Canceler Performance Degradation Due to Estimation Noise

The multiple sidelobe canceler (MSLC) configured using the gradient descent algorithm converges to an approximation to the optimum weight vector. Since the weight vector estimate is obtained from a finite data set, there is a random error that increases the steady state residue power. An exact analysis of the steady state residue power for a digital implementation is performed. The analysis predicts that as the algorithm's gain (step size) is increased, the steady state residue power tends towards infinity. The gain that causes infinite power is smaller than the gain that causes instability for the average weight vector analysis. It is shown that the steady state residue power is equal to the minimum residue power multiplied by a factor that depends upon ratios of the eigenvalues. The steady state residue power is evaluated for some special cases. It is shown that the value of the factor is greatest when the interference is due to a single jammer.     

The Uncertainty of Pulse Position Due to Noise

The time at which a received signal crosses a certain level fluctuates in the presence of noise. In this paper, a theoretical formula for the standard deviation of this thresholding time is obtained. The formula is applied to the detection of a pulse perturbed by Gaussian noise. Two practical detection schemes, the peak amplitude estimator and the double differentiator, are theoretically analyzed and compared. Also, a formula is derived which may be used to determine the efficacy of a false-alarm detection system.     

Interference Due to Limiting and Demodulation of Two Angle Modulated Signals

Two angle modulated signals (FM or PM) passing through a limiter and then a demodulator are analyzed. The analysis considers the problem of adjacent carrier interference, direct adjacent channel interference (DACI) or cross talk, and adjacent channel interference (ACI). The analysis of adjacent carrier interference shows that if the 3rd order IM is not to overlap the signal spectra, the carrier frequencies must be separated by 2B where B is the bandwidth of each carrier. The ACI analysis shows that the carrier frequencies must be separated by B+2?m for no ACI, since the demodulator reduces the bandwidth of the 3rd order IM from 3B to 2B+2?m where ?m is the maximum frequency of each baseband. The DACI analysis shows that DACI does not exist in a PM system and is -52 dB for an ideal hard limiter with no bandpass filter. But the DACI is -58 dB for an ideal hard limiter with a more realistic bandpass filter.     

Phase Monopulse Error Due to Nonuniform Noise Background

A phase monopulse antenna system can be used for the high accuracy tracking of active or passive objects in space or on earth. Far-field noise sources that are present in the background of the object being tracked will introduce an offset or bias error in the determination of the angle of incidence of the coherent sinusoidal wave received from the source. The dependency of this bias error upon the nonuniformity of the noise background or equivalently upon the asymmetry of the antenna patterns about the direction to the signal being tracked is determined. Although the variance in the measurement of the sinusoidal source direction can be reduced by increasing the post detection integration time, it is shown that the bias or offset error is unaffected by this change. In order to decrease the offset or bias error the predetection bandwidth must be reduced.     

Normalized LMS Algorithm Degradation Due to Estimation Noise

The steady-state weight vector derived by either the least mean square (LMS) or normalized least mean square (NLMS) algorithms has random deviations from the optimum values. These deviations increase the steady-state residue power. A previous paper derived the LMS weight noise effects for a multiple sidelobe canceller (MSLC) application. This paper describes the NLMS weight noise effects. It is shown that for a thermal noise environment, the weight noise effect for the LMS algorithm is insignificant but is quite significant for the NLMS algorithm. Calculations for example noise plus interference environments imply that the NLMS weight noise effects are always larger than that for LMS.     

Detection of Known Signals in Nonstationary Noise

The basic design of a nonlinear, time-invariant filter is postulated for detecting signal pulses of known shape imbedded in nonstationary noise. The noise is a sample function of a Gaussian random process whose statistics are approximately constant during the length of a signal pulse. The parameters of the filter are optimized to maximize the output signal-to-noise ratio (SNR). The resulting nonlinear filter has the interesting property of approximating the performance of an adaptive filter in that it weights each frequency band of each input pulse by a factor that depends on the instantaneous noise power spectrum present at that time. The SNR at the output of the nonlinear filter is compared to that at the output of a matched filter. The relative performance of the nonlinear system is good when the signal pulses have large time-bandwidth products and the instantaneous noise power spectrum is colored in the signal pass band.     

Spectral Analysis and Subtraction of Noise in Radar Signals

A new method of maximum entropy spectral estimation called the revised maximum entropy method (MEM) is formulated and is applied to the spectral analysis of the echo signals from atmospheric turbulence observed by an incoherent scatter radar. The revised MEM is shown free from many demerits of the other methods for spectral analysis. Further it makes it possible to subtract the white noise usually contained in the data during the processing. Some examples of spectral estimation are shown for the actual radar signals and the simulated data. Another application of the revised MEM is the subtraction of the clutter component which is difficult to do by linear filtering. The method is successfully applied to several data abounding with the clutter to obtain the spectra of the echo signals with less clutter distortion.     

不同飞行状态下施翼与大气湍流的干扰噪声

本文简述了一种直升机旋翼与大气湍流入流相干扰产生的噪声预估方法。这一方法考虑了桨叶上非定常载荷的弦向及展向非紧致性，桨叶－桨叶载荷之间的相关，通过结合大气湍流能量谱模型与快速畸变湍流收缩模型来确定旋翼平面处非均匀、各向异性湍流场的特性，使得这种方法可用于直升机在真实飞行状态下的旋翼与湍流场干扰噪声计算。利用文献中模型旋翼试验的结果，验证了本方法的可行性，并计算了某型直升机在六种飞行状态下的流场畸变情况及旋翼与湍流干扰的远场噪声谱，结果表明：在准悬停及低速爬升状态，湍流场的畸变较大，而在中、快速前飞状态，湍流场的畸变最小，在低速爬升状态，线性总声压级最小。     

Ideal Limiting of Periodic Signals in Random Noise

A method based on Hermite polynomials is developed for analysis of the output resulting from passing Fourier expandable signals and noise through general zero-memory devices. New results are developed for the output time and autocorrelation functions. Special results are generated for an ideal clipper. Techniques for obtaining results for practical cases are discussed. The method itself can be modified and applied to non-Gaussian noise and general nonlinear devices with nondeterministic signals.     

航空发动机测试信号噪声特性分析

在采集到的航空发动机测试信号中不可避免地混有噪声或干扰信号,讨论了利用频谱分析、滤波、小波分解、双谱估计、以及自相关分析等提取发动机信号噪声的方法,分析了发动机信号噪声的类型和特性。结果表明:发动机噪声主要是加性、低强度的连续频谱,在某几个频率成分上也分布着线状频谱。噪声中既有白噪声、又有非平稳的入侵色噪声。      

The Nonparametric Detection of Signals Embedded in Log-Normal Noise

The nonparametric detection of signals embedded in log-normal noise is discussed. The generalized sign (GS), Mann-Whitney (MW), modified Savage (MS), and modified rank squared (MRS) non-parametic detectors are considered and are compared with the mean and trimmed mean (TM) detectors when envelope detection is used. The detection of both nonfluctuating and Rayleigh fluctuating signals is considered.     

An Alternate Approach to the Prediction of Polynomial Signals in Noise from Discrete Data

When the problem of predicting the past, present, or future value of a polynomial signal or any of its derivatives is considered, where the signal is in white Gaussian noise, the standard approach has been to minimize mean-square-error with constraints by use of Lagrange multipliers. In this paper an alternate approach is described, using results of Rao and Bhattacharyya from the statistical literature, which reduce the specified prediction problem to a simple one requiring no formal minimizations and no use of Lagrange multipliers. It further has the advantage of yielding the covariances between estimates of the polynomial and its derivates. Useful engineering formulas for smoothing and prediction are developed in the main part of the paper. These include both filter and covariance expressions. A tutorial discussion of the theory is given in two appendixes.     

识别信号对尾流激励的叶片气动力Volterra 降阶模型的影响

针对涉及动、静叶干涉的叶片气动弹性振动问题,基于Volterra级数方法,建立了尾流激励的叶片气动力降阶模型,分析了稳态条件和识别信号幅值对气动力降阶模型辨识精度的影响。结果表明:所建立的气动力降阶模型能够正确表征尾流对叶片的激励作用,不同流场稳态条件和阶跃信号幅值下气动力降阶模型的结果基本相同。     

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。     

Sonar Array Detection of Gaussian Signals in Gaussian Noise of Unknown Power

A statistical test is postulated for detecting, with an M-element hydrophone array, a Gaussian signal in spatially independent Gaussian noise of unknown power. The test is an extension of the uniformly-most-powerful (UMP) unbiased test for a two-element array. The output signal-to-noise ratio of the test is calculated and, for a large number of independent space-time samples, is shown to be no better than a mean-level detector (MLD). Receiver operating characteristic curves (ROC) for the MLD are computed and compared to the ROC curves for the optimum (Bayes) parametric detector. The input signal-to-noise power ratios required to provide a detection probability of 0.5 differ by less than 0.2 dB for a fifty-element array with wide variation in false-alarm probability and time-bandwidth product. This result suggests that both the extended bivariate UMP unbiased test and the MLD perform close to the unknown UMP unbiased test for independence of a multivariate Gaussian distribution.     

噪声调制连续波雷达信号波形射频隐身特性

雷达信号波形的射频(RF)隐身性能是雷达系统能否适应现代战场环境的重要因素,雷达射频隐身信号波形设计是现代雷达系统设计中的重要课题.首先,在介绍随机噪声信号雷达原理的基础上,基于Schleher截获因子阐述了噪声调制连续波雷达信号波形的射频隐身特性.然后,分析了高斯噪声相位和频率调制连续波雷达输出自相关函数和高斯噪声相...     

Optimum Linear Estimation of Stochastic Signals in the Presence of Multiplicative Noise

This paper considers optimum (MMSE) linear recursive estimation of stochastic signals in the presence of multiplicative noise in addition to measurement noise. Often problems associated with phenomena such as fading or reflection of the transmitted signal at an ionospheric layer, and also situations involving sampling, gating, or amplitude modulation, can be cast into such formulation. The different kinds of estimation problems treated include one-stage prediction, filtering, and smoothing. Algorithms are presented for discrete time as well as for continuous time estimation.     

Error Probability for Fading CPSK Signals in Gaussian and Impulsive Atmospheric Noise Environments

Recently the performance of digital communication systems in the presence of impulsive atmospheric noise has been evaluated assuming a noise model which is in excellent agreement with experimental results. We evaluate the bit error probability for coherent phase-shift keying (CPSK) signaling assuming the same atmospheric noise model but considering a more reasonable representation of the communication channel which accounts for the simultaneous presence of Gaussian (always present) atmospheric noise and signal fading.     

Spectral Location of Rayleigh and "m" Fading Signals in White Gaussian Noise

The classical problem is considered of locating a fading sinusoidal signal known to be present in one of several frequency " cells," each of which contains additive white Gaussian noise. The signal fading is assumed to follow the popular Rayleigh distribution, but generalizations tions to non-Rayleigh fading are included in terms of the " in" distribution due to Nakagami. The channel observation time is allowed to be either predetermined or variable (corresponding, respectively, to " fixed sample size" and " sequential" reception), and the practically important situation of intermittent signal transmissions is also examined. Results are in the form of optimal and near-optimal receiver structures, and of measures of performance.     

时频域滤波方法及其在颤振信号处理中的应用

采用自适应时频分析方法并通过理论分析和数字仿真完成了相应的数值特性与应用特性研究。根据颠振试验的原理和观测信号特点，将所提出的两种时频域滤波算法引入到了飞机结构亚临界响应分析的颠振边界预测研究当中，即通过联合时频分析(JTFA)与时频域滤波提取有效信号再进行模态参数提取与颠振边界预测，取得了预期的效果。