末制导雷达虚警概率检验方法

针对只有10^-8～10^-9量级的末制导雷达虚警概率难以检验的问题,研究虚警概率与发现概率、虚警时间的关系,论证了将虚警概率转化为虚警时间的检验方法,利用定时截尾统计检验理论,研究了不同鉴别比、不同试验时间、不同接收故障数时研制方与使用方的风险,提出了新型末制导雷达虚警概率的检验方法,解决了该项指标检验的难题。     

基于时间应力分析的机内测试系统综合降虚警技术

 虚警率高是困扰机内测试（BIT）系统得到广泛应用的主要原因。针对该问题,从机电系统所承受时间应力的角度构建了机内测试系统综合降低虚警技术的总体模型。首先采用双支持向量机（SVM）的方法将实时应力信息与机内测试诊断结果相互关联。在此基础上,提出了基于核主元模糊聚类的虚警识别方法将机电系统多源信息进行综合分析,并通过优化决策实现多级降低机内测试系统虚警的目的。最后,针对某型直升机航空地平仪的机内测试系统进行了试验验证与分析。     

False Alarm Rate and False Alarm Number for Discrete and Continuous Time Sampling

A comparison of the false alarm rates and false alarm numbers for discrete and continuous time sampling is given for different noise spectrums (rectangular, Hamming, Gaussian, and cosine noise voltage spectrums) and for different sampling rates for the case of discrete time sampling. Also given is the increase in the false alarm rate when going from discrete to continuous time sampling when the detection threshold is held fixed. The amount that the threshold has to be increased for continuous sampling to achieve the same false alarm rate obtained with discrete time sampling is also given.     

机内测试虚警分析和控制

现代飞行器广泛采用机内测试(Built-intest,BIT)技术,以便对其内部故障进行自动检测、诊断和隔离,但是常规BIT面临诊断能力不足和诊断模糊性等问题,导致BIT虚警率高,难以有效发挥其应有的作用.本文论述了BIT虚警的基本理论、虚警的危害及现状,并从BIT虚警产生的原因分析入手,提出了解决虚警问题的一些方法和措施.     

基于正交小波变换的目标检测方法

理论分析表明,独立高斯噪声经过正交小波变换后保持方差和独立性不变。基于Mallat的小波多分辨分析,通过对小波系数进行平方律处理,建立了基于正交小波变换的恒虚警率检测器模型,推导了相应的虚警和检测概率公式,分析了噪声未知情况下小波系数序列长度对检测性能的影响,并给出了合适的长度值。实验结果表明,所提出的检测器能满足不同虚警概率和杂波背景的要求,具有较好自适应性。     

基于改进归纳式监控算法的液体火箭发动机实时故障检测

对归纳式监控算法（IMS）应用于故障检测时虚警率高的问题,提出一种改进IMS.改进后的算法对测试时可能出现的野点进行了处理,降低了待测数据中野点对测试结果的干扰.以某型液体火箭发动机仿真试车数据为例,进行了使用IMS的实时故障检测实验.结果表明,原始IMS在进行故障检测时会出现多次虚警,改进后的IMS在实时准确的同时,虚警率大大降低,由37.5%降低至0,达到液体火箭发动机故障检测程序的要求.      

Clutter Map CFAR Analysis

An analysis of the probability of target detection for a clutter map CFAR using digital exponential filtering has been performed. General performance equations are derived. The probability of detection versus signal-to-noise ratio is plotted for a false alarm probability of 1.E-06 for several weight values. The CFAR loss is plotted for a detection probability of 0.9 and false alarm probabilities of 1.E-06 and 1.E-08.     

On the false alarm probability for an overlapped FFT processor

A standard processor for detecting narrowband signals in noise applies the fast Fourier transform (FFT) to overlapped data blocks, and then sums the squared magnitudes of the bins from successive FFTs. The overlap of the data blocks causes these bins to be correlated, even when the noise is white. A simple expression is derived for the probability of false alarm when the covariance matrix of the FFT bins is tridiagonal     

一种限定虚警概率的PN码捕获自适应门限估计算法

提出了一种限定虚警概率的PN码捕获的自适应门限估计算法,首先在对判决变量的统计特性分析的基础上,计算出了判决门限的有偏估计量;然后分析了估计偏差对捕获系统检测概率和虚警概率的影响;最后,计算机仿真表明,在限定虚警概率的前提下,捕获系统在高斯白噪声信道和瑞利衰落信道下具有较高的检测概率,自适应门限的估计方法易于实现,且适合工程应用。     

CFAR integration processors in randomly arriving impulseinterference

Time diversity transmission is often used to circumvent the high probability of a deep fade on a single transmission which may result in loss of the signal. One way to combat deep fades is to postdetection integrate the received observations from each range resolution cell. The false alarm rate of the postdetection integrator (PI) is extremely sensitive to randomly arriving impulse interference. Such interfering pulses may be unintentionally generated by nearby radars or intentionally generated by pulse jammers seeking to destroy the visibility of the radar. The binary integrator (PI) which uses an M-out-of-L decision rule is insensitive to at most M-1 interfering pulses. We consider the adaptive implementation of the PI and BI detectors for constant false alarm rate (CFAR) operation. We show that the CFAR BI detector when the “AND” (L-out-of-L) decision rule is used exhibits more robust false alarm control properties in the presence of impulse interference at the expense of severe detection loss when no interference is present. The CFAR adaptive PI (API) detector is proposed to alleviate this problem. The CFAR API detector implements an adaptive censoring algorithm which determines and censors with high probability the interference samples thereby achieving robust false alarm control in the presence of interference and optimum detection performance in the absence of interference     

一种模糊飞行冲突实时检测方法研究

为了解决飞行冲突检测中虚警和漏警问题，提出飞机之间的模糊空间接近度概念以及一种模糊冲突检测方法。该方法通过实时计算飞机对之间垂直接近度与水平接近度，并使用模糊推理规则来判断飞机当前相对接近趋势以及是否存在冲突。仿真实验表明：该冲突检测方法能有效减少飞行冲突的虚警和漏警。     

Adaptive False Alarmrm Regulation in Double Threshold Radar Detection

In practical situations the false alarm probability in double threshold radar detection, sometimes known as binary integration with sliding window detection, is dependent on the nonstationarity and azimuthal correlation of the clutter which is present. Control of the false alarm probability can be achieved, to a certain extent, by the adjustment of the second threshold in the detection process. In this study two adaptive control techniques which are based on the statistical characteristics of the data are compared. Comparing the results for a technique based on first-order statistics with one based on second-order statistics, it is shown that the second-order, or correlation sensitive, technique can give a reduction of 30 to 45 percent in the false alarm probability with no corresponding loss in the detection probability. An interesting aspect of the results is the fact that the effects of the size of the sample area and the bias in the correlation estimator are clearly evident.     

Performance analysis of a dynamic programming track before detectalgorithm

We analyze a dynamic programming (DP)-based track before detect (TBD) algorithm. By using extreme value theory we obtain explicit expressions for various performance measures of the algorithm such as probability of detection and false alarm. Our analysis has two advantages. First the unrealistic Gaussian and independence assumptions used in previous works are not required. Second, the probability of detection and false alarm curves obtained fit computer simulated performance results significantly more accurately than previously proposed analyses of the TBD algorithm     

CFAR behavior of adaptive detectors: an experimental analysis

We conduct an experimental analysis for assessing the constant false alarm rate (CFAR) behavior of four coherent adaptive radar detectors in the presence of experimentally measured clutter data. To this end we exploit several data files containing both land, lake, and mixed land and sea clutter, collected by two radar systems (the MIT Lincoln Laboratory Phase-One radar and the McMaster IPIX radar) at different polarizations, range resolutions, and frequency bands. The results show that all the receivers, in the presence of real data, don't respect their nominal probability of false alarm (P/sub fa/), namely they exhibit a false alarm rate higher than the value preassigned at the design stage. Nevertheless one of them, the recursive persymmetric adaptive normalized matched filter (RP-ANMF) is very robust, in the sense that it presents an acceptable displacement from the nominal P/sub fa/, in correspondence of all the analyzed scenarios.     

一种多源组合定位系统中信息质量评估方法

多源组合定位系统可有效提高定位精度及定位鲁棒性。但更多的信息源提高了引入低质量信号的可能性,从而影响组合系统的定位性能。针对该问题,提出了一种多源组合定位系统中信息质量评估方法。在单系统信息质量评估的基础上,分析了其虚警率与漏警率,发现了二者的影响因素,利用多系统拥有更多冗余信息的特点,通过一致性检验,实现了多源组合导航系统的信息质量评估。仿真实验结果表明,该方法可以同时降低信息质量评估的虚警率与漏警率,且随着组合定位系统数量的增大,虚警率与漏警率呈持续下降趋势,拥有较好的信息质量评估效果。     

Two color temporally correlated infrared background measurements

The use of high speed multicolor imaging sensors provides a valuable tool for characterizing both the infrared signatures of missiles as well as clutter. Over 14 flight hours worth of collections were made of difficult to characterize clutter. This additional data can be utilized to develop and improve missile warning algorithms for better false alarm rates. These analyses show that although a two color staring system could have multiple advantages over a single color system in false alarm rejection, the clutter rejection capabilities can be limited by the relatively low inter-band correlations between the red and blue bands     

Detection of random signals via spectrum matching

Using a priori knowledge of the signal power spectral density (PSD), a spectrum matching approach which effectively utilizes the available signal spectral shape is developed for random signal detection. Two spectrum matching detector (SMD) structures, which are implemented by correlogram and periodogram, respectively, are examined. Theoretical calculation of their false alarm rates is derived and confirmed by simulations. It is also demonstrated that the proposed detectors outperform the standard periodogram, Bartlett method, and energy detector under constant false alarm rate (CFAR) condition for two different random signals.     

Matched subspace CFAR detection of hovering helicopters

A constant false alarm rate (CFAR) strategy for detecting a Gaussian distributed random signal against correlated non-Gaussian clutter is developed. The proposed algorithm is based on Scharf's matched subspace detector (MSD) and has the CFAR property with respect to the clutter amplitude probability density function (apdf), provided that the clutter distribution belongs to the compound-Gaussian family and the clutter covariance matrix is known to within a scale factor. Analytical expressions of false alarm and detection probabilities are derived. An application to the problem of detecting hovering helicopters against vegetated ground clutter is reported     

Parallel Distributed CFAR Detection Optimization Based on Genetic Algorithm with Interval Encoding

Aiming at parallel distributed constant false alarm rate (CFAR) detection employing K/N fusion rule, an optimization algorithm based on the genetic algorithm with interval encoding is proposed. N-1 local probabilities of false alarm are selected as optimization variables. And the encoding intervals for local false alarm probabilities are sequentially designed by the person-by-person optimization technique according to the constraints. By turning constrained optimization to unconstrained optimization, the problem of increasing iteration times due to the punishment technique frequently adopted in the genetic algorithm is thus overcome. Then this optimization scheme is applied to spacebased synthetic aperture radar (SAR) multi-angle collaborative detection, in which the nominal factor for each local detector is determined. The scheme is verified with simulations of cases including two, three and four independent SAR systems. Besides, detection performances with varying K and N are compared and analyzed.