Contents and Author Index,Volume 20, 2013

The United States has multiple nuclear detection initiatives to secure against a terrorist nuclear attack, including the Container Security Initiative, installation of radiation detectors at U.S. border points of entry, and establishment of the Domestic Nuclear Detection Office (DNDO). The current nuclear detection system architecture falls short of being able to reliably catch fissile nuclear material in transit, specifically shielded Highly Enriched Uranium (HEU) and Plutonium (Pu), both within the US and abroad. Checkpoints at border crossings can be circumvented, and no adequate system is under development to deter the transport of fissile materials. Using nuclear link-budget calculations, we show why a network relying primarily on handhelds, fixed detectors, and portals is not sufficient. We examine the technical, economic, and operational feasibility of a comprehensive national network incorporating in-vehicle detectors to reliably detect and deter the transport of fissile material inside the vehicle itself.     

Adaptive subspace detection based on two-step dimension reduction in the underwater waveguide

In the underwater waveguide, the conventional adaptive subspace detector (ASD), derived by using the generalized likelihood ratio test (GLRT) theory, suffers from a significant degradation in detection per-formance when the samplings of training data are deficient. This paper proposes a dimension-reduced approach to alleviate this problem. The dimension reduction includes two steps: firstly, the full array is divided into several subarrays; secondly, the test data and the training data at each subarray are transformed into the modal domain from the hydrophone domain. Then the modal-domain test data and training data at each subarray are processed to formulate the subarray statistic by using the GLRT theory. The final test statistic of the dimension-reduced ASD (DR-ASD) is obtained by summing all the subarray statistics. After the dimension reduction, the unknown parameters can be estimated more accurately so the DR-ASD achieves a better detection performance than the ASD. In order to achieve the optimal detection performance, the processing gain of the DR-ASD is deduced to choose a proper number of subarrays. Simulation experiments verify the improved detection performance of the DR-ASD compared with the ASD.     

基于模糊聚类的入侵检测方法

分析了异常入侵检测存在的问题,研究了基于模糊聚类的入侵检测算法。该算法采用C-均值算法,通过训练数据聚类、异常聚类划分和行为判定等3个步骤实现异常入侵检测。试验采用KDD99数据进行了测试,证明该算法是可行和有效的。     

一种“炮身轴线偏移”检测的新方法

通过光电编码器、步进电机细分电路及可编程逻辑控制器技术,提出了炮身轴线偏移检测的全新方法,克服了传统方法检测精度不高、自动化程度低等不足。基于该方法研制的检测系统,经某新型自行榴弹炮火力系统装配及实弹射击检验,证明该方法是可行的。     

目标起伏特性对雷达威力性能的影响分析

介绍了典型雷达目标RCS起伏模型,阐述了起伏目标在实际中的应用,建立了目标损耗和雷达作用距离之间的关系,为不同目标的等效替代推算提供了理论依据.验证了雷达目标满足卡平方分布时发现概率和起伏因子之间的关系.并针对不同类型的起伏目标,建立了雷达探测距离和发现概率之间的关系,为雷达的威力检测和飞行目标的航线设计提供依据.     

机房漏水检测与精确定位装置研究

机房漏水是危及精密信息设备长期稳定可靠运行的重大安全隐患。为了解决传统定位装置难以实现漏水点精确定位的问题,从传感电缆的检漏原理出发,利用分压补偿原理,通过STEP7软件编程,设计了一个结合自检、漏水检测和漏水定位3种功能的机房漏水检测与定位装置。在此基础上搭建了实验系统,经测试实验,结果表明短距离定位精度可以达到1．70％,从而证实了该装置检测的有效性和定位的精确性。     

基于OCSVM和MCSVM的新故障检测与诊断技术研究

针对SVM故障诊断方法无法对新故障模式进行有效检测的问题,在阐述OCSVM原理的基础上,详细分析了各种参数对其性能的影响,提出了基于OCSVM和多类分类MCSVM相结合的新故障检测与诊断方法．实验结果表明,该算法在故障诊断及新故障检测方面有较高的精度,具有良好的推广性．     

基于粒子滤波改进的VTS微弱目标检测前跟踪算法

舰船交通服务系统是民用雷达的信息集成系统,探测微弱目标存在RCS小、回波弱、杂波强等问题,导致信噪比低,难以实现有效检测跟踪。基于粒子滤波的检测前跟踪技术对低信噪比下微弱目标信息积累和探测有良好效果。通过采集单设备实测数据,构建遗忘因子和收敛因子以增加重采样的效率,引入虚拟采样保持粒子的多样性,提升粒子滤波对微弱目标的探测能力。仿真试验表明,改进后的算法可实现舰船交通服务系统对微弱目标的有效探测,并能获得较精准的目标状态估计值。     

基于多通道雷达的对侦察接收机截获距离压制设计

低截获概率(LPI)雷达为了达到低截获的目的,雷达通常会采取很多措施,包括可变的重频,复杂的脉内调制,甚至于载频捷变等等,但是,从根本上来说,这些措施只是增加了侦察机的分选识别难度,间接地降低截获概率,真正想要获得很好的低截获概率,通常需要雷达控制探测距离。在LPI雷达作用距离不变的条件下,采用多通道的设计方法,根据灵敏度的计算给出了获得较大安全探测距离的方法,从而压制侦察接收机的截获距离。     

基于Hough变换的叶簇环境下SAR/GMTI动目标检测算法

叶簇环境下,当动杂波比较复杂时,常规的目标检测算法CFAR和DPCA不能有效地滤除杂波。提出了一种基于Hough变换的叶簇环境下SAR/GMTI动目标检测算法(HD),该算法在叶簇杂波比较复杂的情况下能够有效滤除动杂波,提取出动目标。首先,介绍了叶簇扰动环境下的场景建模,并且给出了建模分析和建模场景仿真;其次,给出了HD算法推导过程;最后,在建模基础上对该算法和常规算法进行了对比仿真实验。实验结果表明,该算法在较低信噪比情况下也能保持较高的检测概率。