机械抖动偏频激光陀螺静态测角方法

阐述采用机械抖动偏频激光陀螺进行静态角度测量的原理,分析测角随机误差与激光陀螺角随机游走系数、测量时间的关系,通过转台分度误差实验验证了测角随机误差公式。采用排列互比法对测角系统误差和转台分度误差进行分离。实验与理论分析表明,静态测角方法具有良好的环境适应性和稳定性,测角随机误差优于0.26″,系统误差优于1″。最后分析了进一步减小测角随机误差和系统误差的措施。     

飞机结构疲劳可靠度贝叶斯组合预测

在实际工程中,常常需要利用模型去描述和分析问题。然而模型亦存在不确定性,即可能存在多个描述同一现象的模型,例如多个疲劳分析的模型。针对飞机结构的疲劳可靠性问题,提出在考虑三种裂纹扩展模型下基于贝叶斯公式的疲劳可靠度组合预测方法。针对不同应力水平下飞机结构试件的裂纹扩展数据建立了三种随机裂纹扩展模型;在考虑模型参数不确定性条件下,采用贝叶斯模型平均方法对三种模型进行组合;基于组合模型分析结构的可靠度。所提方法在分析飞机结构疲劳可靠度上,采用了组合模型,能够最大限度保障结果的稳定性。此外,考虑了模型参数的不确定性,能够得到更为合理的裂纹扩展预测分布和可靠度预测值。给出的实例及分析结果表明所提方法可行。     

MgSO4弛豫吸收对水下强声波脉冲传播的影响分析

对水下等离子体放电强声波脉冲实验测量波形进行FFT变换发现,其能量主要集中在100kHz以下的频段内,在这个频段内,海水中存在的一种盐类——MgSO4(硫酸镁)化学弛豫会造成声波的逾量吸收.本文从包含海水中MgSO4弛豫吸收的修正物质状态方程出发,推导了强声波脉冲传播的新的波动方程,并结合具体的数值算法,对强声波脉冲的传播进行了数值模拟,分析了MgSO4弛豫吸收对脉冲波形的传播及频谱的影响.研究表明,MgSO4弛豫吸收对陡峭的冲击脉冲波形具有平滑和展宽作用,使得脉冲的能量更靠近低频.这种效应与球面波阵面的几何扩散相结合,造成了强声波脉冲能量的逾量损失.     

基于脉冲串信号的无源定位系统频差估计误差CRLB分析

频差估计是无源定位系统中的关键部分,其估计精度直接决定了无源定位系统的性能。本文对单频脉冲信号频差估计误差方差的Cramer-Rao下限(CRLB)进行了理论分析研究。在建立数学模型的基础上,定量分析了频差估计误差CRLB与接收信号参数的数学关系。通过直接公式推导和数值仿真归纳,分别得出了相参/非相参单频脉冲信号频差估计误差CRLB的解析表达式,该结论可用于指导基于频差估计的无源定位系统设计。     

采用3电平非均匀量化的脉冲编码策略

作为全数字发信机系统中广泛应用的一种脉冲编码技术,Delta-Sigma调制(Delta-Sigma Modulation, DSM)通过增加量化电平,能够实现调制性能的提升。但限于全数字发信机系统开关功放的具体结构,多电平DSM序列无法直接驱动后级功放电路。在传统3电平DSM基础上,通过引入面积等效原理和非均匀量化技术,提出了适用于开关功放的一种新的脉冲编码策略。理论分析和仿真结果表明,相比常规2电平DSM序列,采用该策略获得的调制脉冲序列具有更优的带内SNR和编码效率性能。     

UWB-SAR抑制RFI算法性能评估与测试

参数化方法是实现UWB -SAR抑制RFI的重要手段。为评估抑制RFI算法的实际性能 ,利用UWB -SAR实验系统的实测数据 ,从干扰抑制能力和脉冲压缩性能改善两个方面对几种主要算法进行了比较分析。结果表明 ,在干扰能量抑制比和脉冲压缩指标度量下 ,几种典型的参数化算法都能显著提高接收信号的信干比 ,而基于正弦波模型的算法略优于基于AR模型的算法。     

条件随机变量与条件数据融合

本文讨论基于条件事件代数系统上的条件随机变量的表示问题,并给出了在多个信息源提供的不同类型的条件数据时之统一表示方法,以及利用条件随机变量分布函数性质,对所得数据进行关联等。     

Adaptive random search for continuous simulation optimization

We present, analyze, and compare three random search methods for solving stochastic optimization problems with uncountable feasible regions. Our adaptive search with resampling (ASR) approach is a framework for designing provably convergent algorithms that are adaptive and may consequently involve local search. The deterministic and stochastic shrinking ball (DSB and SSB) approaches are also convergent, but they are based on pure random search with the only difference being the estimator of the optimal solution [the DSB method was originally proposed and analyzed by Baumert and Smith]. The three methods use different techniques to reduce the effects of noise in the estimated objective function values. Our ASR method achieves this goal through resampling of already sampled points, whereas the DSB and SSB approaches address it by averaging observations in balls that shrink with time. We present conditions under which the three methods are convergent, both in probability and almost surely, and provide a limited computational study aimed at comparing the methods. Although further investigation is needed, our numerical results suggest that the ASR approach is promising, especially for difficult problems where the probability of identifying good solutions using pure random search is small. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于DRFM的机载PD雷达干扰研究

针对传统干扰技术对PD雷达干扰的不足,噪声干扰对干扰机功率要求高,欺骗干扰产生的干扰数目单一,基于当前对抗先进体制雷达的手段——DRFM,对PD雷达干扰进行研究。通过将截获的雷达信号存储、处理,按程序设定的转发间隔重复读出当前采样信号并转发,产生了多个距离欺骗假目标;通过对每次转发干扰进行频率调制,产生了包含距离速度欺骗的一系列假目标;并经过Matable仿真验证了在PD雷达窄带滤波器中,出现多个距离或速度欺骗假目标。并通过仿真验证了干扰的有效性。     

Averaging frameworks for simulation optimization with applications to simulated annealing

We present two frameworks for designing random search methods for discrete simulation optimization. One of our frameworks is very broad (in that it includes many random search methods), whereas the other one considers a special class of random search methods called point‐based methods, that move iteratively between points within the feasible region. Our frameworks involve averaging, in that all decisions that require estimates of the objective function values at various feasible solutions are based on the averages of all observations collected at these solutions so far. Also, the methods are adaptive in that they can use information gathered in previous iterations to decide how simulation effort is expended in the current iteration. We show that the methods within our frameworks are almost surely globally convergent under mild conditions. Thus, the generality of our frameworks and associated convergence guarantees makes the frameworks useful to algorithm developers wishing to design efficient and rigorous procedures for simulation optimization. We also present two variants of the simulated annealing (SA) algorithm and provide their convergence analysis as example application of our point‐based framework. Finally, we provide numerical results that demonstrate the empirical effectiveness of averaging and adaptivity in the context of SA. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012