channel representation

This paper studies the multiuser diversity with constellation selection based on a virtual representation of realistic Multiple Input Multiple Output （MIMO） correlated channels. To realize multiuser diversity in slow fading channels, random beamforming is adopted. Random beamforming matrix exploiting virtual channel representation is constructed, which can match the channel matrix of the desired user better. Sirnultaneously, adaptive coded modulation is applied to each sub-channel of the selected user to improve the system performance further.     

冲击噪声背景下基于稀疏表示的双基地MIMO雷达多目标定位

该文研究了对称稳定分布(SS)冲击噪声下双基地MIMO雷达的多目标定位问题。针对SS噪声下因二阶矩不存在而造成子空间类算法估计性能下降的不足,提出了矩阵行2范数最大的预处理方法对接收数据进行归一化,使得归一化后的协方差矩阵有界,并以拉直后的协方差矩阵构造稀疏线性模型,提出了基于协方差矩阵-近似零范数(Covariance Matrix Smoothed L0 norm, CMSL0)算法进行目标的发射角和接收角估计。仿真实验表明:通过矩阵行2范数最大化预处理之后,MUSIC(Multiple Signal Classification)和CMSL0算法均能有效地估计出目标的角度,并且CMSL0算法的估计精度及对冲击噪声的稳健性均优于MUSIC算法。此外,与MUSIC算法相比,CMSL0算法不要预先估计目标源的数目,且收发阵元不受半波长间隔的限制。