PRECONDITIONED METHODS FOR SPACE-TIME ADAPTIVE PROCESSING

This paper introduces the preconditioned methods for Space-Time Adaptive Processing(STAP).Using the Block-Toeplitz-Toeplitz-Block(BTTB)structure of the clutter-plus-noise covari-ance matrix,a Block-Circulant-Circulant-Block(BCCB)preconditioner is constructed.Based on thepreconditioner,a Preconditioned Multistage Wiener Filter(PMWF)which can be implemented by thePreconditioned Conjugate Gradient(PCG)method is proposed.Simulation results show that thePMWF has faster convergence rate and lower processing rank compared with the MWF.

SPACE-TIME ADAPTIVE PROCESSING FOR AIRBORNE RADAR:A CONVENIENT IMPLEMENTATION APPROACH

A convenient implementation approach to space-time adaptive processing for airborne radar has been proposed, which is added by some auxiliary array elements in the area of main-lobe clutter on the basis of 2-D Capon approach . It is of practical use for its small computational load. This approach possesses the ideal performance in the area of main-lobe clutter . In addition, the approach which is added by some auxiliary beams in the area of main-lobe clutter has also been discussed.

Range walk and array rotation in space-time adaptive processing:effects and compensations

This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter model,STAP performance is then analyzed from the perspective of covariance matrix tapering（CMT）.For STAP performance degradation due to array rotation,a determinate compensation method is proposed based on the CMT method.Numerical examples are provided to verify the analysis and the proposed compensation method.

Direct data domain approach to space-time adaptive processing

In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristic of the range cell under test. A ravel methodology utilizing the direct data domain approach to space-time adaptive processing （ STAP ） in airbome radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a ＂snapshot-by-snapshot＂ basis to dethrone the adaptive adaptive weights for nulling interferences and estimating signal of interest （SOI）. Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.

STATISTICAL SPACE-TIME ADAPTIVE PROCESSING ALGORITHM

For the slowly changed environment-range-dependent non-homogeneity, a new statistical space-time adaptive processing algorithm is proposed, which uses the statistical methods, such as Bayes or likelihood criterion to estimate the approximative covariance matrix in the non-homogeneous condition. According to the statistical characteristics of the space-time snapshot data, via defining the aggregate snapshot data and corresponding events, the conditional probability of the space-time snapshot data which is the effective training data is given, then the weighting coefficients are obtained for the weighting method. The theory analysis indicates that the statistical methods of the Bayes and likelihood criterion for covariance matrix estimation are more reasonable than other methods that estimate the covariance matrix with the use of training data except the detected outliers. The last simulations attest that the proposed algorithms can estimate the covariance in the non-homogeneous condition exactly and have favorable characteristics.

基于杂波和噪声联合稀疏特性的直接数据域STAP方法

针对机载预警雷达空时自适应处理(space-time adaptive processing,STAP)所面临的异构杂波环境,基于杂波和噪声的联合稀疏特性提出了一种直接数据域(direct data domain,D3)STAP方法。首先通过子孔径平滑技术扩充训练样本集合;然后基于杂波谱二阶表征理论构造STAP功率字典矩阵、导出目标函数,并解得待检测单元信号的空时功率谱;最后根据杂波先验信息重构无孔径损失的杂波加噪声协方差矩阵。数值实验验证了所提方法的协方差矩阵估计精度高于传统的稀疏恢复D3-STAP算法,且在理想情况和存在阵列误差的情况下,所提方法皆具备更好的低速目标检测性能。

A framework of rank-reduced space-time adaptive processing for airborne radar and its applications

A new equivalent formulation of the joint domain space-time optimum processor for airborne phased array radar application is derived. Then a new framework of space-time adaptive processing (STAP) for airborne radar systems which includes most of suboptimum algorithms in the literature is proposed. The performance of two typical rank-reduced time-space joint-domain processors based on Doppler pre-filtering is analyzed in detail based on the proposed framework.

W ideband interference suppression based on space-time filter

Based upon the diagonal loading technique and the structure of the space-time adaptive processors, a novel anti-jamming method of satellite navigation is proposed. According to matrix in- verse theorem, the range of the diagonal loading values for space-time adaptive wideband signal pro- cessing structure is deduced, and the optimum equation of diagonal loading beam forming algorithm of space-time structure is obtained. Then, by the analysis of two-dimensional oriented vector in di- rection of the perturbation interference, the wideband interference covariance matrix obtained in the weights training period is modified. Finally, the optimum weight of multi-linear constrained space- time adaptive beam-forming alogrithm is derived for anti-interference filter processing. The new method effectively widens the null steering beams tion results prove the robustness of the proposed when discrepancy happens. The computer simula- method.

基于稀疏贝叶斯学习的稳健STAP算法

为了提高阵列幅相误差和格点失配情况下稀疏恢复空时自适应处理(sparse recovery space-time adaptive processing,SR-STAP)算法的性能,提出一种基于稀疏贝叶斯学习的稳健SR-STAP算法。首先,利用空时导向矢量的Kronecker结构构建SR-STAP误差信号模型;然后,利用贝叶斯推断和最大期望算法迭代求取角度多普勒像和误差参数;最后,利用求解参数估计精确的杂波加噪声协方差矩阵并计算权矢量。仿真实验表明,所提算法能够显著提高稀疏信号模型失配时的目标检测性能。

Adaptive beamforming and phase bias compensation for GNSS receiver

Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by the antenna array. However,the adaptive beamforming will change the array pattern in realtime, which has the potential to introduce phase center biases into the antenna array. For precise applications, these phase biases must be mitigated or compensated because they will bring errors in code phase and carrier phase measurements. A novel adaptive beamforming algorithm is proposed firstly, then the phase bias induced by the proposed algorithm is estimated, and finally a compensation strategy is addressed. Simulations demonstrate that the proposed beamforming algorithm suppresses effectively the strong interference and improves significantly the capturing performance of GNSS signals. Simultaneously, the bias compensation method avoids the loss of the carrier phase lock and reduces the phase measurement errors for GNSS receivers.

雷达海上预警的快速SR-STAP海杂波抑制方法

针对稀疏重构空时自适应处理技术在低样本量时的非均匀海杂波抑制中存在大维度杂波测量矩阵和复杂迭代机制中的运算负担较大的问题,提出了一种快速SR-STAP海杂波抑制方法.通过回波空时解耦的方式降低了测量矩阵维度,减小了高维矩阵的运算负担;基于快速傅里叶变换获取频谱分布支撑集并构造先验矩阵因子,改进稀疏优化问题并通过调整因子权值加快收敛,以实现杂波频谱快速恢复.仿真结果验证了所提方法的低复杂度优势与可靠的海上目标检测性能.

一种抑制严重非均匀杂波的机载MIMO-STAP方法

在机载MIMO雷达体制下,针对严重非均匀环境(包括斜视阵和前视阵近程段),提出了一种新的基于时域平滑的两级级联降维STAP方法,先后对杂波和孤立干扰进行抑制.第一级对少量独立同分布(IID)辅助样本进行平滑,用得到的所有样本估计杂波特性并用先时后空自适应级联处理器(称为mDT-SAP)中的3DT-SAP(简称3DT)方法进行抑制,第二级用待检测距离单元数据进行平滑估计孤立干扰特性并用3DT方法进行抑制.该方法克服了直接数据域(DDD)方法空时孔径损失大,误差鲁棒性差及没有充分利用统计信息的缺点,具有良好的性能.计算机仿真实验验证了其有效性和优越性.

机载多载频频控阵非均匀距离模糊杂波抑制方法

机载雷达下视工作面临严重的地海杂波,雷达平台运动造成杂波多普勒频率严重扩散,将微弱目标完全淹没。空时自适应处理(space time adaptive processing,STAP)技术通过联合多天线脉冲的接收信号,能够有效地抑制杂波,实现运动目标检测。对于非正侧视阵列高速平台雷达,杂波距离依赖和距离模糊严重制约着目标检测性能。基于多载频频控阵,通过发射一组载频不同的正交信号,在杂波回波中,获得新的发射维自由度,并根据不同模糊在发射维的差异分离各模糊区域。此外,通过进一步对分离后的近程进行杂波补偿,利用降维STAP实现杂波抑制。仿真结果验证了所提方法的有效性。

基于子阵波束设计的空时二维杂波抑制方法

机载雷达接收端采用子阵处理时面临栅瓣杂波导致的复杂空时耦合分布,使主瓣波束方向存在多个由栅瓣杂波导致的检测性能凹口,目标检测性能恶化严重。针对此问题,该文首先分析了子阵处理中栅瓣杂波空时谱分布特性,并在此基础上提出了基于接收子阵波束设计的空时二维杂波抑制方法。该方法采用重叠子阵构型方案,通过子阵方向图设计形成在子阵间栅瓣区域处的宽凹口,实现对子阵间栅瓣区域杂波的预滤波。进一步构建子阵级空时处理器,由于栅瓣杂波已经在子阵内完成预滤波,避免了栅瓣杂波在空时二维平面上的耦合扩散,从而提高了杂波抑制和动目标检测性能。仿真结果表明,所提方法显著改善了栅瓣杂波区的输出信杂噪比损失性能。

有源干扰条件下机载MIMO雷达STAP协方差矩阵秩的分析

该文分析了正侧阵机载MIMO雷达杂波加有源干扰协方差矩阵的结构,得到杂波加有源干扰协方差矩阵秩的上界为杂波的秩与有源干扰的秩之和减去有源干扰个数。并由此得到MIMO雷达杂波加有源干扰协方差矩阵非满秩而SIMO雷达杂波加有源干扰协方差矩阵满秩时有源干扰个数的范围。当有源干扰的数目在此范围时,SIMO雷达的理论性能严重下降,而MIMO雷达在理论上仍然有足够的自由度来抑制杂波和有源干扰,从而保证有较好的性能。通过仿真实验验证了上述结论。

STAP技术在有源干扰环境下的运用方法

为了在复杂的有源干扰环境下改善空时二维自适应处理(Space-time Adaptive Process-ing,STAP)技术的处理性能,提出了一种基于局部空域自适应阵列处理的改进型自适应波束形成方法。这是一种空间抗干扰与STAP技术滤除杂波级联的方法。采用MUSIC技术对有源干扰的波达方向进行估计,然后分别在期望方向和干扰方向形成接收多波束,再在波束域进行自适应处理以抑制有源干扰,最后在空间反干扰滤波后运用STAP技术进行杂波抑制。仿真结果表明,该方法能有效估计出干扰源的方位,使STAP技术在有干扰的环境下也能保持较好的杂波抑制性能,同时在波束域进行自适应滤波,大大降低了抑制干扰所需的运算量,理论分析和仿真结果表明了该算法的有效性。

非均匀杂波环境3D-STAP方法研究

传统二维空时自适应处理(2D-STAP)利用与待检测单元相邻单元的独立同分布杂波样本估计待检测单元的杂波特性.而许多实际应用情况中(如前向阵),杂波谱分布随距离(俯仰角)变化而变化,杂波统计特性与距离(俯仰角)相关,呈现非均匀性,2D-STAP方法性能严重下降.本文首先对非正侧面阵配置所产生的与俯仰角相关的杂波分布规律进行了分析,然后对3D-STAP方法能有效解决与俯仰角相关的杂波非均匀问题的本质机理进行了研究,最后通过仿真实验从杂波抑制性能和运算量两个方面,论证了非均匀杂波环境下3D-STAP方法的综合性能.

知识辅助的机载MIMO雷达STAP非均匀样本检测方法

针对样本协方差矩阵受干扰目标污染时机载多输入多输出(multiple-input multiple-output,MIMO)雷达空时自适应处理(space-time adaptive processing,STAP)目标检测性能下降的不足,提出一种知识辅助(knowledge-aided,KA)的广义内积非均匀样本检测方法。首先利用扁长椭球波函数估计的杂波子空间知识,离线构造杂波协方差矩阵,然后与广义内积非均匀检测器(generalized inner product non-homogeneity detector,GIP NHD)结合,实现对训练样本的有效选择,使目标检测不受训练样本中干扰目标的影响。仿真结果表明,相对于常规GIP方法,KA-GIP方法能够对存在干扰目标的样本进行更加有效地剔除,并且机载MIMO雷达STAP的目标检测性能得到显著提升,因此更有利于实际工程应用。

阵元失效情况下的STAP性能研究

本文针对矩形面阵的情况,讨论了面阵上不同阵元失效情况对阵列方向图、杂波特性及STAP性能的影响.可以发现,在加权的情况下失效阵元距阵面中心越接近,阵列方向图主瓣下降,副瓣升高越严重,子阵中失效阵元增多时,杂波自由度会随之增加,但当整个子阵失效时,杂波自由度反而会降低到接近原先无阵元失效的情况.文末讨论了阵元失效对目标信号相参积累的影响,对两种STAP算法在不同阵元失效情况下的性能进行了仿真分析,可以看出,阵元失效除了可能导致杂波自由度增加,还可能致使空域自适应方向图畸变,从而对自由度较匮乏的算法影响较大,最后针对空域自适应方向图畸变提出了一种空域深加权的改善方法,有一定的改善效果.

基于频率非均匀采样杂波谱配准的天基雷达STAP方法

地球自转和非正侧面阵配置会使得天基雷达杂波谱随距离发生变化,呈现出非平稳性,从而严重影响统计STAP方法的杂波抑制性能。为了补偿这种非平稳性,该文提出了一种基于频率非均匀采样的杂波谱配准方法,建立了非均匀谱配准法的数学模型,给出了频率非均匀采样点的选取方法以及谱配准后杂波协方差矩阵的估计方法等。通过对天基雷达的仿真实验表明,上述谱配准法可有效消除杂波非平稳性,获得较好的处理性能。