Contiguous pulse binary integration analysis

The probability of detecting m or more pulses contiguously-that is, in a row-from a pulse train of n pulses is determined when the detection of each pulse is an independent Bernoulli trial with probability p. While a general closed-form expression for this probability is not known, we present an analytical procedure that gives the exact expression for the probability of interest for any particular case. We also present simple asymptotic expressions for these probabilities and develop bounds on the probability that the number of pulses that must be observed before m contiguous detections is greater than or less than some particular number. We consider the implications for binary integration in radar and electronic warfare problems     

Photoelectron Counting Statistics and Error Performance of m-Distributed Optical Signal

By the term "m-distributed optical signal" we mean a noise-like optical signal whose envelope (or intensity) fluctuation probability is modeled by Nakagami's "m-distribution." Using the m-distribution which has been widely used as an analytical model of the fading envelope in radio communications, it is shown that one can generally analyze the statistical properties such as the photoelectron count probabilities and error probabilities for the wider class of noise-like optical signals; some numerical results are also given.     

Fade Probabilities: Measures for Predicting Search-Radar Performance

By itself, the cumulative probability of detection has been inadequate for accurate performance prediction of the AN/APQ-159, airborne, F-5 radar. For this reason, quantitative measures of fading of target echoes were formulated. Probabilities of 10-percent fade and of triple miss are defined here, and algorithms, as well as some important general properties, are derived for their efficient computation by machine in terms of the single-scan probabilities of detection. Both probabilities are cumulative quantities, dependent on the total number of independent looks at the target.     

Sliding Window Detection Probabilities

A method is proposed for computing sliding window detection probabilities which have applications in track-while-scan acquisition logic and radar detection theory. The sliding window probability is the probability of achieving m successes out of n consecutive events at least once by the Nth opportunity. Expressions are derived for these probabilities as a function of N and p (the per-event success probability) for 1 ? n ? 4 and m ? n. Tabulated results are presented for the mean and standard deviation of the detection delay associated with each m/n logic.     

Performance of an Ideal Quantum Receiver of a Coherent Signal of Random Phase

An ideal quantum receiver is to detect a coherent narrow-band optical signal in the presence of thermal background radiation. Curves are given both of the average probability of error in a binary communication system transmitting O's (blanks) and 1's (pulses) with equal probabilities, and of the probability of detection for various fixed values of the false-alarm probability.     

Envelope Threshold Detection in a Class of Non-Gaussian Interference

This paper considers the detection of a sinusoidal or chirp signal imbedded in wideband FM interference (as might be generated by some types of active jamming), such that after pulse compression or other integration, the interference can be approximated by a sum of sinusoids of independent phase. The detection probability in such non-Gaussian noise is compared to that for Gaussian noise, with the Gaussian result approached, as required, in the limit that the number of sinusoids in the sum increases without bound. For detection using a comparison of the envelope with a threshold which yields a given false-alarm probability (CFAR detection), the detection probability is improved over the case of Gaussian noise, so that the usual approach basing the design on Gaussian noise would be conservative. Using a threshold determined from the envelope mean, the FM interference yields a lower false-alarm probability than for Gaussian noise, with detection probability only slightly degraded.     

加工误差对压气机叶栅气动性能及稳定性影响的数据挖掘

为缓解加工误差影响评估过程中的"维数灾难",结合展向平均假设和基于高斯过程的Karhunen-Loève展开,提出了一种由法向加工误差导致的三维叶片表面几何不确定性降阶模型.通过给定加工误差分布的标准差函数求解几何不确定性降阶模型,并运用伪蒙特卡洛方法随机生成样本,最终训练人工神经网络预测了加工误差对高负荷直叶栅气动性...     

A Method for Setting a Test Signal Level Relative to Noise

A method is described for adjusting the leval of an RF test signal generator relative to the noise level at the receiver output. The method compares a detected output to a threshold and counts the number of times noise and signal plus noise cross the threshold in a given number of tries. By setting the threshold at a given false alarm probability for noise alone and then adding the test signal and adjusting its level to give a specified detection probability, the signal-to-noise ratio can be calibrated to an accuracy that depends on the number of samples used to measure the probabilities. The false alarm and detection probabilities are given for best accuracy as well as the rms error in signal-to-noise ratio as a function of the number of samples used.     

Blind adaptive decision fusion for distributed detection

We consider the problem of decision fusion in a distributed detection system. In this system, each detector makes a binary decision based on its own observation, and then communicates its binary decision to a fusion center. The objective of the fusion center is to optimally fuse the local decisions in order to minimize the final error probability. To implement such an optimal fusion center, the performance parameters of each detector (i.e., its probabilities of false alarm and missed detection) as well as the a priori probabilities of the hypotheses must be known. However, in practical applications these statistics may be unknown or may vary with time. We develop a recursive algorithm that approximates these unknown values on-line. We then use these approximations to adapt the fusion center. Our algorithm is based on an explicit analytic relation between the unknown probabilities and the joint probabilities of the local decisions. Under the assumption that the local observations are conditionally independent, the estimates given by our algorithm are shown to be asymptotically unbiased and converge to their true values at the rate of O(1/k/sup 1/2/) in the rms error sense, where k is the number of iterations. Simulation results indicate that our algorithm is substantially more reliable than two existing (asymptotically biased) algorithms, and performs at least as well as those algorithms when they work.     

Uncertainty analysis of measured geometric variations in turbine blades and impact on aerodynamic performance

Inevitable geometric variations significantly affect the performance of turbines or even that of entire engines; thus, it is necessary to determine their actual characteristics and accurately estimate their impact on performance. In this study, based on 1781 measured profiles of a typical turbine blade, the statistical characteristics of the geometric variations and the uncertainty impact are analyzed, and some commonly used uncertainty modelling methods based on PrincipalComponent Analysis(PCA)...     

Radiowave Receiving System Intercept Probability Model

A model is presented for estimating the intercept probabilities of radiowave-acquisition receiving systems. The specific architecture of each of the receiving systems is not important, but there must be two or more of them and they must operate in such a manner that for each trial (event) they alarm independently from a statistical point of view. The data giving the number of alarms for each receiver and the number of receivers alarming for each trial is all that is required. These data are used to form estimates of the conditional probabilities of intercept and simultaneous alarm. A least mean square estimator is then used to find the unconditional intercept probabilities.     

Image Correlation with Geometric Distortion Part 1: Acquisition Performance

The degradation in acquisition probability that occurs when cross correlation is used to determine the offset of two images of the same scene that differ by a relative geometric distortion is presented. The geometric distortions considered can be represented by a general affine transformation of image coordinates. The analysis shows that for a given geometric distortion there is an image size and shape that minimizes the probability of false acquisition. The results are derived for images modeled as random patterns with arbitrary auto-correlation functions. The results are illustrated for images with Gaussian autocorrelation functions.     

基于Simulink?的复合衰落信道仿真与分析

基于Simulink平台建立了Rayleigh-Lognormal、Ricean-Lognormal、Nakagami-Lognormal复合衰落信道的仿真模型,这些模型可用于进行单频组网的DRM系统的设计和性能分析。给出了各种复合衰落的概率密度函数、累积分布函数、平均电平交叉率、平均衰落时间的统一表达式。仿真结果验证了理论分析结果的正确性。     

煤油凝胶单液滴燃烧特性试验

利用二氧化碳激光器点火装置及高分辨率高速成像系统,开展了煤油凝胶单液滴在空气中的点火燃烧试验,观察了凝胶液滴在燃烧过程中的形态变化,为进行凝胶冲压发动机的总体设计提供依据。试验结果表明,煤油凝胶液滴的燃烧经历了煤油的蒸发燃烧、气泡产生、胶凝层形成、胶凝层破裂、微爆等物理化学过程,基本满足D²定律。分析了胶凝剂含量、硼含量对含硼煤油凝胶燃烧过程的影响。当硼含量一定时,随着胶凝剂含量的增加,含硼凝胶的稳定燃烧相对时间增加,但微爆过程更加剧烈;当胶凝剂含量一定时,随着硼含量的增加,含硼凝胶液滴的稳定燃烧相对时间缩短,微爆现象更加剧烈。     

考虑几何分散性的涡轮盘寿命概率分析

针对考虑几何分散性的涡轮盘低循环疲劳（LCF）寿命概率分析中几何参数多、几何随机变量难确定、分布特征获取困难、模型需自动更新及计算成本高的问题,提出几何分散性的概率处理方法:采用试验设计方法对涡轮盘结构所有几何参数进行灵敏度分析,筛选出对应力影响较大的关键几何参数作为随机变量,使用K-S(Kolmogorov Smirnov)方法确定其分布类型和特征参数,最后建立代理模型进行Monte Carlo概率分析.基于此方法,开发出了涡轮盘概率分析系统,在该系统中筛选得到某发动机GH720Li涡轮盘内径、外径、盘缘厚度3个结构参数作为几何随机变量,完成对LCF寿命的概率分析工作得到寿命-可靠度分布曲线.分析结果表明涡轮盘外径对LCF寿命有较大影响.      

气流激励下叶片的高周疲劳概率寿命预估

航空发动机中叶片振动引起的高循环疲劳失效是尤为突出的问题,将概率方法引入叶片高周疲劳寿命预估是叶片高周疲劳问题研究的重要途径。建立了叶片系统的概率疲劳积累损伤模型,由求得的振动应力出发,提出了一套完整的气流激励下叶片高周疲劳概率寿命的预估方法,分析中可以量化各种不确定因素对振动应力和疲劳寿命的影响,包括模态特征的不确定性和激励特征的不确定性。结合具体工程算例,分析得到某小型发动机二级静叶在工作转速下随工作时间增长的概率疲劳积累损伤,并给出了对应的工作可靠性。     

Cochannel Interference in Partially Coherent Communication

Effects of cochannel interference and synchronization error of the carrier phase on the probability of error in binary communications are considered. Several bounds on the probability of error are proposed. The bounds are easy to compute and do not require complete statistical characterization of the errors. They turn out to be simple linear combinations of error probabilities with no cochannel interferences and no phase errors. Several illustrative examples are given which show that the bounds can be tight.     

A method for estimating parameters of K-distributed clutter

A method for estimating the parameters of K-distributed clutter when the available sample size of the data is limited is proposed. In this method, the arithmetic mean and geometric mean of the given data are used to estimate the model parameters. Expressions characterizing the performance of the proposed estimator are presented, along with some simulation results. For spiky clutter, simulations show that parameter estimates obtained from the arithmetic and geometric mean are approximately equal to the numerically evaluated maximum-likelihood (ML) estimates. The method is also used to estimate the parameter of the Weibull density     

Causal probabilistic model for evaluating future transoceanicairline separations

With the advent of automatic dependent surveillance (ADS), a detailed probability model of aircraft cross-track deviations is required to determine the impact of ADS. A suitable causal probability model is presented where normal navigation, degradation, pilot blunder, and failure are each modeled by Gaussian density functions with mean and standard deviations defined by the physics of the event. The overall model is a weighted sum of the Gaussian error probabilities and is thus amenable to extrapolation. Overlap and encroachment probabilities are derived,and the effect of ADS on this is model determined. It is shown that by using a simple form of ADS separation standards can be reduced, and transmitting a figure of merit (FOM) providing information on failures and degradations can further reduce separation standards. The results suggest an improvement by a factor of two from current separation standards     

无人机双机编队攻击作战效能评估

针对无人机双机编队任务协同/非协同攻击作战情况,运用概率论及搜索理论,建立了目标搜索、识别、攻击作战的效能评估数学模型,在此数学模型基础上分析了任务协同和非协同条件下的攻击任务成功率及影响因素,结果得出双机协同、非协同在不同作战情况下有着各自的优势。分析结果对实际作战安排做出了指导性原则,对提高无人机集群作战效能具有实际意义。