基于微多普勒特征的欺骗干扰识别

为了提高雷达的抗干扰能力,提出了一种基于微多普勒特征的欺骗干扰识别方法,为雷达选择抗干扰措施提供了先验知识。首先建立了目标回波和干扰信号的数学模型,分析了二者微多普勒频率的差异。其次利用Viterbi算法和FFT谱分析对信号的特征参数进行了提取。最后,定义了识别目标和干扰的特征因子,并根据特征因子设定阈值对目标回波和欺骗干扰进行识别。仿真结果验证了算法的正确性和稳定性,与理论分析一致,表明该方法能够在较低的信噪比环境下对欺骗干扰进行检测识别。     

浅谈边防部队基层干部“六结合”监督模式

在分析公安边防部队基层干部监督的特点及现状的基础上,构建以党内监督、行政监督、群众监督、新闻舆论监督、法制监督、自我监督为主体,相互协调、相互促进的公安边防部队基层干部＂六结合＂监督模式。     

Dynamic signatures and their use in comparing the reliability of new and used systems

The signature of a system with independent and identically distributed (i.i.d.) component lifetimes is a vector whose ith element is the probability that the ith component failure is fatal to the system. System signatures have been found to be quite useful tools in the study and comparison of engineered systems. In this article, the theory of system signatures is extended to versions of signatures applicable in dynamic reliability settings. It is shown that, when a working used system is inspected at time t and it is noted that precisely k failures have occurred, the vector s [0,1]^n‐k whose jth element is the probability that the (k + j)th component failure is fatal to the system, for j = 1,2,2026;,n ‐ k, is a distribution‐free measure of the design of the residual system. Next, known representation and preservation theorems for system signatures are generalized to dynamic versions. Two additional applications of dynamic signatures are studied in detail. The well‐known “new better than used” (NBU) property of aging systems is extended to a uniform (UNBU) version, which compares systems when new and when used, conditional on the known number of failures. Sufficient conditions are given for a system to have the UNBU property. The application of dynamic signatures to the engineering practice of “burn‐in” is also treated. Specifically, we consider the comparison of new systems with working used systems burned‐in to a given ordered component failure time. In a reliability economics framework, we illustrate how one might compare a new system to one successfully burned‐in to the kth component failure, and we identify circumstances in which burn‐in is inferior (or is superior) to the fielding of a new system. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

机械系统状态监测特征参数评价与选取

根据机械不同异常状态出现的频率和危害度的大小,引入状态权值,建立了特征参数总体敏感性和稳定性的评价指标,采用专家系统设计思想,编写了机械状态监测特征参数评价与选取应用软件,实现了特征参数的自动选取以及对特征参数和机械状态数据的有效管理。     

基于多指标相似性的T/R组件剩余寿命融合预测方法

为实现对T/R组件剩余寿命的准确预测，及时掌握装备当前健康状态和提高装备维修保障水平，分析T/R组件的故障特点，筛选出反映T/R组件状态退化过程的状态监测指标，通过计算每个指标对应的剩余寿命信息和权重，得到T/R组件的剩余寿命预测结果。通过算例分析与比较，验证了预测方法的实用性与有效性。研究结果可为电子装备剩余寿命预测提供理论指导，对合理计划维修资源和提高装备战斗力具有重要意义。     

机械振动烈度的频域算法研究

在理论分析的基础上,研究了利用DFT在频域计算振动烈度的方法,并结合实践经验,给出了实际应用中的注意事项。在频域计算振动烈度,对振动信号类型和计算频率范围选择具有较强灵活性,避免了在时域利用微积分进行信号类型转换和选频滤波等处理过程。     

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

基于LabVIEW的机电设备远程监测虚拟仪器设计

随着计算机技术、网络技术及虚拟仪器技术的飞速发展，机电设备的监测与诊断也趋于网络化、实时化及分析显示仪器化。因此，充分利用计算机资源，将实时采集到的数据及时准确地发布到远程监测客户端，并建立功能完备的监测与分析虚拟仪器，已成为远程设备监测的关键。     

基于方位量测的舰艇对潜定位技术研究

结合舰艇拖曳线列阵声纳实际搜潜装备,利用舰载线列阵声纳测得的潜艇目标方位信息,建立了基于方位量测的舰艇对潜艇目标定位的数学模型,给出求解潜艇运动参数的定位算法,并对定位误差进行了分析,在定位模型及算法的基础上,仿真研究了潜艇与舰艇之间的初始距离、舰艇测得潜艇目标初始方位角、潜艇航向等因素对定位性能的影响,给出仿真结果并进行了分析,该结果对于指导实际反潜具有一定的实用价值。     

型号研制与产品数据管理

介绍了产品数据管理(PDM)的概念和基本功能,结合当前型号研制的特点和计算机信息技术应用的状况、发展,研究了型号研制产品数据管理的需求、功能及实施,为当前型号研制依靠CIMS技术实现产品数据管理提出了8条基本原则。