Fluctuating Target Detection in Clutter Using Sidelobe Blanking Logic

In an earlier paper, Maisel [6] considered two-channel detection systems using a sidelobe blanking logic when a nonfluctuating target was present. This paper is an extension of the earlier work to include fluctuating targets. The Swerling I, II, III, and IV models are considered when single-pulse detection is of interest. An adaptive threshold procedure is also briefly discussed whereby the probability of false alarm at any given resolution cell is maintained constant, even though the input clutter level may vary from cell to cell or from beam position to beam position. Useful data are presented for detection probabilities in the range 0.5 to 0.9, for false alarm probabilities in the range 104 to 10-8, and for a false detection probability of 0.1 for a sidelobe target yielding an apparent signal to total noise power density ratio of 13.0 dB in the main beam receiver.     

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     

基于滑窗检测的机载设备故障诊断仿真系统

根据机载设备故障诊断的需求,结合飞机性能监控系统的结构框架和机载设备的特点,提出基于快速存取记录器（QAR）记录的飞行数据和滑窗检测原理的机载设备故障诊断算法,并实现相应的机栽设备故障诊断仿真系统。在简述QAR数据译码与数据选择方法的基础上,论述了滑窗检测的原理并对其性能进行分析：设计实现了基于QAR的机载设备故障诊断仿真系统并给出仿真结果。结果表明,该系统可以有效诊断存在的故障,并能大大降低虚警概率,对保障飞行安全具有重要意义。     

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.     

基于傅立叶变换和模糊逻辑的APC/PIO探测方法

为了对飞机-驾驶员耦合(APC)或驾驶员诱发振荡(PIO)现象实现在线探测,提出了适于实时计算的滑动窗口傅立叶变换递推算法、相关特征的模糊隶属函数以及基于模糊逻辑的识别模型。各种情况飞行试验数据的计算和分析表明,该方法对探测APC/PIO是有效、可行的。最后提出了进一步研究的若干建议。     

On the Effective Single Trial Probability of Success

Define the cumulative probability Pn of occurence of some event as the probability that it occurs at least once in n trials. If the single trial probabilities are not fixed, but are drawn from a distribution of their own, or are dependent on some other nonfixed variable, then it would be convenient to have an ?effective single trial probability (esp)? for use in the simple Bernoulli model which would give the same cumulative probability of occurence as actually observed. We show here that the esp can be interpreted as a kind of average, and that its value is given by 1 minus the geometric mean of 1-d(p), where d(p) is the probability density function of the single trial probabilities, the p's. We further define this geometric mean for both discrete and continuous distributions and evaluate the esp for several cases. These results are compared with earlier ones which suggest that the esp is given by the (arithmetic) average or expectation of the single trial probabilities, and we determine under what conditions this simpler result can be used.     

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.     

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.     

Comparison of Two Scanning Radar Detectors: The Moving Window and the Feedback Integrator

A comparison is made between the moving window and feedback integrator detectors for a scanning radar. Detection probabilities and position estimates are calculated by using a Monte Carlo simulation. The moving window is a slightly better detector than the feedback integrator: it provides 0.5-dB better detection capability and 8 percent more accurate estimate of position. However, the feedback integrator can be implemented more easily.     

The Detection Performance of a Modified Moving Window Detector

The modified moving window detector for binary integration has a shorter window length compared with the ordinary moving window detector because of the addition of a third threshold. When the second threshold is reached, a counter begins to count until the third threshold is reached. A graphical method using a probability chain is developed here to analyze and to calculate the detection performance of this type detector. The detection performances for some practical cases are calculated by computer and are compared with the ordinary moving window detector.     

A CFAR Design for a Window Spanning Two Clutter Fields

When the heterogeneous clutter field spanning the spatial sampling sliding window can be modeled as two contiguous homogeneous clutter fields with the statistical parameters of each field unknown and independent from field to field and with the transition point between fields also not known, then the cell-averaging constant false alarm rate (CFAR) performance significantly degrades, yielding target masking effects and loss of false alarm regulation. For the same defined and encountered environment spanning the sliding window, the performance degradation effects are shown to be largely eliminated when a newly developed class of CFAR tests is employed. These tests are designated as heterogeneous clutter estimating CFARs (HCE-CFAR). The test initially involves the combined use of multiple hypothesis testing and maximum likelihood estimation procedures to estimate the statistical parameters of each of the two fields, and the transition point between them, and then makes use of the relevant estimated clutter field parameters to effect the final decision rule. HCE-CFAR designs are presented for both the cases when the contiguous fields have Rayleigh first-order probability distributions, and log-normal probability distribution. However, the focus of the development and the conducted performance evaluation is for the Rayleigh clutter cases.     

Computation of binary integration detection probabilities

Efficient algorithms are described for computing the probability of detection for a binary integration when the probability of a threshold crossing changes from sample to sample. A binary integrator is exceeded (a hit occurs) in a sequence of N trials and declares a detection if the number of hits is at least as large as some number M, where O>     

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.     

Polygonal Detection Thresholds for In-Phase and Quadrature Channels

A joint detection threshold corresponding to a circle around the origin of the in-phase and quadrature components of a radar IF process is equivalent to envelope thresholding. Square and octagonal approximations to the circle are evaluated for prescribed false-alarm probabilities and the variation of detection probability with signal phase.     

GA—HCM混合聚类算法及其在液体火箭发动机故障检测中的应用

针对HCM聚类算法对初始值和学习参数具有较强依赖性的缺点，提出了GA－HCM混合聚类算法。应用改进的基因算法为HCM算法选取初始种子解，使滑动数据窗上的聚类算法以功能层次分明的“导师一学生”制智能结构出现，从而实现了“精”与“初”相结合的解空间搜索算法，使HCM聚类算法能较快收敛到问题的最优解。同时针对液体火箭发动机系统动力学的特殊性，利用我们提出的一种适用于离线或在线系统故障检测与诊断的算法框架，基于实际试车数据对GA－HCM混合聚类算法进行了准实时的数字仿真。仿真结果表明该算法基本上克服了HCM算法的缺点，能有效地用于液体火箭发动机的事后故障分析或在线故障诊断。该故障诊断框架能区分干扰噪声、永久性故障或间歇性故障所引起的异常数据现象，并能形成当前系统的故障特征模式。对缓变故障的早期检测能力使该算法框架极富应用前景。     

Models for Radar Scatterer Density in Terrain Images

Statistical models for the density of strong scatterers detected in high resolution radar images of rural terrain are presented. The probability distribution of the density of these natural terrain detections was found to be negative binomial. The variance of the negative binomial depended strongly on the window size used to measure the density. This dependence indicates that these detections, like those of a Poisson process, are locally uncorrelated, but have a slowly varying mean density whose correlation distance is 1 km or more. Negative binomial parameters were computed using over 200 km2 of terrain image for densities measured using windows sized from 75 m × 75 m to 375 m × 375 m. Average terrain detection densities of 10-3 and 10-4 per resolution cell were evaluated on images with resolutions of 7 and 28 ft.     

Detection Performance of a Mean-Level Threshold

The problem of detecting signals in nonstationary clutter is met by presenting a mean-level or adaptive threshold which adjusts to the changing background level. Such a threshold performs better than a fixed threshold that must be set for the highest amplitude clutter. However, the mean-level threshold does not perform as well for stationary noise as a fixed threshold set at the proper value. One measure of effectiveness of an adaptive threshold is its performance in stationary noise (compared to the optimum fixed threshold) for a specified speed of response. For the mean-level threshold, a simple mathematical solution is found for the detection probability when the noise is stationary and the signal scintillates rapidly. The performance is evaluated for a wide range of mean-level-threshold time constants and for several false-alarm probabilities. The results are presented graphically. As an example, the mean-level threshold suffers 3 dB in detectability (equivalent signal-to-noise ratio) in the presence of stationary noise as compared to the optimum fixed threshold for 50-percent probability of detection, false-alarm probability of 10-8, and an adjustment time of 15 times the signal duration.     

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.     

导弹复合控制系统的模糊逻辑控制分配

针对空空导弹复合控制系统中的控制分配问题,提出了一种模糊逻辑控制分配算法。采用动态面控制方法设计了复合控制量的控制律。在设计过程中,利用扩张状态观测器估计汇总不确定项,并采用光滑二阶滑模控制算法设计了控制律,达到了提高鲁棒性和削弱抖振现象的目的。应用模糊逻辑控制分配算法将复合控制量分解为直接力控制指令和舵偏角控制指令。为了检验所设计的复合控制系统的控制效果,对采用基于模糊逻辑控制分配算法的复合控制系统和传统的气动力控制系统进行了对比仿真实验。仿真结果表明,所设计的复合控制系统具有更好的控制效果。     

密集杂波背景下的水下多目标跟踪方法

水下多目标跟踪是水声信号处理领域研究的热点和难点问题。高斯混合概率假设密度（Gaussian mixture probability hypothesis density, GM-PHD）滤波器以其高效的计算效率为解决水下多目标跟踪问题提供了保证。然而，GM-PHD滤波器在跟踪目标时需要先验已知新生目标的强度，否则其性能会出现严重退化。针对该问题，提出一种滑动窗两步初始化高斯混合概率假设密度（sliding window two step initialization GM-PHD, SWTSI-GMPHD）滤波器。将提出的滑动窗两步初始化方法嵌入GM-PHD滤波器，利用滑动窗两步初始化方法估计新生目标强度，减少杂波干扰导致跟踪结果中出现的虚假目标。仿真实验表明，在杂波密集环境下，相较于其他跟踪方法，提出方法将跟踪精度提高69.84%，52.62%和41.05%。