数字储频器相干性分析

主要分析数字储频本身对复制信号绝对相干性的影响，讨论了DRFM复制信号的相干性、储频误差与输入信号及系统参数的关系，推导出了计算公式，最后根据实际应用对DRFM的相位相干性进行了说明。     

DRFM相位校正技术研究

DRFM复制信号的相位不连续会破坏输出信号的相干性，影响干扰效果。将信号取样的起始和终止相位之差记录下来，并在信号复制时进行相位补偿的新技术，可以消除复制信号首尾相位差，并简化电路。3比特相位DRFM中相位校正的精度优于π／4。     

基于频率集的DRFM噪声干扰探讨

分析了传统捷变频干扰技术优缺点,运用数字射频存储器（DRFM）具有储频精度高、相干性保持好的特点,提出了基于频率集的噪声干扰方式,分析了该干扰方式效果和优点。结果表明：该干扰方式具有明显优势,具有广泛的应用前途。     

数字射频存储技术及其在电子对抗中的应用

描述数字射频存储技术(DRFM)的原理与结构，分析了DRFM信号相干性的引入因素及影响，对DRFM在电子对抗中的应用方式及应用中的若干问题进行了探讨。     

数字储频技术发展刍议

描述了数字射频存储器（DRFM）的结构和工作原理,分析了数字储频技术在电子干扰方面的优点和影响数字射频存储干扰效果的几个参数,重点研究了数字储频技术和雷达反数字储频干扰的发展趋势,为DRFM干扰及反干扰的进一步研究应用提供了理论基础。     

一种利用多站角度融合抗干扰方法研究

随着自卫式干扰技术的不断发展,数字储频(DRFM)技术广泛地应用到现代干扰装备中,数字储频技术能够对雷达信号进行多次复制转发干扰,在自卫式干扰场景中形成主瓣距离欺骗干扰,对目标检测和跟踪带来了困难。文中提出一种利用雷达网络内其他节点采用与被干扰雷达同样的工作频点被动接收,对干扰源进行测角处理,通过有源探测和无源测角融合处理实现主瓣内其他虚假目标的剔除。文中最后分析了该方法的优点和缺点,并与传统的测向交叉定位的性能相比较,给出了不同方法使用的适用范围。     

基于DRFM的欺骗干扰及反干扰

数字射频存储器（DRFM）是现代电子对抗中常用的干扰器件,基于DRFM的干扰效果非常显著。介绍了基于DRFM的延时和移频产生距离假目标的干扰,分析了反欺骗干扰的方法,阐述了反数字储频干扰的发展趋势。     

反数字储频干扰雷达波形设计研究

介绍了数字射频存储器（DRFM）的结构和工作原理。针对目前还没有成熟的理论来对付数字储频干扰的特点,设计了两种复杂的雷达波形反数字储频干扰,并进行了仿真验证,为反数字储频干扰的研究提供重要的理论依据。     

相位数字储频的性能与干扰效果

分析数字储频在电子对抗中的主要性能、影响性能的主要因素和储频性能与干扰效果、干扰功率利用率的关系。分析说明影响储频信号相参性的主要因素是本振和时钟的频漂,储频输出信号的相参性和储频的比特数无关。量化噪声是影响储频信噪比的关键因素,适当的输入信比有改善储频输出信噪比的作用,有利于抑制交调,互调产物。储频误差是采存样本的首尾相位差不为０造成的,储频误差与储频的比特数、连续复制样本数和采样时间长度有关。     

基于加权网络的DRFM干扰PD雷达特征研究

数字射频存储器(DRFM)通过对雷达信号进行复制和调制,能对雷达产生良好的干扰效果。基于加权网络分析了3bit相位量化DRFM干扰信号特性,提出利用等均值离散的方法求得加权网络的加权值,建立了3bit相位量化DRFM时域波形表达式,分析了3bit相位量化DRFM干扰信号的频谱特性。利用PD雷达模型对DRFM干扰效果进行了分析,仿真证明DRFM对PD雷达具有良好的干扰效果。     

Source localization with distributed sensor arrays and partial spatial coherence

Multiple sensor arrays provide the means for highly accurate localization of the (x,y) position of a source. In some applications, such as microphone arrays receiving aeroacoustic signals from ground vehicles, random fluctuations in the air lead to frequency-selective coherence losses in the signals that arrive at widely separated sensors. We present performance analysis for localization of a wideband source using multiple, distributed sensor arrays. The wavefronts are modeled with perfect spatial coherence over individual arrays and frequency-selective coherence between distinct arrays, and the sensor signals are modeled as wideband, Gaussian random processes. Analysis of the Cramer-Rao bound (CRB) on source localization accuracy reveals that a distributed processing scheme involving bearing estimation at the individual arrays and time-delay estimation (TDE) between sensors on different arrays performs nearly as well as the optimum scheme while requiring less communication bandwidth with a central processing node. We develop Ziv-Zakai bounds for TDE with partially coherent signals in order to study the achievability of the CRB. This analysis shows that a threshold value of coherence is required in order to achieve accurate time-delay estimates, and the threshold coherence value depends on the source signal bandwidth, the additive noise level, and the observation time. Results are included based on processing measured aeroacoustic data from ground vehicles to illustrate the frequency-dependent signal coherence and the TDE performance.     

Polarization-independent transmission on a single mode fiber usingcoherence modulation of light

A polarization-independent transmission link on a single mode fiber at 1300-nm wavelength is demonstrated using coherence multiplexing. The use of a source with a very short coherence length (about 200 μm) allows an easy implementation of the suitable optical delays (some millimeters) using LiNbO₃ modulators matched to fiber interferometers. Experiments were conducted with transmission of analog signals and baseband TV signals on a 2500-m-long single mode fiber. The polarization-independence of the method is obtained at the cost of relatively high losses. The high losses are introduced by the interferometers that are required at both ends of the link (theoretical losses of -3 dB/interferometer). They are physically inherent in the coding and detection process, which requires optical delays greater than the coherence length, and hence cannot be decreased     

Coherence function of interrelated periodically nonstationary random processes

A coherence function characterizing the correlation between harmonic components of two signals that are described by periodically correlated random processes has been proposed. Such function is shown to be invariant with regard to linear transformations of signals.Aformula for coherence function is concretized for the amplitude- and phase-modulated signals.     

Coherence multiplexing of fiber-optic interferometric sensors

This paper describes a method of multiplexing several optical signals onto a single spatial channel (e.g., a single-mode fiber) using a short coherence length continuous wave light source. Several system configurations which utilize this technique are proposed, and some design considerations are discussed. Experimental results for a single sensor and receiver are presented and compared with theoretical predictions.     

星载分布式SAR干涉信号分析

星载分布式合成孔径雷达(SAR)具有双站和斜视的特点,本文分析了在这种情况下干涉信号的一些特征:(1)干涉信号相位与成像处理间的关系;(2)考虑地形情况下,干涉信号相位差及其相干性;(3)考虑配准误差时干涉信号相位差及其相干性。仿真分析了一系统干涉信号相干性随地形、基线及配准误差的变化。     

Evolutionary Coherence of Nonstationary Signals

Coherence is a widely used measure for characterizing linear dependence between a pair of signals. For nonstationary signals, the autospectrum, cross spectrum, and coherence between signals may evolve over time. A standard approach is to divide the signals into overlapping blocks of fixed width and then smooth (over frequency) the periodogram matrix at each time block. In this paper, a consistent estimation procedure is developed using time-localized linear filtering. The proposed method automatically selects, via repeated tests of homogeneity, the optimal window width for estimating local coherence. It is pointwise adaptive in the sense that the width of the optimal interval is allowed to change across time. Under the locally stationary process framework, we develop a central limit theorem on the Fisher-z transform of our time-localized band coherence. We apply our method to a pair of highly dynamic brain waves signals whose coherence is shown to evolve during an epileptic seizure.     

A statistical description of stimulated Brillouin scattering beamcombination efficiency

The mutual coherence between two stimulated Brillouin signals produced by undepleted pump beams that are partially overlapped is studied. The mutual coherence of the stimulated-Brillouin-scattered beams determines the efficiency with which the two beams can be combined. The statistical properties of the mutual coherence are calculated. The mechanism for coupling of two stimulated-Brillouin-scattering outputs is four-wave mixing. Mutual coherence is found to depend on the pump beam's pulse duration, the medium's phonon lifetime, and the degree of overlap between the laser pump beams     

Cyclic Wiener filtering: theory and method

Conventional time and space filtering of stationary random signals, which amounts to forming linear combinations of time translates and space translates, exploits the temporal and spatial coherence of the signals. By including frequency translates as well, the spectral coherence that is characteristic of cyclostationary signals can also be exploited. Some of the theoretical concepts underlying this generalized type of filtering, called frequency-shift (FRESH) filtering, are developed. The theory of optimum FRESH filtering, which is a generalization of Wiener filtering called cyclic Wiener filtering, is summarized, and the theory is illustrated with specific examples of separating temporally and spectrally overlapping communications signals, including AM, BPSK, and QPSK. The structures and performances of optimum FRESH filters are presented, and adaptive adjustment of the weights in these structures is discussed. Also, specific results on the number of digital QAM signals that can be separated, as a function of excess bandwidth, are obtained     

Approximate Time-Variable Coherence Analysis of Multichannel Signals

We present a new method for signal extraction from noisy multichannel epileptic seizure onset EEG signals. These signals are non-stationary which makes time-invariant filtering unsuitable. The new method assumes a signal model and performs denoising by filtering the signal of each channel using a time-variable filter which is an estimate of the Wiener filter. The approximate Wiener filters are obtained using the time-frequency coherence functions between all channel pairs, and a fix-point algorithm. We estimate the coherence functions using the multiple window method, after which the fix-point algorithm is applied. Simulations indicate that this method improves upon its restriction to assumed stationary signals for realistically non-stationary data, in terms of mean square error, and we show that it can also be used for time-frequency representation of noisy multichannel signals. The method was applied to two epileptic seizure onset signals, and it turned out that the most informative output of the method are the filters themselves studied in the time-frequency domain. They seem to reveal hidden features of the epileptic signal which are otherwise invisible. This algorithm can be used as preprocessing for seizure onset EEG signals prior to time-frequency representation and manual or algorithmic pattern classification.     

A blind source separation technique using second-order statistics

Separation of sources consists of recovering a set of signals of which only instantaneous linear mixtures are observed. In many situations, no a priori information on the mixing matrix is available: The linear mixture should be “blindly” processed. This typically occurs in narrowband array processing applications when the array manifold is unknown or distorted. This paper introduces a new source separation technique exploiting the time coherence of the source signals. In contrast with other previously reported techniques, the proposed approach relies only on stationary second-order statistics that are based on a joint diagonalization of a set of covariance matrices. Asymptotic performance analysis of this method is carried out; some numerical simulations are provided to illustrate the effectiveness of the proposed method