Theory of LDV Tracking Systems

The application of frequency-tracking systems to the analysis of laser doppler velocimeter (LDV) signals degraded by background noise has been studied both theoretically and experimentally. Expressions are derived for both the correlation function and the expected value of the phase derivative in the general case of noise off center from the Doppler frequency, and these results are specialized to specific cases of practical interest. Laboratory measurements of output signal-to-noise ratio (SNR) and dc error, for varying input SNR and noise center frequency offset, show good agreement with the theoretical predictions.     

宽带信号角跟踪和四通道单脉冲方案

分析了宽带信号角跟踪的特殊问题及其实现方案。基于互相关函数的角误差检测方法,推导出了在非相关噪声及相关噪声背景下差路信号的输出信噪比及其角度随机误差的数学表达式,进而给出了带宽增益和最佳带宽的概念,以及提高输出信噪比的方法。为了在低载噪比（C/N）时获得角捕获所需要的和路信号以及差路的归一化信号,提出了四通道单脉冲方案。最后归纳出了低C/N时宽带信号角捕获和角跟踪的几种方法并提出了建议。     

Research on Auto-detection for Remainder Particles of Aerospace Relay Based on Wavelet Analysis

Aerospace relay is one kind of electronic components which is used widely in national defense system and aerospace system. The existence of remainder particles induces the reliability declining, which has become a severe problem in the development of aerospace relay. Traditional particle impact noise detection (PIND) method for remainder detection is ineffective for small particles, due to its low precision and involvement of subjective factors. An auto-detection method for PIND output signals is proposed in this paper, which is based on direct wavelet de-noising (DWD), cross-correlation analysis (CCA) and homo-filtering (HF), the method enhances the affectiv-ity of PIND test about the small particles. In the end, some practical PIND output signals are analysed, and the validity of this new method is proved.     

Optimal Digital Beam Splitting for Radar Beacon Systems

Beam splitting for a radar beacon system that scans in azimuth is investigated from a theoretical viewpoint. The video output is quantized into two levels corresponding to a detection and no detection. Further, the antenna sensitivity profile is described by sin ?/?. For this system, a digital method of beam splitting that minimizes angular error is developed. Prior information about the probable location of targets can be included. Both Bayesian and minimax approaches are developed. The minimax estimate of the target azimuth is the average of the angles at which beacon signals are detected. The antenna beam can be interpolated by a factor of 10 when the signal power is 3 dB above the noise and without prior azimuth information The interaction of beam splitting and detection is discussed.     

Calculation of Output Noise Variances for Discrete Time-Invariant Filters

Certain calculations to minimize output noise variance are introduced. Many applied problems in sampled data systems require that data be smoothed in the presence of noise for the prediction of future positions, velocities, or accelerations. Smoothing coefficients in discrete time-invariant filters are computed to minimize the output noise variance, but under the constraints that the function and derivatives be predicted ahead. The output noise variance is seen to be a function of the input noise, the number of input signals (N+1) that the filter has to smooth, and the prediction time ?T. Four examples are given in the derivation of smoothing coefficients for step and ramp inputs subjected to either almost white noise or Gaussian-Markoff noise. The examples illustrate the number of constraint relations that the filter smoothing coefficients must satisfy for function and/or derivative convergence under noise-free conditions. The smoothing coefficients are also a function of the type of noise input into the system or the discrete filter. From the examples, it can be observed that as N becomes larger, the output noise variance becomes smaller, but the computation time is increased.     

考虑噪声抑制的高超声速风洞气动力识别方法

对于风洞试验中全尺寸模型试验的非平稳信号进行载荷辨识仍存在诸多问题。针对全尺度模型试验的非平稳信号载荷辨识提出了一种基于深度残差收缩网络（DRSN）深度学习技术的智能载荷辨识方法，该方法通过深度学习提取测力系统输出数据中的气动力、惯性力和噪声等特征，通过注意力机制对每组数据进行获取阈值，再通过软阈值函数对特征进行滤波降噪，有效辨识出测力系统响应信号中的惯性力分量并进行剔除，实现气动力载荷辨识。在测试验证中，均值法的辨识精度为85%以上，DRSN模型的辨识精度为94%以上，证明DRSN模型能有效降低噪声和惯性力对于载荷辨识的干扰，用于非平稳信号的载荷辨识具有精度高、可靠性好等特点。     

Output Signal-to-Noise Ratio for Amplitude and Intensity Modulated Laser

General expressions are obtained for output SNR for both amplitude- and intensity-modulated lasers, where bandlimited Gaussian noise has been chosen as a modulating signal, and in the presence of background light. Two types of modulating signals are considered: the baseband and bandpass modulating signals. Detailed calculations are made for output SNR when an ideal narrowband optical filter is used. The dependence of output SNR on several parameters, such as the center frequency of the modulating signal, the effective average quantum rate, and input SNR, are discussed. In addition, the difference in performance between amplitude and intensity modulation is discussed. The detection characteristics of the homodyne system are also considered.     

A Superlimiting Phased-Array Receiving System in a Two-Source Environment

The performance of a uniformly spaced phased-steered line array with element channel superlimiting is studied for far-field sources consisting of 1) two sinusoidal signals with different frequencies and angular locations, and 2) a sinusoid and a noise signal at different angular locations. Attention is focused on the nonlinear case where internal noise is negligible compared to both input signals. The analysis for the two-sinusoid case gives the precise frequencies, positions, and amplitudes of all apparent sources. In addition to the two active sources, the array output has an array of images arranged symmetrically in sine space about the larger input, at intervals equal to the spacing between the two active sources. For the case of a separated sinusoid and a noise source, the analysis shows that the angular positions and average powers of the array outputs duplicate the double-sinusoid results, but the images have noise-like spectra. The analyses are confirmed by experimental results obtained with a 60-element superlimiting X-band array.     

Eigenanalysis for interference cancellation with minimum redundancy array structure

In a previous work, the principles of the eigenanalysis method for interference cancellation was studied for uniform regular array (URA) structure, wherein the array elements are equally spaced. The main objective of this paper is to extend the results of that work to adaptive arrays with different geometry termed "minimum redundancy array" (MRA). An efficient method is presented to solve the minimum variance optimization problem and explicit analytical solutions are derived for the optimal weight vector and output noise variance of the eigencanceler. Performance analysis of the general N-element array was first derived and used to extract the performance of MRA. URA is also considered as a special case. The closed-form equation depicts the minimum variance noise residue for the single interference case, while an interactive procedure is suggested for the two interferences case. If there are more than two interferences, we propose to use direct numerical calculation.     

Performance Analysis of Monopulse Receivers for Secondary Surveillance Radar

In modern secondary surveillance radar (SSR) the monopulse technique is currently introduced for the measurement of the azimuth of the targets. The monopulse technique is based on a suitable processing of signals received by a multiple antenna. In SSR the signals are generated by a transponder on the aircraft as replies to interrogations from ground equipment, and consist of trains of pulses. The monopulse measurements can be carried out on the basis of a single pulse from each train, so that it provides a great number of azimuth estimates. Many monopulse measurement devices exist, corresponding to different processing techniques. From the point of view of accuracy and precision, their behaviors differ with respect to the sources of errors, both internal (noise and imperfect calibrations) and external (interference and propagation effects). The four main types of monopulse receivers are analyzed here with respect to the effects of the internal error sources on the resulting measurement accuracy. After an introductory discussion of the performances of the receivers, a detailed analysis is carried out on the basis of a general mathematical model. The results are given in an analytical form and in some comprehensive diagrams.     

Detection probabilities for correlated Rayleigh fading signals

Both the method of saddlepoint integration and its associated saddlepoint approximation are applied to calculating the probability of detecting correlated Rayleigh-fading signals in Gaussian noise by means of a detector that integrates M samples of the output of a quadratic rectifier. The quadrature components of the signal samples are modeled as an autoregressive moving-average process, and specific results are exhibited for a first-order Markov process. By these methods the fluctuation loss can be computed for much larger values of M and for larger values of the detection probability than previously. Values calculated by the saddlepoint approximation prove to be close enough to the exact values to be useful over a broad range of signal parameters     

利用时延相关解调法诊断滚动轴承的故障

为诊断滚动轴承的故障,常常对其振动信号进行包络解调,以获取故障特征。但所测振动信号中,包含大量的噪声,严重地影响解调结果,使得滚动轴承的故障特征难以凸现。为此,利用时延相关解调法以实现降噪解调。该方法利用相关函数的降噪特性,首先对振动信号进行相关分析,得信号的自相关函数。然后对自相关函数适当延迟以尽量避开噪声影响,再进行Hilbert变换,以求得解调结果。实验证明在滚动轴承故障诊断中时延相关解调法与直接解调法相比,噪声影响大幅减小,故障信息得以凸现。     

齿轮故障诊断的时延相关解调法

为诊断齿轮与滚动轴承的故障,常常对其振动信号进行包络解调,以获取故障特征。但所测振动信号中,包含大量的噪声,严重地影响解调结果,使得齿轮或滚动轴承的故障特征难以凸现。为此,本文提出了时延相关解调法以实现降噪解调。该方法利用相关函数的降噪特性,首先对振动信号进行相关分析,得信号的自相关函数。然后对自相关函数适当延迟以尽量避开噪声影响,再进行Hilbert变换,以求得解调结果。本文进行了仿真信号验证和实验验证,证明时延相关解调法与直接解调法相比,噪声影响大幅减小,故障信息得以凸现。      

A Semi-Empirical Approach to the PLL Threshold

This correspondence considers the response of the PLL near threshold to an input consisting of a modulated carrier and white, Gaussian noise. For high input signal-to-noise power ratios ?, the output noise power is Gaussian with a parabolic spectrum. As ? is decreased, the PLL tends to lose lock which gives rise to impulses or ?spikes? in the output with a resulting white power spectrum. The additional output noise due to these ?spikes? causes a threshold in the output signal-to-noise ratio. Unfortunately the loss of lock rate in the PLL depends on the modulation as well as the noise power. A semiempirical approximate expression for the loss of lock rate as a function of the noise and sinusoidal frequency modulation is presented and is used to determine the optimum design procedure for PLL's to demodulate FM signals of varying modulation indexes, ?.     

Radar Partial Coherence Theory: An Introduction

The nature of physical phenomena is such that scattering from portions of an object, a number of objects, or clutter, is not completely unrelated; the underlying environment causes some degree of order in the phenomenon. Radar partial coherence theory describes a structure for the general target, or clutter, and its relationship to radar cross section, waveform coding, and the radar output signal. The clutter ambiguity function is introduced for extended bodies and embraces the (Woodward) ambiguity function for a point target. Due to nonlinear effects caused by partial coherence within the general target, radar signals and targets are formulated in terms of mutual coherence functions. The basic quantities describing the radar output are 1) the radar mutual coherence function (formulated in terms of the radar waveform) and 2) the target mutual coherence function which depends upon target properties, physical environment, and viewing aspect. Random noise (independent point scatterers) and partially coherent portions of reflecting bodies are made accountable in the theory. Partial coherence effects are treated as patches of reflected energy: self-coherent energy patches plus mutually coherent energy among the patches.     

含噪声的转子碰摩混沌信号分类识别

采用基于竞争学习和聚类分析的学习向量量化 ( LVQ)方法 ,研究转子碰摩混沌响应信号的神经网络分类识别问题 ,给出了相应的理论分析和计算结果 ,着重研究了 LVQ网络在不同噪声时的识别情况。分析结果表明 ,该方法可以实现转子碰摩混沌信号与其它响应信号的分类识别 ,并且具有良好的抗噪性能 ,为转子碰摩混沌信号的分类识别提供了一种较为直接的实时处理方法。     

Operational modal parameter identification with colored noise excitation

Operational Modal Analysis (OMA) refers to the modal analysis of a structure in its operating state. The advantage of OMA is that only the output vibration signal of a system is used in the analysis process. Classic OMA is based on the white noise excitation assumption and many identification methods have been developed in both time domain and frequency domain. But in reality, many environmental excitations are not compliance with the white noise assumption. In this paper, a method of half power bandwidth analysis is applied to power spectrum analysis to deal with the colored noise and trapezoidal spectral excitation. The modal frequencies and modal damping ratios are derived and the error caused by trapezoidal spectral and colored noise excitation are analyzed. It is proved that the OMA algorithm based on the white noise assumption can be extended to the colored noise environments under certain conditions. Finally, a simulation example with a cantilever beam and a vibration test with four kinds of colored noise and trapezoidal spectrum base excitation are carried out and the results support the proposed method.     

Software approach to access UWB interference on GPS receivers

Ever since the FCC approved the use of UWB devices in commercial and federal bands, various agencies whose operations and/or products rely on the integrity of signals within certain "restricted" radio frequency bands have voiced concerns over the potential impact of the UWB interference. GPS signals are among these "restricted" bands. Several groups in the GPS community have conducted experimental studies concerning the impact of UWB interference on the performance of various grades of commercial and aviation GPS receivers. In this paper, we present a software approach to simulate and evaluate UWB interference on GPS receivers. The software approach provides greater flexibility in the design of testing scenarios, such as the inclusion of a large number of aggregated UWB devices, the generation of new UWB signals and modulation schemes, and the possibility of extending the study to new GPS signals. The paper discusses a general framework for developing algorithms to evaluate UWB and GPS interference under a wide variety of hardware and software conditions. This framework consists of three classes of components: input, processing, and analysis. The input components are responsible for the generation of UWB signal waveforms and modulation schemes, and GPS signals. The processing components include a simulated model of GPS RF front end and software implementation of GPS processing blocks, such as acquisition, tracking, and post-processing. The analysis components focus on the study of specific receiver processing component outputs. Both real and simulated UWB signals can be used in the study. The real UWB signals are primarily used to validate the simulation procedure, whereas the simulated UWB signals are used to allow the immediate incorporation of new UWB waveforms and modulations in the evaluations. This paper presents details of the software components developed and the preliminary results achieved     

一种时间传递系统中调制器时延的数字标定算法

针对传统示波器观察法测量BPSK（Binary phase shift keying,二进制相移键控）调制器时延时存在整码元模糊、噪声敏感、载波初相要求苛刻及标定精度低的缺点,利用软件无线电的相关处理技术,提出一种精密的BPSK调制器时延标定算法.通过高速数字示波器对BPSK调制器的输入基带信号和输出载波调制信号进行双通道同步过采样,对输出信号与输入信号采样值进行循环相关,根据相关峰值对应的样本点序号以及连接电缆的校准时延,计算得到BPSK调制器时延.仿真和试验验证表明：提出的算法不受载波初始相位影响,时延标定上限可达1个伪随机码周期,而且低载噪比情况下也能得到准确结果.数字示波器的通道采样率为10 GSa/s时,采用提出的算法进行BPSK调制器时延标定,标定结果的不确定度可以达到0.2 ns.