对空时二维自适应处理雷达的投散射宽时限扫频式干扰技术研究

针对传统干扰方法因干扰信号维度单一而难以在空时二维联合域对空时自适应处理器（Space-Time Adaptive Processing,STAP）产生有效干扰这一问题,提出了一种能覆盖整个空时二维平面的投散射宽时限扫频式干扰方法.该方法是向特定区域投射具有多普勒带宽的扫频信号,利用散射回波干扰STAP雷达.地形散射使干扰信号具有空时耦合特性,干扰信号空域连续,STAP处理器无法从空域识别抑制;宽时限扫频方式导致脉冲间多普勒频率存在差异,使雷达无法提取干扰信号多普勒频率,能占用处理器大量自由度.仿真结果表明,该方法产生的干扰功率谱能覆盖整个空时平面,使处理器自由度严重损失,导致STAP处理器性能下降,验证了该方法的有效性.     

对STAP处理器的投散射式伪杂波干扰技术

具有空时自适应处理技术（STAP）的机载雷达从空时二维联合域处理信号,而传统干扰方法因信号维度单一性很难产生有效干扰效果。文中针对STAP处理器抗干扰特性,提出一种具有空时二维特性的投散射式伪杂波干扰新技术,根据多普勒频率对方位的依从关系,向地面投射干扰信号,利用地面散射特性产生与地杂波特性相似的伪杂波干扰信号。分析了该干扰信号的空时矢量模型,研究了干扰信号二维功率谱的轨迹可控性问题。该干扰信号在空时二维空间上呈现不与杂波轨迹重合的刀背式分布,多普勒轨迹可控,能控制干扰信号的二维功率谱始终覆盖在被保护目标上。仿真实验结果显示：处理器改善因子降低,杂波谱畸变,证明了该干扰方法的有效性。     

基于自适应局域变换的离散干扰抑制算法

在非均匀杂波环境中,针对待检测距离单元的离散干扰严重影响统计空时自适应处理(STAP)杂波抑制性能的问题,提出了基于自适应局域变换的离散干扰抑制算法。该方法利用自适应局域变换矩阵具有局域变换和自适应滤波的双重特性,在较低计算复杂度条件下有效消除离散干扰对统计STAP方法的影响。仿真数据和MCARM实测数据分析表明,该方法能有效抑制待检测距离单元中的离散干扰和均匀杂波,显著改善STAP在非均匀杂波中的性能。     

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。     

基于改进快速子空间迭代跟踪的部分自适应STAP算法

针对部分空时自适应(STAP)处理的特征值分解(EVD)影响杂波抑制的实时处理性能,提出了基于改进快速子空间迭代跟踪(PAST)的部分自适应STAP算法.该方法首先在PAST处理的基础上,对正交PAST方法进行改进,得到改进后的PAST(MPAST)方法;然后将MPAST方法应用于计算部分自适应STAP算法的特征子空间,从而有效提高STAP算法的收敛速度和降低自适应权矢量计算的运算量.仿真数据和MCARM实测数据分析表明,该方法能有效抑制待检测距离单元的杂波,并能在低计算复杂度下显著提高STAP处理的收敛速度.     

一种改进现有机载雷达探测性能的多普勒处理新技术北大核心CSCD

文中提出了一种自适应多普勒补偿算法,用来缓解近距离单元中退化的空时自适应处理(STAP)性能,从而提高机载雷达探测性能。自适应特性可以避免飞机对雷达参数的实时性的需要。同时,提出了一种有效的STAP算法用来检测和估计目标参数,输入STAP权值数据以获得三维数组,并且利用三维数组的距离投影来检测和估计目标的距离,利用角度-多普勒投影来估计目标的空间和时间参数。在本研究中,基于一个机载相控阵雷达模型的合成数据生成估计协方差矩阵。所提出的STAP算法非常接近机载雷达平台的实时实现方案。通过对合成数据的目标参数估计和STAP度量,验证了自适应多普勒补偿算法的有效性。     

通道失配对空时自适应处理性能的影响分析

通道失配严重影响着空时自适应处理(STAP)的性能,定量地分析通道失配对STAP性能的影响对于STAP算法的工程应用具有重要意义。文中根据通道失配是否依赖于到达角、信号带宽是否为窄带等方面,从理论上推导了存在通道失配时的杂波协方差矩阵,并仿真分析了通道失配对STAP性能的影响,为STAP算法理论建模、STAP系统设计提供理论依据。     

基于时变空时自回归模型的STAP算法

针对空时自适应处理(STAP)中时域非平稳杂波过程造成的空时自回归(STAR)算法失效问题,文中将时变自回归(TVAR)模型引入STAP处理中,提出了一种新的时变空时自回归(TV-STAR)算法。TV-STAR算法能够有效弥补平稳自回归(AR)模型与实际非平稳杂波环境失配造成的STAR算法性能损耗,在非平稳杂波环境中具有良好的检测性能。同时,TV-STAR算法由于引入了低阶数的TVAR模型,其收敛速度显著优于降秩STAP算法。文中分别通过仿真实验以及机载雷达实测数据的处理对算法有效性进行了验证。     

机载雷达空时自适应处理的实时实现

多通道机载雷达空时自适应 (STAP) 算法运算量巨大,不易实时实现。本文详细分析了部分自适应STAP的3个计算步骤,指出了其内在并行性。针对多片DSP系统提出了一种部分自适应STAP并行算法,给出了该算法的任务划分、执行模型、任务映射策略以及性能评价函数。该算法在不同的计算阶段之间进行数据重映射。通过数据试验证明这种基于多片DSP系统的STAP并行算法具有较高的实时性能。     

一种波束域的高速空中动目标检测及参数估计方法

Keystone变换所需的插值运算存在计算量大的问题,尤其是用于空时自适应处理(Space-Time Adaptive Processing,STAP)时需要对每个阵元接收的数据分别进行Keystone变换,给工程实现带来了困难.为了解决这一问题,提出了一种在波束域进行Keystone变换校正目标距离走动的新方法,该方法将传统的对每个阵元数据的Keystone变换转换为在波束域进行Keystone变换,从而将N个阵元对应的N次Keystone变换转换为只在主波束内进行一次Keystone变换,这样做使算法的主要运算量降低为原来的1/N.然后将压缩感知(Compressed Sensing,CS)理论用于空时自适应处理的目标参数估计,取得了良好的估计性能.最后通过仿真实验验证了本文方法的有效性.     

Improved Multistage Wiener Filters in Nonhomogeneous Clutter Environments

A new method combining space-time preprocessing with multistage Wiener filters（STPMWF）is proposed to improve the performance of space-time adaptive processing（STAP）in nonhomogeneous clutter scenario.The new scheme only requires the data from the primary range bin,thus it can suppress discrete interferers efficiently,without calculating the inverse of covariance matrix.Comparing to the original MWF approach,the proposed scheme can be regarded as practical solutions for robust and effective STAP of nonhomogeneous radar data.The theoretical analysis shows that our STPMWF is simple in implementation and fast in convergence.The numeric results by using simulated data exhibit a good agreement with the proposed theory.     

基于降秩空时联合处理的GPS多径干扰抑制

GPS测量,尤其是差分GPS测量,多径信号是主要的误差来源,会引起定位精确度的恶化。因此基于GPS多径影响分析,提出采用空时处理抗多径的方法,但是由于大的计算量,必须做降秩处理,并给出了仿真的结果。     

The statistical performance of eigenspace-based adaptive arraybeamformers

We analyze the statistical performance of several eigenspace-based adaptive array beamformers, including conventional direct-form beamformers and generalized sidelobe canceler (GSC). It is shown that the convergence rate of eigenspace-based adaptive array beamforming depends on the number of array elements, the input signal-to-noise ratio (SNR), and the number of interferers when the desired signal is present during the weight adaptation. In contrast, the misadjustment of the array output power is a function of the number of interferers and is independent of the number of array elements when the desired signal is absent. Several simulation examples are also provided to confirm the theoretical results     

GPS接收机空时二维抗干扰技术研究

随着干扰技术的发展,GPS抗干扰性能差的缺点日益突出,对于能有效用于工程应用的抗干扰方法的研究显得尤为重要。空时二维抗干扰方法是GPS接收机抗干扰技术上的重大突破。在已给空时二维自适应滤波的模型及原理的基础上,通过对自适应约束准则的分析及选择,进而对不同情况下的空时自适应滤波权值的频率-角度响应进行了数字仿真和分析,得出了空时自适应滤波抗干扰的一些有益结论及合理解释。     

一种基于核的GPS空时自适应抗干扰方法

针对GPS接收系统的空时自适应抗干扰技术,分析目前基于FROST阵列处理的最小均方算法LMS(FLMS)算法,提出一种基于核方法的FLMS算法(Kernel FLMS,KFLMS).通过对空时自适应STAP和算法的建模,研究了KFLMS算法的性能.系统仿真表明,KFLMS算法不仅能抑制大于阵元个数的多个宽、窄带干扰,而且使接收机整体抗干扰能力达到70dB左右,比FLMS算法效果更优.     

Dynamic algorithm transforms for low-power reconfigurable adaptiveequalizers

In this paper, we present low-power reconfigurable adaptive equalizers derived via dynamic algorithm transforms (DATs). The principle behind DAT is that conventional signal processing systems are designed for the worst case and are not energy-optimum on average. Therefore, significant energy savings can be achieved by optimally reconfiguring the hardware in these situations. Practical reconfiguration strategies for adaptive filters are presented. These strategies are derived as a solution to an optimization problem. The optimization problem has energy as the objective function and a constraint on the algorithm performance (specifically the SNR). The DAT-based adaptive filter is employed as an equalizer for a 51.84 Mb/s very high speed digital subscriber loop (VDSL) over 24-pair BKMA cable. The channel nonstationarities are due to variations in cable length and number of far end crosstalk (FEXT) interferers. For this application, the traditional design is based on 1 kft cable length and 11 FEXT interferers. It was found that up to 81% energy savings can be achieved when cable length varies from 1-0.1 kft and the number of FEXT interferers varies from 11 to 4. On the average, 53% energy savings are achieved as compared with the conventional worst-case design     

Adaptive multiuser detection and beamforming for interferencesuppression in CDMA mobile radio systems

This paper considers the problem of interference suppression in direct-sequence code-division multiple-access (DS-CDMA) systems over fading channels. An adaptive array receiver is presented which integrates multiuser detection, beamforming, and RAKE reception to mitigate cochannel interference and fading. The adaptive multiuser detector is formulated using a blind constrained energy minimization criterion and adaptation is carried out using a novel algorithm based on set-membership parameter estimation theory. The proposed detector overcomes the shortcomings of conventional LMS- and RLS-type algorithms, namely, that of slow convergence and large computational load, respectively. This is especially the case when strong interferers are present or when the number of adaptive weights is relatively large. DS-CDMA systems can have a relatively large number of spatially distributed interferers. Thus beamforming is based on direction-of-arrival (DOA) estimates provided by an approximate maximum-likelihood estimator (DOA-MLE). Unlike previous approaches, the DOA-MLE exploits the structure of the DS-CDMA signaling scheme resulting in robust performance and simple implementation in the presence of angle spreading. The overall method is suitable for real-time implementation and can substantially improve the interference suppression capabilities of a CDMA system     

知识辅助的APR非均匀样本检测方法

针对空时自适应处理(STAP)中样本协方差矩阵受强干扰目标污染时检测性能下降的问题,提出了一种知识辅助的自适应功率剩余(KA-APR)非均匀样本检测方法。该方法将杂波先验知识与自适应功率剩余非均匀检测器(APR NHD)相结合,对训练样本进行有效选择。仿真结果表明,相对于传统的APR 方法,KA-APR 方法能更有效剔除存在强干扰目标的样本,提高训练样本被强干扰目标污染时空时自适应处理的检测性能。     

Reduced‐rank space–time adaptive interference suppression for navigation systems based on QR decomposition and approximations of basis functions

This paper presents a novel reduced‐rank space–time adaptive processing (STAP) algorithm for interference suppression in global positioning system (GPS) receivers with low computational complexity for protection against the multipath and jamming interferences. The proposed STAP algorithm is based on the least‐squares (LS) criterion to jointly optimize a projection matrix, which is used for dimensionality reduction, and the reduced‐rank filter. The main novelties are the design of the projection matrix based on approximations of basis functions, the pattern matching between the projection matrix and the received data, and the derivation of a QR decomposition‐based reduced‐rank recursive LS algorithm for practical implementations. The proposed scheme works on an instantaneous basis, i.e. at each time instant, the most suitable pattern and the rank of the projection matrix are selected to reduce the dimensionality of the received data aiming at minimizing the squared error, while using an improved search algorithm to save the effort in finding the best projection matrix. Simulation results in a GPS system show that compared to existing reduced‐rank and full‐rank algorithms, the proposed algorithm has a much lower computational complexity, and remarkably better performance for interference suppression. Copyright © 2011 John Wiley & Sons, Ltd.     

Joint space-time interpolation for distorted linear and bistatic array geometries

This paper presents a new joint space-time interpolation technique (STINT) to improve the small sample support performance of space-time adaptive processing (STAP) with distorted linear monostatic arrays and linear bistatic array configurations. Brennan's rule for the space-time clutter covariance matrix rank is extended to monostatic linear arrays with arbitrary intersensor spacing, distorted linear arrays and bistatic geometries. It is shown that both distortion in the array geometry and bistatic operation increase the clutter rank and cause the space-time clutter covariance matrix to become range dependent. This results in lower output signal-to-interference-plus-noise ratio (SINR) for the same number of adaptive degrees of freedom and reduced available sample support. This motivates the development of the STINT technique aimed at compensating for the clutter rank inflation, while also making the clutter statistics appear more stationary across range. More specifically, a linear transformation is designed that maps the received clutter across space and time to that which would be received by a "virtual" monostatic side-looking ULA. By mapping the data to form a reduced rank clutter covariance matrix, fewer snapshots are needed for a statistically stable matrix inversion as required in STAP, thereby improving the short observation time performance. Simulation results for a typical airborne radar scenario indicate up to 10-dB SINR improvement can be obtained using STINT with limited sample support.