Method of Forming Classified Training Sample in Case of Spacial Signal Processing under Influence of Combined Interference

Under the conditions of the combined interference, the operation efficiency of the radar equipment is substantially deteriorated. This is due to the decorrelation of the signals of the point source of active interference acting on the radar by passive interference. In this article methods of formation of the classified training sample, generated only by active interference, are considered for adaptation of the weight coefficients of spatial filters under conditions of combined interference presence. An effective method of forming the classified training sample generated by active masking interference was developed for spatial processing of radar signals under conditions of simultaneous exposure to passive interference. The developed method of forming the training sample is based on estimating the width of the normalized autocorrelation function in each element of the distance resolution. The current analysis of the combined interference components in each resolution element improves the quality of the interference component classification and, as a result, minimizes the effect of passive interference on the adaptation process of the spatial filter. The theoretical and practical aspects of the formation of the classified training sample are considered. The functional scheme of the classifier for the combined interference components is developed. The efficiency of the proposed method is compared with known correlation methods. The current analysis of the combined interference components in each element of the range resolution improves the quality of interference classification, which is important in the context of complex hydrometeorological conditions.     

Method of compensating the active component of combined interference in coherent pulse radar

The combined impact of active and passive interferences on coherent pulse radar was investigated. A mathematical model was developed implementing a new method for compensating the active component of combined interference in coherent pulse radar employing spectral differences in the structure of active and passive interferences. The results of simulation reveal that the polarization-time signal processing involving the use of rejection filters for suppression of passive interferences in circuits of forming the weight coefficients of automatic compensator make it possible to significantly enhance the quality of active interference compensation under conditions of exposure to combined interferences. The rejection of passive interference in circuits of forming the weight coefficients is shown to eliminate the distortion of passive spectrum distortion at the output of adaptive polarization filter.     

An adaptation of nonrecursive rejectors

We considered criteria and algorithms of nonrecursive rejectors adaptation to unknown spectral- correlation characteristics of passive interferences. Structural charts of adaptive rejectors for sliding and group processing are represented. Analysis of adaptive rejectors efficiency, dependently on their order and structure and also on learning sample volume and interference parameters was carried out.     

基于FRFT的伪码引信自适应LFM干扰对消方法

该文分析了LFM干扰对伪码引信相关输出的影响,当干扰强度超出伪码引信自身的抗干扰容限时,相关输出严重恶化,因此必须采取相应的抗干扰措施。考虑到LFM干扰与伪码引信有用信号间存在着强的时频耦合,提出了基于FRFT的自适应干扰对消方法。该方法首先对观察信号进行FRFT,估计干扰的特征参数,利用估计出的干扰参数构造自适应干扰对消器,将干扰去除。仿真表明,该方法能够有效滤除LFM干扰,相关输出得到显著改善,该方法对单分量和多分量干扰均有效,不受交叉项影响。     

基于协方差矩阵双层重构的稳健自适应单脉冲测角

常规自适应单脉冲方法在主瓣干扰下会引起自适应波束形成性能恶化并导致其单脉冲比曲线严重失真,影响被动雷达的测角精度与跟踪性能。针对此问题,提出了一种适用于平面阵的基于协方差矩阵双层重构的稳健自适应单脉冲测角方法。首先,利用Capon功率谱通过稀疏重构法初步估计出干扰加噪声协方差矩阵,通过干扰导向矢量估计完成对协方差矩阵的优化校正以提高自适应波束形成性能;然后,基于线性约束最小方差(Linearly Constrained Minimum Variance, LCMV)准则对方位角和俯仰角进行联合线性约束以避免单脉冲比曲线在主瓣干扰下严重失真;最后,根据自适应单脉冲比值求出目标与波束指向之间的偏转角以实现目标测角。与常规方法相比,所提方法在干扰抑制能力与测角精度上都有显著提升。     

Optimization of systems for interperiod signal processing

The optimization methods based on the probabilistic criterion of systems for interperiod signal processing have been considered. The specified methods perform coherent rejection of passive interferences (clutter) with subsequent coherent or incoherent accumulation of rejection residues. Adaptation principles of recursive rejection filters with a priori uncertainty of correlation characteristics of clutter were proposed. The efficiency analysis of adaptive rejection filters depending on the estimation errors of clutter parameters was carried out.     

迭代自适应收缩加权融合的波束形成方法

自适应数字波束形成是通过对阵列接收数据进行加权处理来获得最大的输出信干噪比,对采样协方差矩阵的依赖性较大。针对小样本条件下采样协方差矩阵求逆算法性能下降问题,提出迭代自适应加权融合样本协方差矩阵与先验协方差矩阵的波束形成算法。在估计协方差矩阵时,依据最小均方误差准则计算加权系数,并采用迭代自适应的方式更新先验协方差矩阵。仿真结果表明,所提方法能显著提高小样本条件下的协方差矩阵估计精度,能获得更大的输出信干噪比。      

基于特征子空间的强主瓣干扰抑制方法

当空间中存在大功率主瓣干扰时,传统特征投影类干扰抑制方法存在主瓣峰值偏移、 旁瓣内干扰零陷变浅等问题.针对上述问题,本文提出一种新的基于特征子空间的主瓣干扰抑制方法.首先根据赤池信息准则(AIC)与相关性判别分离主、旁瓣干扰的特征矢量;其次利用特征投影预处理抑制主瓣干扰分量;最后定义新的权矢量赋形方式,在主瓣子空间约束...     

基于多PRI脉压回波的单通道雷达干扰分离方法

研究了一种基于盲源分离的单通道雷达有源相干干扰抑制方法。针对伴随式干扰场景，在间歇采样转发干扰、部分脉冲密集转发干扰等有源相干干扰并存的条件下，建立了基于脉冲压缩的多脉冲重复间隔采样抗主瓣有源相干干扰模型并对其可行性进行了证明。针对现有单通道盲源分离方法在时域进行分离效果有限的问题，提出对脉压后的距离维数据进行盲源分离的思想，可在一定程度上抑制噪声对盲源分离的影响。同时，由于目标信号和干扰信号在脉冲压缩后重合度较低，可获得更好的分离效果。仿真和实测结果表明，在多个干扰源存在的条件下，本方法可有效分离真实目标回波和干扰回波。当信噪比大于5 dB时，目标脉压回波相似系数接近100%；选取虚拟通道数越多，分离效果越好。     

一种通用的GPS多类干扰抑制方法

欺骗式干扰、压制式干扰、卫星多径信号干扰是GPS最常见的,也是最有威胁的干扰。本文针对这三种干扰共存的情况,将子空间技术和低副瓣常规波束形成技术相结合,提出了一种通用的抗干扰算法。该算法能够同时抑制欺骗式干扰、压制式干扰和卫星多径信号干扰,并对GPS信号提供信号处理增益。本文还分析了欺骗式干扰和GPS卫星信号的相关特性,针对不同的相关性,提出分别采用协方差矩阵特征值分解和高分辨相干子空间估计方法来计算干扰子空间。仿真结果表明本文方法可以同时抑制多类干扰,保证接收机能够准确捕获到卫星信号。      

基于特定导频OFDM信道估计的研究

在OFDM系统中,准确的信道估计是对抗瑞利衰落信道中信道干扰的关键。提出了一种对OFDM信道估计的新方法,利用CR Spline函数的插值方法,设计一个特定的导频结构,从而导出信道估计的CR Spline函数形式,用该函数近似信道衰落包络。实验结果表明,仅用少量导频就可以近似出信道特性,并具有良好的平滑性。计算机仿真证明了提出算法的有效性。     

Parallel Interference Cancellation in Multiuser CDMA Channel Estimation

Parallel interference cancellation (PIC) based channel parameter estimators for frequency selective fading channels are proposed for the uplink in code-division multiple-access (CDMA) mobile communication systems. The performance of PIC based algorithms depends heavily on the quality of the multiple-access interference estimates, which can be improved by using adaptive channel estimation filters. The performance of two adaptive complex channel coefficient estimation filters has been verified in a fading channel by computer simulations. According to the results, the PIC based adaptive channel estimators outperform clearly conventional, successive interference cancellation, and decorrelation based adaptive channel estimators. The PIC method is also used in delay tracking. By using the principles of sample-correlate-choose-largest (SCCL) delay trackers, a robust algorithm for multiuser delay tracking in fading channels is obtained.     

基于广义合成分析和深度神经网络的自回归系数估计方法

自回归(AR)模型是一类描述时序序列相关性的有效方法,经典的AR系数估计方法对残差信号做了简单的假设,在噪声干扰等复杂场景中难以准确估计AR系数,而基于深度神经网络(DNN)的AR(DNN-AR)系数估计方法在训练中容易受到莱文逊-杜宾迭代(LDR)解法的数值稳定性的影响.为改善DNN-AR系数训练的稳定性和整体性能,...     

基于样本质量估计的空间正则化自适应相关滤波视觉跟踪

相关滤波(CF)方法应用于视觉跟踪领域中效果显著,但是由于边界效应的影响,导致跟踪效果受到限制,针对这一问题,该文提出一种基于样本质量估计的正则化自适应的相关滤波视觉跟踪算法。首先,该算法在滤波器的训练过程中加入空间惩罚项,构建目标与背景的颜色及灰度直方图模板并计算样本质量系数,使得空间正则项根据样本质量系数自适应变化,不同质量的样本受到不同程度的惩罚,减小了边界效应对跟踪的影响;其次,通过对样本质量系数的判定,合理优化跟踪结果及模型更新,提高了跟踪的可靠性和准确性。在OTB2013和OTB2015数据平台上的实验数据表明,与近几年主流的跟踪算法相比,该文算法的成功率均为最高,且与空间正则化相关滤波(SRDCF)算法相比分别提高了9.3%和9.9%。     

有源欺骗干扰环境下的DOA估计

针对有源欺骗干扰环境下基于小样本的DOA估计问题,该文提出自适应极化滤波(APF)联合块稀疏贝叶斯学习(BSBL)算法的DOA估计方法。首先,通过APF抑制干扰能量,提高信干比。然后,建立有源欺骗干扰环境下的稀疏贝叶斯模型,基于相邻快拍相关性,利用BSBL算法进行DOA估计。仿真和实测数据处理结果表明,所提方法降低了干扰对BSBL算法的影响,且与APF联合子空间类算法或最大似然算法(ML)相比,具有更高的空间分辨率和DOA估计精度。     

Algorithm of Robust Frequency Estimation in a Channel with White Gaussian Noise and Pulse Interferences

An algorithm for robust frequency estimation in a channel with additive white Gaussian noise and pulse interference is proposed. The algorithm involves iterative elimination of pulse interferences and subsequent calculation of the maximum likelihood estimate. It is demonstrated that the proposed filter-cleaner differs from the well-known Martin–Thomson filter in the functional dependence of adaptive coefficients on the estimates of parameters of distributions of the linear prediction error and the amplitude envelope of the signal. The results of mathematical modeling and numerical estimation of the threshold point of the method (0.49) are presented.     

Adaptive time-varying cancellation of wideband interferences inspread-spectrum communications based on time-frequencydistributions

The paper proposes an adaptive method for suppressing wideband interferences in spread-spectrum (SS) communications. The proposed method is based on the time-frequency representation of the received signal from which the parameters of an adaptive time-varying interference excision filter are estimated. The approach is based on the generalized Wigner-Hough transform as an effective way to estimate the instantaneous frequency of parametric signals embedded in noise. The performance of the proposed approach is evaluated in the presence of linear and sinusoidal FM interferences plus white Gaussian noise in terms of the SNR improvement factor and bit error rate (BER)     

Partially Loaded Superimposed Training Scheme for Large MIMO Uplink Systems

This paper proposes a new superimposed training (ST) scheme for uplink multi-user multi-cell system, where each base station, equipped with a large number of antennas (M), communicates to single antenna users. In uplink training phase, large number of users within limited coherence time introduces the pilot contamination, which causes two types of interferences in data estimation. The first type, which is referred as self interference, arises due to the dependence between channel estimate and estimation error of the same user, while the second type, known as cross interference, occurs because of the correlation between ST vectors of different users. In this paper, an ST scheme with variable data length is proposed for Rician fading channels. For simplicity of analysis, a single cell model is considered first to derive mean squared error and signal to interference plus noise ratio. The analysis is further extended to multi-cell system. Various limiting cases are investigated, and the design parameters viz., power allocation factor and length of data vector, are optimized. Simulation results verify that the proposed ST scheme reduces self interference, and yields sum rate improvement over conventional ST scheme.     

基于局部搜索的机载外辐射源干扰抑制算法

在机载外辐射源雷达不纯净参考信号条件下,参考通道中的多径与回波匹配得到的干扰将降低空时自适应处理的目标检测能力,而网格失配问题严重影响了干扰的估计性能.本文针对网格失配下的机载外辐射源干扰抑制问题,提出一种基于局部搜索的干扰估计算法.该算法在干扰稀疏观测模型的基础上构建全局距离-多普勒字典,从中选择与干扰相匹配的全局网格点;然后以该全局网格点为中心,对多普勒平面精细划分来构建局部多普勒字典,并选择与干扰更匹配的局部网格点;最后估计干扰的距离-多普勒像以实现干扰抑制,克服不纯净参考信号的影响.仿真结果表明,所提算法可降低网格失配导致的抑制性能损失,有效提高不纯净参考信号下空时处理的目标检测能力.     

Channel‐power profile estimation for orthogonal frequency‐division multiplexing systems

In this work, a channel‐power profile estimation for orthogonal frequency‐division multiplexing systems, based on the cyclic prefix (CP), is introduced. By knowing the delay of each path, the time‐dispersion information can be derived. The proposed method, considering long intersymbol interference (ISI) fading channels, requires only the coarse symbol timing information. More specifically, quasi‐stationary fading channels are considered. The basic contribution is to obtain the maximum‐likelihood estimation of the correlation coefficient based on the CP. Subsequently, the relationship between the correlation coefficient and the channel‐tap powers is explored. With the estimate of correlation coefficient, the least‐square solution of the channel‐tap powers can be determined. The proposed method is suitable for both short and long ISI channels. Furthermore, the Cramér–Rao lower bound of the channel‐power profile estimation is analyzed, and simulations confirm the advantages of the proposed estimator. Copyright © 2011 John Wiley & Sons, Ltd.