Detectability of signals in Laplace noise

Closed-form expressions for the false-alarm and detection probabilities attained by the optimum and the linear detectors of a positive signal in n independent samples of noise having a bilateral exponential or Laplace distribution require lengthy computation when n is large, and those for the optimum detector suffer from round-off error because their terms alternate in sign. It is shown how the method of saddlepoint integration can be conveniently applied to compute these probabilities, and numerical comparisons of the accuracies of the methods are presented. The relative efficiency of the two detectors is calculated as a function of n and found to approach the asymptotic value of 2 very slowly     

Coherent detection in Laplace noise

The discrete-time detection of a time-varying, additive signal in independent Laplace noise is considered. Previous efforts in this area have been restricted to the constant signal, and identically distributed noise case. Theoretical (closed form) expressions for the false alarm and detection probabilities are developed for both the Neyman-Pearson optimal detector and the classical matched filter detector. Comparisons between the two detectors are made which illustrate the effects of signal-to-noise power ratio and sample size for certain false alarm and detection probability constraints. In view of the fact that the optimal Laplace detector is not UMP, we also investigate the effect of signal amplitude mismatch     

Likelihood-ratio detection of frequency-hopped signals

The optimum system for intercepting frequency-hopped signals uses a channelized receiver and a likelihood-ratio test (LRT). Previous results on the performance of the optimum system have been based on Gaussian assumptions, which are generally valid for transmissions having large time-bandwidth areas. Results, obtained by Monte Carlo simulation, for relatively small time-bandwidth transmissions are given here. The signal model is a simple one known as “pure frequency hopping.” Comparisons with the LRT show that energy detection loss increases when the time-bandwidth product of the transmission is increased by increasing the number of frequencies, even when the number of pulses is also increased. The loss decreases when only the number of pulses is increased. Over the parameter range observed, binary detection loss tends to increase with the number of pulses and decrease with the number of frequencies. Results are included for a moving-window version of the LRT. A parameter of the LRT is the signal-to-noise ratio (SNR). The effect of using a design value not equal to the true SNR is shown     

Estimating the number of signals using reference noise samples

Criteria for estimating the number of signals in the case of small-sample populations are considered. The criteria introduced by M. Wax and T. Kailath (1985) do not work well in this case. Two new criteria based on information theoretic and eigenmode composition-based criteria are proposed, assuming a known noise covariance. Simulation results show a significant improvement in the performance of estimating the number of signals in the small-sample case, by the use of the new criteria combined with an estimate of the noise covariance obtained from reference noise samples     

Robust detection of small stochastic signals

We consider the problem of detecting a stochastic signal in white not-necessarily-Gaussian noise, using vector valued observations. The locally optimal detector is presented and its performance evaluated. The least-favorable signal spectrum and noise density (over specified classes) are found, and it is shown that the detector using these least-favorable assumptions is minimax robust. The class of spectra is that of any stochastic signal of specified power whose spectrum can be bounded from above and from below by two given positive functions. The class of densities is the ε-contamination model. We present examples of the performance achievable with the robust detector in one of these the spectral uncertainty class corresponds to the unknown Doppler shift of a radar return signal. It is demonstrated that the standard matched-filter's performance degradation with increasing Doppler shift can be avoided almost entirely through use of the robust processor     

Minimax detection for signals with unknown parameters

Minimax detectors are often used for the detection of signals with unknown parameters in additive white Gaussian noise. Several minimax strategies are discussed for both real and complex signals, including one based on the least favorable distribution of the unknown parameters and a second, distribution-free method based on the worst case parameter values. Also discussed are the relationships between these minimax detectors and equal correlation filters for real signals and equal deflection quadratic detectors for complex signals. Conditions are given under which the two different minimax strategies produce identical detectors     

Coiflet wavelet transform applied to inspect power systemdisturbance-generated signals

An application of Coiflet wavelet transform for the study of power system disturbance-generated signals is proposed. Because the wavelet transform possesses the time-frequency localization characteristics, the time and frequency information of a waveform can be integrally presented. Therefore, this approach can be more efficient in monitoring time-varying disturbances when compared with those Fourier transform-based methods. Moreover, when compared with the Morlet wavelet transform, the merits of easier implementation presented by Coiflet transform method as a discrete form further solidify the practicality for electric power quality applications. This approach has been validated through various test scenarios, including oscillatory transients, voltage sag, voltage swell, momentary interruption, and flat-top. Test results demonstrated the feasibility of the method for the applications considered     

Performance of an adaptive detection algorithm; rejection ofunwanted signals

The analysis of an adaptive detection algorithm described previously by the author (1985, 1986) is extended. Previously, the performance was evaluated for the case of a signal corresponding exactly to the steering vector used in the derivation of the algorithm. Here the performance for signals arriving from other directions is evaluated. It is shown that these signals are rejected much more strongly than would be suggested by the sidelobe levels of the adapted patterns themselves     

Distributed target detection in compound-Gaussian noise with Rao and Wald tests

The problem of detecting distributed targets in compound-Gaussian noise with unknown statistics is considered. At the design stage, in order to cope with the a priori uncertainty, we model noise returns as Gaussian vectors with the same structure of the covariance matrix, but possibly different power levels. We also assume that a set of secondary data, free of signal components, is available to estimate the covariance matrix of the disturbance. Since no uniformly most powerful test exists for the problem at hand we devise and assess two detection strategies based on the Rao test, and the Wald test respectively. Remarkably these detectors ensure the constant false alarm rate property with respect to both the structure of the covariance matrix as well as the power levels. Moreover, the performance assessment, conducted also in comparison with the generalized likelihood ratio test based receiver, shows that the Wald test outperforms the others and is very effective in scenarios of practical interest for radar systems.     

美国深空网的无线电跟踪测量新技术

本文介绍了美国航空航天局所属深空网(DSN)在无线电跟踪测量方面已采用的新技术的应用情况,探讨了这些技术对于我国发展深空导航技术的实际意义。     

面向电容式微机电加速度计的接口噪声分析和数字闭环技术研究

优化电容检测接口并采用力反馈控制方案能够在不影响表头敏感结构的情况下,通过改变环路参数提高加速度计的信噪比,改善加速度计性能。基于一款阵列式差分电容的加速度计敏感结构,在等效电容模型的基础上,通过电容检测接口电路的搭建与输出信号的频谱分析,验证了单载波电容检测电路具有更出色的输出信噪比。后级采用STM32H743VIT6微处理器实现调幅信号的数字解调,经PI控制算法调节后作为反馈电压施加于可动极板,实现了加速度计的数字闭环控制。实测结果显示,闭环状态下加速度计的速度随机游走（VRW）为57 μg/Hz1/2,与开环状态相当,而零偏稳定性则从开环状态的184 μg改善至58 μg,验证了单载波调制型电容检测接口和力反馈控制技术对提升加速度计静态性能的具体效果。     

Improving EGT sensing data anomaly detection of aircraft auxiliary power unit

The reliability of the on-wing aircraft Auxiliary Power Unit (APU) decides the cost and the comfort of flight to a large degree. The most important function of APU is to help start main engines by providing compressed air. Especially on the condition of sudden shutdown in the air, APU can offer additional thrust for landing. Therefore, its condition monitoring has drawn much attention from the academic and industrial field. Among the on-wing sensing data which can reflect its condition, Exhaust Gas Temperature (EGT) is one of the most important parameters. To ensure the reliability of EGT, one kind of data-driven anomaly detection framework for EGT sensing data is proposed based on the Gaussian Process Regression and Kernel Principal Component Analysis. The situations of one-dimensional and two-dimensional input data for EGT anomaly detection are considered, respectively. The cross-validation experiments are carried out by utilizing the real condition data of APU, which are provided by China Southern Airlines Company Limited Shenyang Maintenance Base. The anomalous stuck condition of EGT sensing data is also detected. Experimental results show that the proposed EGT sensing data anomaly detection method can achieve better performance of false positive ratio, false negative ratio and accuracy.     

Monopulse-radar angle tracking in noise or noise jamming

In many monopulse radars, feedback in the angle-tracking servo system is taken to be directly proportional to the monopulse ratio. In those radars, monopulse measurements are conditioned on simultaneous occurrences of receiver sum-channel video exceeding a detection threshold: if a detection fails to occur, the measurement is ignored, and the angle-tracking servo is made to coast. Such conditioning is shown to be necessary in order that the noise power be finite in the servo feedback. The conditional mean value and conditional variance of the monopulse ratio are derived and quantified in terms of threshold level as well as signal-to-noise ratio. The formulation permits the noise covariance between receiver difference and sum channels to be complex rather than only real-valued, so that the sources of noise jamming are not required to be positioned in the receiving-antenna mainlobe and to be copolarized with the antenna response there. Nonfluctuating and Rayleigh-fluctuating target cases are considered and compared, and fluctuation loss is quantified     

Radio noise level due to electric power lines and its relation to line design parameters

The main results of radio noise measurements taken in Poland for 220 and 400 kV power lines are presented. The influence of various line parameters, such as conductor diameter and number, phase spacing, and height of conductor above ground on the radio noise level for power lines is discussed. The basic philosophy of choosing the line parameters and route at the design stage in Poland is described taking into account radio noise levels, electrical field gradients, and corona losses.     

基于相控麦克风阵列的民机主起落架气动噪声源识别技术研究

起落架气动噪声是民机机体噪声极为重要的组成部分。由于起落架结构外形复杂,同时各部件之间干扰严重,使得其噪声机制十分复杂。目前,相控麦克风阵列技术已经成为识别民机机体噪声声源位置最为常用和可靠的技术手段。结合闭口声学风洞试验数据,采用经典的Beamforming算法,分析对比了民机主起落架构型在不同频率下声源位置分布情况,获得了不同频率下的最大声源位置;采用CLEAN-PSF算法剔除主起舱门位置处的声源,抑制了最大声源旁瓣对其他声源位置遮盖效应。     

A fast arc fault detection method for AC solid state power controllers in MEA

Arc fault detection is desperately required in Solid State Power Controllers (SSPC) in addition to their fundamental functions because arcs will provoke growing harm and threat to aircraft safety. Experimental study has been done to obtain the faulted current data. In order to improve the detection speed and accuracy, two fast arc fault detection methods have been proposed in this paper with the analysis of only half cycle data. Both Fast Fourier Transform (FFT) and Wavelet Packets Decomposition (WPD) have been adopted to distinguish arc fault currents from normal operation currents. Analysis results show that Alternating Current (AC) arcs can be effectively and accurately detected with the proposed half cycle data based methods. Moreover, experimental verification results have also been provided.     

An Application of Radiometric Techniques to Precision Angle Tracking Radar Systems

A new technique is described which provides for precision angle tracking of celestial radio sources with a conventional monopulse antenna receiving system. It is shown that this technique is readily adapted to angle tracking radars. The features of conventional monopulse operation are preserved while permitting precise angle tracking of noise sources when signal to noise ratios are much less than unity. Measurements, using a four-horn monopulse feed with a 28-foot parabolic reflector and a "monopulse radiometer" produced the characteristic monopulse angle detection functions when using the sun, the moon, and Cassiopeia A as boresight reference sources. Precision measurements were made to 8 arc second under varying weather conditions using 28-foot radio astronomy antennas. The accuracy of the measurements were limited by the antenna angle encoders, consequently no conclusions are drawn with regard to the absolute accuracy of the measurements. The celestial coordinates of four discrete radio sources and the equations for coordinate transformation to local elevation and azimuth are contained in the Appendixes.     

DSMC方法中的统计噪声分析

通过对基于颗粒输运随机统计模拟的DSMC方法模拟准则的分析研究,定义了该方法中统计量的噪声、相对统计涨落及置信度。引入概率论中的切比雪夫不等式,利用正态分布平衡流统计理论,推导出DSMC方法模拟流场宏观速度和温度的统计噪声理论公式,并以过渡流区平面Couette剪切流和激波结构内流动为算例进行数值模拟验证与理论分析。结果表明,在一定的置信度下,选择适当的模拟参考值,DSMC统计量的噪声除与样本容量(模拟分子数及统计抽样次数)的平方根成反比例外,速度的相对统计涨落还与流场马赫数成反比,而温度的相对统计涨落与流场宏观参数无关。这为控制DSMC模拟结果的相对统计涨落提供了理论指导和计算依据。     

喷流噪声声源识别与声源机理分析方法进展

喷流噪声是航空气动噪声的主要来源,会造成严重的环境污染和健康威胁。缺乏对湍流涡如何产生 噪声辐射这一物理过程的深刻理解,是难以设计出高精度噪声预测方法和高效降噪装置的根本原因。本文总结公开发表文献中喷流噪声的声源识别与声源机理分析的研究进展和局限。从噪声由湍流脉动产生这一因果 律出发,指出未来研究仍需要对噪声和湍流脉动建立合理的物理模型和控制方程,进行合理的分离,并将噪声 脉动表示为背景湍流的广义函数,从动力学角度揭示非定常湍流涡演化产生噪声辐射的物理机理。