21世纪初军用飞行器战术技术要求的新内容——隐身能力

本文从战争的启示、系统工程分析的结论及反隐身技术的威胁等三方面,论证了“隐身能力”对未来军用飞行器的重要性。文中着重分析了21世纪初军用飞行器战术技术要求的新内容——“隐身能力”所包括的三个内容:（1）飞行器的散射特性及辐射特性;（2）飞行器的电子干扰能力;（3）飞行器所用的战术隐身技术。     

CESM-a new category of radar ECCM

Radar ECCM techniques are well known. Heretofore the listed ECCM effects have generally been to counteract the effects of ECM. This approach is one of attempting to cure an illness, rather than preventing it. Modem ECM systems usually include an ESM receiver to detect the radar signal, identify it by its emission characteristics, assess its importance, select the proper ECM, and signal to initiate ECM. If the ESM receiver detection of the radar signal can be delayed/denied, or the identification be confused, either the wrong ECM may be applied, or delayed. The radar may thus not be confronted with timely, proper ECM. Radar operation may therefore be possible. This paper introduces and defines CESM, a new category of radar ECCM. There are two principles of CESM-those which delay/deny ESM receiver detection, and those which confuse/impede signal identification. Illustrative examples of CESM techniques/operating techniques are given. It is shown that many CESM techniques may have multiple roles by impeding detection, impeding identification, and also diluting effects of ECM     

Importance sampling for characterizing STAP detectors

This paper describes the development of adaptive importance sampling (IS) techniques for estimating false alarm probabilities of detectors that use space-time adaptive processing (STAP) algorithms. Fast simulation using IS methods has been notably successful in the study of conventional constant false alarm rate (CFAR) radar detectors, and in several other applications. The principal objectives here are to examine the viability of using these methods for STAP detectors, develop them into powerful analysis and design algorithms and, in the long term, use them for synthesizing novel detection structures. The adaptive matched filter (AMF) detector has been analyzed successfully using fast simulation. Of two biasing methods considered, one is implemented and shown to yield good results. The important problem of detector threshold determination is also addressed, with matching outcome. As an illustration of the power of these methods, two variants of the square-law AMF detector that are thought to be robust under heterogeneous clutter conditions have also been successfully investigated. These are the envelope-law and geometric-mean STAP detectors. Their CFAR property is established and performance evaluated. It turns out the variants have detection performances better than those of the AMF detector for training data contaminated by interferers. In summary, the work reported here paves the way for development of advanced estimation techniques that can facilitate design of powerful and robust detection algorithms     

“机械制图”仿真教具的开发与应用

“机械制图”课程是各类工科专业必修的非常重要的专业基础课程,通过分析观察发现,学生对投影知识理解困难,利用AutoCAD、Flash、SolidWorks等软件,开发制作了仿真动画演示教具,本文详细介绍了该教具的制作思路、过程和制作技巧。     

体积成形数值模拟技术的研究现状及发展趋势

 简要回顾了金属体积成形三维数值模拟技术的发展历程 ,对国内外在此领域的研究现状及发展趋势作了较全面的分析与展望 ,指出研究的重点由宏观转向微观、单一分散转向耦合集成、由共性通用转向特性专用型的模拟。介绍了 4种数值模拟新方法——无网格数值模拟、自适应有限元数值模拟、刚塑性有限边界单元法、基于特征的有限元数值模拟。     

Spectral-spatial target detection based on data field modeling for hyperspectral data

Target detection is always an important application in hyperspectral image processing field. In this paper, a spectral-spatial target detection algorithm for hyperspectral data is proposed. The spatial feature and spectral feature were unified based on the data filed theory and extracted by weighted manifold embedding. The novelties of the proposed method lie in two aspects. One is the way in which the spatial features and spectral features were fused as a new feature based on the data field theory, and the other is that local information was introduced to describe the decision boundary and explore the discriminative features for target detection. The extracted features based on data field modeling and manifold embedding techniques were considered for a target detection task. Three standard hyperspectral datasets were considered in the analysis. The effectiveness of the proposed target detection algorithm based on data field theory was proved by the higher detection rates with lower False Alarm Rates (FARs) with respect to those achieved by conventional hyperspectral target detectors.     

Fault Detection in Dynamic Systems via Decision Fusion

Due to the growing demands for system reliability and availability of large amounts of data, efficient fault detection techniques for dynamic systems are desired. In this paper, we consider fault detection in dynamic systems monitored by multiple sensors. Normal and faulty behaviors can be modeled as two hypotheses. Due to communication constraints, it is assumed that sensors can only send binary data to the fusion center. Under the assumption of independent and identically distributed (1ID) observations, we propose a distributed fault detection algorithm, including local detector design and decision fusion rule design, based on state estimation via particle filtering. Illustrative examples are presented to demonstrate the effectiveness of our approach.     

基于遗传算法的目标检测定位方法

将目标的检测定位归结为一类组合优化问题,利用遗传算法的进化策略,采用改进的遗传算法,提出了2种基于遗传算法的目标检测定位方法:基于遗传算法的相关匹配定位法和图象序列目标检测定位法。并给出了在可见光图象序列上的实验结果。     

Validation of techniques for space based remote sensing of auroral precipitation and its ionospheric effects

Knowledge of the spatial distribution of auroral precipitation and its associated ionospheric effects is important both to scientific studies of the Earth's environment and successful operation of defense and communication systems. Observations with the best spatial and temporal coverage are obtained through remote sensing from space-based platforms. Various techniques have been used, including the detection of visible, ultraviolet and X-ray emissions produced by the precipitating particles. Interpretation of the measurements is enabled through theoretical modeling of the interaction of precipitating particles with atmospheric constituents. A great variety of auroral precipitation exists, with each kind differing in the type and energy distribution of the particles, as well as in its spatial and temporal behavior. Viable remote sensing techniques must be able to distinguish at least the species of particle, the total energy flux, and the average energy. Methods based on visible, ultraviolet and X-ray emissions meet these requirements to varying degrees. These techniques and the associated space instrumentation have evolved in parallel over the last two decades. Each of the methods has been tested using simultaneous measurements made by space-based imaging systems and ground-based measurements made by radars and optical instruments. These experiments have been extremely helpful in evaluating the performance and practicality of the instruments and the results have been crucial in improving instrument design for future remote sensing platforms. The next decade will see continued development and test of remote sensing instruments and the measurements, in addition to providing important operational data, will be increasingly more critical in addressing a number of scientific problems in auroral and atmospheric physics.     

高职专业建设探索

作为一种新的教学类型，高等职业教育的专业建设对于培养适应市场需求的技术应用性人才犹为重要。本分析了现行专业建设中存在的问题，提出了如何结合高职教育特点改革高职专业建设的设想。     

A Coarse Search Correlation Tracker for Image Registration

A high-speed compact digital correlation tracker which determines the frame-to-frame translational motion between two images is presented. By combining a similarity detection approach with the correlation coefficient in a parallel pipelined architecture, effective tracking rates comparable to conventional fast Fourier transform (FFT) techniques can be achieved. Examples of the tracker's performance using simulated data and image data acquired by an active infrared radar are given.     

Grazing-incidence telescopes for X-ray astronomy

We review the progress made at our laboratory over the past several years in developing grazing-incidence imaging X-ray optics. Mirrors, detection systems and dispersion techniques are discussed and experimental results are given. We discuss the application of two telescope systems to a number of experimental observations in X-ray astronomy.     

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.     

In search of other planetary systems

Numerous recent developments have led to an increasing awareness of and interest in the detection of other planetary systems. A brief review of the modern history of this subject is presented with emphasis on the status of data concerning Barnard's star. A discussion is given of plausible observable effects of other planetary systems with numerical examples to indicate the nature of the detection problem. Possible types of information (in addition to discovery) that observations of these effects might yield (e.g., planetary mass and temperature) are outlined. Also discussed are various candidate detection techniques (e.g., astrometric observations) which might be employed to conduct a search, the current state-of-the-art of these techniques in terms of measurement accuracy, and the capability of existing or planned facilities (e.g., space telescope) to perform a search. Finally, consideration is given to possible search strategies and the scope of a comprehensive search program.     

飞行员情境意识定量测量研究综述

情境意识是飞行员驾驶飞机所需的关键能力之一,而量化评估飞行员的情境意识则是许多研究关注的重点。为了厘清过往飞行员情境意识方面的研究,本文首先总结了六种传统测量方式,包括冻结探测技术、实时探测技术、实验后自评技术、观察者评分技术、绩效表现评估及生理指标评估;然后,介绍了采用数学建模测量飞行员情境意识的方式,这种测量方式更加精细,且具有很强的预测性;最后,详细总结归纳了飞行员情境意识的过往研究中所采用的主要测量手段,对其发展方向进行展望,为该领域的后续研究提供了一定参考。     

液体火箭发动机推进剂检漏技术的综述

在液体火箭发动机发射前,必须进行完整性试验。完整性试验包括对推进剂和其它液体系统的泄漏检测。建立一个能实现推进剂泄漏故障自动检测的系统是很必要的。本文对液体火箭发动机的泄漏故障检测方法进行了综述,对已用于或可能用于液体火箭发动机检漏的技术进行分类和详细评述,指出了液体火箭发动机检漏技术的几个发展方向。     

A multiobjective optimization approach to determine the parameters of stepped frequency pulse train

Frequency stepping techniques are commonly used in modern radar system to get high range resolution with the disadvantage that its autocorrelation function (ACF) yield undesirable “grating lobes”. Wider mainlobe deteriorates the range resolution capability of the waveform and higher peak sidelobe either hides the small targets or causes the false target detection. Several techniques have been used to choose the parameters of linear frequency modulated (LFM) pulse train to suppress the grating lobes without paying much attention to the mainlobe width and peak sidelobe level. In this paper a multiobjective optimization (Nondominated Sorting Genetic Algorithm-II (NSGA-II)) approach is proposed to optimize the parameters of the LFM pulse train to achieve reduced grating lobes, low peak sidelobe level and narrow mainlobe width. The optimization problem has been studied in two different ways: first one is associated with the reduction of grating lobes and the minimization of peak sidelobe level of the ACF with constraints and second one is related to the minimization of the peak sidelobe level and mainlobe width of the ACF with constraints. Simulation studies have been carried out to justify the potentiality of the proposed approach.     

Generalized input-estimation technique for tracking maneuveringtargets

A new input estimation technique for target tracking problem is proposed. Conventional input estimation techniques assume that the target maneuver level is constant within the detection window, which has been the major drawback of the techniques. The proposed technique is developed to overcome this drawback by modeling the target maneuver as a linear combination of some basic time functions. The resulting algorithm has a generalized formulation including earlier works on input estimation. A detection performance of the proposed algorithm is analyzed by investigating the detection sensitivity according to the selection of maneuver models and other design parameters such as the detection window size, measurement noise level, and sampling step size. A computer simulation study shows that the estimation performance of the proposed algorithm is comparable to Bogler's input estimation method while the computation time is greatly reduced     

Automatic spectral target recognition in hyperspectral imagery

Automatic target recognition (ATR) in hyperspectral imagery is a challenging problem due to recent advances of remote sensing instruments which have significantly improved sensor's spectral resolution. As a result, small and subtle targets can be uncovered and extracted from image scenes, which may not be identified by prior knowledge. In particular, when target size is smaller than pixel resolution, target recognition must be carried out at subpixel level. Under such circumstance, traditional spatial-based image processing techniques are generally not applicable and may not perform well if they are applied. The work presented here investigates this issue and develops spectral-based algorithms for automatic spectral target recognition (ASTR) in hyperspectral imagery with no required a priori knowledge, specifically, in reconnaissance and surveillance applications. The proposed ASTR consists of two stage processes, automatic target generation process (ATGP) followed by target classification process (TCP). The ATGP generates a set of targets from image data in an unsupervised manner which will subsequently be classified by the TCP. Depending upon how an initial target is selected in ATGP, two versions of the ASTR can be implemented, referred to as desired target detection and classification algorithm (DTDCA) and automatic target detection and classification algorithm (ATDCA). The former can be used to search for a specific target in unknown scenes while the latter can be used to detect anomalies in blind environments. In order to evaluate their performance, a comparative and quantitative study using real hyperspectral images is conducted for analysis.