A Fast Beamforming Algorithm for Large Arrays

This beamforming algorithm is written specifically for array radars in which the number of array elements K is very large compared with the number of jammers L the radar is designed to suppress. It uses a set of M noise vectors to construct a basis for the jammer component of the antenna output vectors. The component of the quiescent weight vector orthogonal to each basis vector is calculated, renormalized to unit length, and identified as the adapted weight vector. This algorithm is effective in the suppression of many types of jammers. The number of noise samples M required in the construction of the adapted weight vector is approximately equal to L. In the special case of L narrowband noise jammers, for example, a choice of M = L usually reduces the receiver output jammer power to a few dBs above the white noise background. It is permissible to have M相似文献   

基于EKF的天线罩误差斜率多模型估计方法

 提出一种新的滤波器结构,利用基于扩展卡尔曼滤波(EKF)的多模型(MM)算法,对天线罩误差斜率进行估计,降低天线罩误差对雷达自寻的导弹的影响,提高系统性能。在三维坐标下,创建包含导弹运动方程、目标运动方程、弹目相对运动方程的滤波模型。采用EKF算法,对包含天线罩误差的非线性观测方程进行线性化处理;依照多模滤波的思想,对天线罩误差进行离散建模,构建伪观测方程,更新模型概率,得到天线罩误差斜率的估计值;将斜率估计结果代入EKF,得到滤除天线罩误差影响的系统状态量估计结果并形成制导指令。仿真结果表明,所提方法可以有效地估计天线罩斜率,提高系统制导精度。     

一种利用功率反演和线性约束最小方差算法的自适应天线

介绍了一种新的基于功率反演和线性约束最小方差的算法,以高度抑制GPS接收机的干扰信号。这种结构通过提调整天线阵列的权值,实时地接收并改变来自各方向的GPS信号,同时对不同方向的干扰信号有高的抑制比。对固定和移动的干扰都做了仿真,仿真表明这种结构有很深的零点,对固定干扰信号的抑制比可达到115dB,对移动干扰信号的抑制比可达到94dB。     

Subspace array processing for the suppression of FM jamming in GPS receivers

The mitigation of FM interference in GPS receivers is considered. In difference to commonly assumed wideband and narrowband interferers, the FM interferers are wideband, but instantaneously narrowband, and as such, have clear time-frequency (TF) signatures that are distinct from the GPS coarse acquisition (C/A) spread spectrum code. In the proposed technique, the estimate of the FM interference instantaneous frequency (IF) and the interference spatial signature are used to construct the spatiotemporal interference subspace. The IF estimates can be provided using existing effective linear or bilinear TF methods. The undesired signal arrival is suppressed by projecting the input data on the interference orthogonal subspace. With a multisensor receiver, the distinctions in both the spatial and TF signatures of signal arrivals allow effective interference suppressions. The deterministic nature of the signal model is considered and the known underlying structure of the GPS C/A code is utilized. We derive the receiver signal-to-interference-plus-noise ratio (SINR) under exact and perturbed IF values. The effect of IF estimation errors on both pseudorange measurements and navigation data recovery is analyzed. Simulation results comparing the receiver performances under IF errors in single and multiantenna GPS receivers are provided.     

New approach for suppression of FM jamming in GPS receivers

A new approach is proposed for the suppression of FM jammers in C/A code GPS receivers. This approach is based on the cascading of the augmented-state approximate conditional mean (ASACM) filter and the discrete wavelet transform (DWT) filter. An ASACM filter for single interference suppression in spread-spectrum systems has been reported in the recent literature. However, the formulation of the ASACM filter and its performance analysis is lacking in the case of suppression of multiple FM interferences. The ASACM filter is formulated here for the suppression of multiple FM jammers. Further, a DWT filter using biorthogonal wavelet is suggested for the suppression of FM jammers. Finally, these two filters are cascaded to get an optimum performance for higher jammer to signal ratio, which is of importance in the GPS, for the case of suppression of multiple FM jammers. The performance of the proposed filters is analyzed through simulation examples for the suppression of single and multiple FM jammers in GPS receivers     

多干扰机InSAR欺骗干扰方法

单航过的干涉合成孔径雷达（InSAR）有很强的抗干扰能力,单部干扰机所发射干扰信号的干涉相位在不同快时间是完全相同的,不同慢时间也近似相等,不能产生具有高程信息的干扰图像。基于此,提出了一种利用双（多）干扰机产生InSAR三维图像欺骗干扰的方法,分析了InSAR的成像机理,给出了假目标模板设置方法,讨论了聚焦后复图像和干涉相位要求的干扰信号调制参数以及干涉相位的估计方法。产生的干扰信号在雷达接收机中可独立实现SAR二维像干扰,经干涉后能生成虚假高程信息,理论分析和仿真结果表明,该方法能实现对SAR二维成像和InSAR三维成像的有效干扰。     

一种基于数据跳变检测的高动态环境GPS信号参数估计方法

鉴于高动态环境中 Ｇ Ｐ Ｓ信号参数估计和调制数据跳变检测所遇到的问题,采用扩展卡尔曼滤波方法（ Ｅ Ｋ Ｆ）对信号参数进行了估计,分析了通过载波辅助技术实现伪码延时估计的原理,重点研究了一种简单的数据跳变检测和估计参数修正方法。模拟结果表明这种方法在信号参数估计精度和动态跟踪性能等方面都能够满足高动态环境的要求。     

基于误码率准则的窄带干扰抑制算法性能分析

采用有效的窄带干扰抑制技术,可极大地改善扩频通信系统的性能.首先详细介绍了频域干扰抑制算法的基本思想,给出了算法实现的模块框图;其次具体分析了算法实现的关键技术：重叠加窗,背景噪声估计,干扰门限确定及干扰消除策略;最后以误码率作为干扰消除算法性能的评判标准,仿真分析了频域窄带干扰抑制技术中干扰强度、干扰频带宽度、干扰频率位置、干扰消除门限、陷幅值、加窗重叠度等因素对系统误码率的影响,为在不同条件下算法最佳参数的选取提供了依据.仿真结果表明：当干扰消除门限值取4aF,陷幅值取2σF～6σF,加窗重叠度为50％时,该算法可获得最佳抗干扰性能.     

GPS信号FFT自适应抗干扰技术的FPGA工程实现

针对自适应抗干扰技术展开研究,提出了易于FPGA实现的FFT自适应窄带抗干扰技术.这种方法减小了数字信号处理部分的计算量,提高了系统处理的实时性,降低了系统的复杂程度.实验表明在有宽带干扰存在的情况下,使用所提出的方法可以自适应检测并剔除窄带干扰.与GPS接收机的对接测试表明,该技术能大大提高接收机的抗干扰能力.     

两种自适应方向图峰值副瓣控制方法比较

自适应阵列（或称自适应波束形成）目前已广泛应用到雷达、声纳和通信领域中用来抑制各种干扰（有意的干扰，杂波干扰和多用户干扰等）。在雷达应用中，为了减轻脉冲欺骗式干扰或旁瓣目标并利用单脉冲雷达来准确测量目标波达方向．要求自适应方向图具有低副瓣和稳定的主瓣形状。在实际应用中，各种失配误差将降低自适应阵列的性能．这些误差包括由于目标的波达方向不精确引起的信号指向误差，由通道失配和位置扰动引起的阵列校准误差和由小样本教引起的协方差矩阵估计误差。在此情况下，自适应波束形成的性能大大下降（干扰抑制性能变差。主瓣失真和高的副瓣）。已提出了一种基于二次约束的集成峰值副瓣控制（integrated peak sidelobe control，简称IPSC）方法。该方法可以精确地控制峰值副瓣电平并产生具有稳定的主瓣形状的自适应方向图。研究IPSC中目标信号的影响和信号消除方案以进一步提高IPSC的性能。并将IPSC方法和最新提出的基于二阶锥规划（second-order cone programming，简称SOCP）的分布式峰值副瓣控制（distfibuted peak sidelobe control，简称为DPSC）新方法在性能上进行了比较。仿真结果表明。在干扰抑制性能和方向图控制质量方面IPSC比DPSC性能优越。此外IPSC比DPSC计算高效。     

An improved LMS adaptive algorithm for narrowband interferencesuppression in direct sequence spread spectrum

In 1990 Vijayan and Poor proposed nonlinear predictive methods for suppressing narrowband interference in spread spectrum (SS) systems with a significant increase in signal-to-noise ratio (SNR) improvement. The main drawback of their adaptive nonlinear filter is its slow convergence rate. A new adaptive least mean squares (LMS) algorithm to increase the slow convergence of their nonlinear adaptive filter is described. Computer simulation results are presented to support the advantages of the new filter     

Algorithmic, architectural, and beam pattern issues of sidelobecancellation

Various important issues concerning the sidelobe cancellation (SLC) approach for suppressing sidelobe interference signals in radar are investigated. The concepts are presented in a tutorial manner and include: formulating the calculation of the complex weights for the auxiliary channels as an exact least-squares (LS) problem; computing the LS weights using orthogonal transformation for improved numerical accuracy; and mapping orthogonalization-based algorithms onto systolic arrays. The problem of excessive degrees of freedom (EDOF) associated with utilizing too many auxiliary elements when a relatively small number of jammers are present, is also considered. A divisionless orthogonalization-based algorithm is presented for the computation of the auxiliary weights. Many of these issues have previously been either implicitly stated or only individually addressed in various sources by a number of researchers. Besides showing simulation results and the divisionless procedure for obtaining the final auxiliary weights, a major consideration was to present all of the aforementioned concepts in a coherent and unified framework     

A sampling-based approach to wideband interference cancellation

Classical adaptive array schemes which use only complex spatial weights are inherently narrowband and consequently perform poorly when attempting to suppress wideband interference. The common solution to this problem is the use of tapped delay line filters in each spatial channel to facilitate space-time adaptive processing (STAP). The higher performance provided by the STAP architecture comes at the cost of a considerable increase in complexity. This paper presents a simpler technique based on programmable time adjustable sampling (TAS) that provides a limited number of wideband degrees of freedom. Two TAS methods are introduced: TAS-sidelobe canceler (TAS-SLC) is based on the sidelobe canceler, while TAS-minimum variance beamformer (TAS-MVB) is derived from the minimum variance beamformer. TAS is implemented by adjusting the sampling instant at selected array channels. TAS-SLC consists of controlling the sampling in the main channel of the sidelobe canceler With TAS-MVB array complex weights are substituted with TAS time delays. The performance of TAS methods with wideband interference is compared to the conventional sidelobe canceler and minimum variance beamformers. It is shown that TAS-SLC provides better performance than the sidelobe canceler, while TAS-MVB outperforms the minimum variance beamformer     

Detection of interference/jamming and spoofing in a DGPS-aidedinertial system

Previous research at the Air Force Institute of Technology (AFIT) has resulted in the design of a differential Global Positioning System (DGPS) aided INS-based (inertial navigation system) precision landing system (PLS) capable of meeting the FAA precision requirements for instrument landings. The susceptibility of DGPS transmissions to both intentional and nonintentional interference/jamming and spoofing must be addressed before DGPS may be safely used as a major component of such a critical navigational device. This research applies multiple model adaptive estimation (MMAE) techniques to the problem of detecting and identifying interference/jamming and spoofing in the DGPS signal. Such an MMAE is composed of a bank of parallel filters, each hypothesizing a different failure status, along with an evaluation of the current probability of each hypothesis being correct, to form a probability-weighted average state estimate as an output. For interference/jamming degradation represented as increased measurement noise variance, simulation results show that, because of the good failure detection and isolation (FDI) performance using MMAE, the blended navigation performance is essentially that of a single extended Kalman filter (EKF) artificially informed of the actual interference noise variance. However, a standard MMAE is completely unable to detect spoofing failures (modeled as a bias or ramp offset signal directly added to the measurement). This work describes a moving-bank pseudoresidual MMAE (PRMMAE) to detect and identify such spoofing. Using the PRMMAE algorithm, spoofing is very effectively detected and isolated; the resulting navigation performance is equivalent to that of an EKF operating in an environment without spoofing     

一种盲多波束形成GNSS天线阵抗干扰算法

天线阵抗干扰是现代卫星导航接收机抗干扰的重要手段。传统的天线阵波束形成类算法能够在抑制干扰的同时提升抗干扰后输出信噪比,但是在信号捕获阶段,由于缺少先验信息的支持,该类算法无法在信号方向形成增益。因此,提出了一种盲多波束形成的天线阵抗干扰算法,通过形成多个波束覆盖天线阵上半球面,可在无先验信息的条件下对卫星信号形成增益,从而提升信号捕获阶段信噪比,使得接收机在干扰环境中具备更强的信号捕获能力。仿真结果表明:与传统的天线阵抗干扰算法相比,提出的算法能够在有效抑制干扰的同时显著提升接收机信号捕获成功率。     

Multicomponent receiver architectures for GPS interference suppression

The global positioning system (GPS) is a one-way satellite-based navigation system employing spread-spectrum techniques that is widely used for commercial and military applications. Although the very low signal-to-noise ratio (SNR) is handled by the large spreading gain, GPS is susceptible to high-power interference signals and various types of jammers. We propose multicomponent receiver architectures for GPS interference suppression. A conventional antenna system is first considered which utilizes a minimum-variance distortionless-response (MVDR) beam former and assumes that the GPS signal angle of arrival (AOA) and the antenna model are known at the receiver. However, this receiver is sensitive to AOA estimation errors and can have a high computational complexity. This sensitivity problem is eliminated by a multicomponent system based on a multistage matched filter (MF). Since this MF receiver also has a high computational complexity because the jammer AOAs must be estimated, we introduce a blind interference canceler based on the constant modulus (CM) array that is insensitive to AOA estimation errors and has a low computational complexity. Computer simulations are provided to illustrate the performance of the various systems for interference suppression in example signal scenarios.     

Householder Multistage Wiener Filter for Space-Time Navigation Receivers

Space-time (ST) processing in navigation receivers is attractive technology because it provides a sufficient number of degrees of freedom for cancelling a large number of wideband and narrowband jammers simultaneously. Low complexity reduced-rank receiver structures are particularly appealing because the number of filter coefficients can be much larger than the rank of the ST signal model. This paper proposes a new Householder-based multistage Wiener filter (HMSWF) structure for estimating the coefficients of an ST navigation receiver. Both floating point and fixed point arithmetic implementations are considered. The computational complexity of the HMSWF compares favorably with the other MSWF methods reported in literature. Furthermore, the use of Householder transformations at each stage ensures unitary blocking and numerically robust behavior even in finite-precision implementations. Simulations studies verify that the proposed ST navigation receiver based on the HMSWF outperforms other MSWF methods in the antijamming (A,J) task.     

A fusion and learning algorithm for landing aircraft tracking:compensating for exhaust plume disturbance

An algorithm is presented for tracking a landing aircraft using fusion of two different passive sensors, a laser range finder (LRF) and a forward-looking infrared (FLIR) camera. The main feature of this algorithm is its ability to identify and compensate for an exhaust plume disturbance. The algorithm is based on the extended Kalman filter (EKF) and the filtering confidence function (FCF) which introduces a learning approach to the tracking problem. The results of a simulation using the learning tracking algorithm and the EKF alone are presented and compared     

基于约束最小冗余线阵与干扰对消的测向方法

针对有源干扰背景下信号源和干扰源的个数超过线阵的自由度而产生线阵饱和现象,提出一种将约束最小冗余线阵与干扰对消技术相结合的测向方法。通过将无源状态和有源状态下线阵输出数据的协方差矩阵进行对消运算去除有源干扰和噪声分量,并对约束最小冗余线阵的波达方向(DOA)估计算法进行改进,构造了新的协方差Toeplitz矩阵,有效抑制了由阵列非均匀性导致的伪峰,提高了阵列的DOA估计性能。仿真结果表明:该算法在低信噪比背景下具有抗有源干扰能力,扩展了阵列孔径,并具有较高的测向精度和鲁棒性。     

Application of the Normalized LMS Algorithm to MSLC

For some conditions, the convergence time of the conventional LMS algorithm is longer than the radar dwell time so that the MSLC technique does not cancel jammers. The convergence time depends upon the power and angular locations of the jammers. The normalized LMS technique can decrease convergence times by several orders of magnitude. It causes the convergence time to be essentially independent of the jammer powers and decreases the convergence time dependence upon location. The derivation of an exact first moment analysis of the weights for the normalized LMS algorithm is given. Simulation results are also given. There is excellent agreement between the two.