基于贝叶斯混合源分离方法的声纳探测误差模型

声纳的探测误差模型是声纳仿真的核心技术。针对现有的声纳误差白噪声模型仿真逼真度低的问题,提出了基于贝叶斯混合源分离方法,建立了声纳的探测误差模型,提高了声纳误差模型的性能。与传统的白噪声仿真方法相比,基于贝叶斯混合源分离方法的声纳误差仿真模型具有较好的逼真度,可以有效地对声纳探测误差进行建模和预测。     

Partial equilibrium in risk‐based production decisions

Characteristically, a small subset of operational problems admit risk neutrality when contingent claims methodology were used in their analysis. That is, for the majority of manufacturing and production problems, operating cash flows are not directly linked to prices of traded assets. However, to the extent that correlations can be estimated, the methodology's applicability to a broader set of operational problems is supported. Our article addresses this issue with the objective of extending the use of contingent claims techniques to a larger set of operational problems. In broad terms, this objective entails a partial equilibrium approach to the problem of valuing uncertain cash flows. To this end, we assume risk aversion and cast our approach within Merton's intertemporal capital asset pricing model. In this context, we formulate a “generic” production valuation model that is framed as an exercise in stochastic optimal control. The model is versatile in its characterization and can easily be adapted to accommodate a wide‐ranging set of risk‐based operational problems where the underlying sources of uncertainty are not traded. To obtain results, the model is recast as a stochastic dynamic program to be solved numerically. The article addresses a number of fundamental issues in the analysis risk based decision problems in operations. First, in the approach provided, decisions are analyzed under a properly defined risk structure. Second, the process of analysis leads to suitably adjusted probability distributions through which, appropriately discounted expectations are derived. Third, through consolidating existing concepts into a standard and adaptable framework, we extend the applicability of contingent claims methodology to a broader set of operational problems. The approach is advantageous as it obviates the need for exogenously specifying utility functions or discount rates.© 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

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     

Optimal inventory control policy for periodic‐review inventory systems with inventory‐level‐dependent demand

We consider a setting in which inventory plays both promotional and service roles; that is, higher inventories not only improve service levels but also stimulate demand by serving as a promotional tool (e.g., as the result of advertising effect by the enhanced product visibility). Specifically, we study the periodic‐review inventory systems in which the demand in each period is uncertain but increases with the inventory level. We investigate the multiperiod model with normal and expediting orders in each period, that is, any shortage will be met through emergency replenishment. Such a model takes the lost sales model as a special case. For the cases without and with fixed order costs, the optimal inventory replenishment policy is shown to be of the base‐stock type and of the (s,S) type, respectively. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Newsvendor problems with sequentially revealed demand information

This article analyzes a capacity/inventory planning problem with a one‐time uncertain demand. There is a long procurement leadtime, but as some partial demand information is revealed, the firm is allowed to cancel some of the original capacity reservation at a certain fee or sell off some inventory at a lower price. The problem can be viewed as a generalization of the classic newsvendor problem and can be found in many applications. One key observation of the analysis is that the dynamic programming formulation of the problem is closely related to a recursion that arises in the study of a far more complex system, a series inventory system with stochastic demand over an infinite horizon. Using this equivalence, we characterize the optimal policy and assess the value of the additional demand information. We also extend the analysis to a richer model of information. Here, demand is driven by an underlying Markov process, representing economic conditions, weather, market competition, and other environmental factors. Interestingly, under this more general model, the connection to the series inventory system is different. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 2012     

基于深度优先搜索与增量式求解的极小一阶不可满足子式提取算法

随着寄存器传输级甚至行为级的硬件描述语言应用越来越广泛,基于一阶逻辑的可满足性模理论(Satisfiability Modulo Theories,SMT)逐渐替代布尔可满足性(Boolean Satisfiability,SAT),在VLSI形式化验证领域具有更加重要的应用价值。而极小不可满足子式能够帮助EDA工具迅速定位硬件中的逻辑错误。针对极小SMT不可满足子式的求解问题,采用深度优先搜索与增量式求解策略,提出了深度优先搜索的极小SMT不可满足子式求解算法。与目前最优的宽度优先搜索算法对比实验表明:该算法能够有效地求解极小不可满足子式,随着公式的规模逐渐增大时,深度优先搜索算法优于宽度优先搜索算法。     

组网雷达的改进粒子滤波算法

针对现代战争中有源雷达容易受到干扰和反辐射导弹的摧毁,以及无源雷达隐蔽性高,只能测量方位角度,测量精度小等特点,提出利用集中式有源雷达系统与无源雷达系统协同组网对目标进行跟踪。但是在实际环境中,噪声属性以及有源雷达,无源雷达接收信号的特点决定了组网雷达需要应用非线性滤波技术对信号进行处理。传统的非线性技术包括卡尔曼滤波、扩展卡尔曼滤波(EKF)或无迹卡尔曼滤波(UKF)等方法。非线性近似过程带来的误差相对较大,而且均要求观测噪声和过程噪声为独立或相关的高斯白噪声。而粒子滤波避免了传统非线性滤波方法的缺陷,但是存在粒子退化,于是用EKF和UKF在每一时刻更新粒子,用更新的粒子及其协方差构造重要性函数,然后重采样。仿真实验表明这两种改进粒子滤波方法有很好的效果。     

基于线加速度计的高分辨率光学影像颤振检测与重建方法

卫星平台颤振条件下,推扫式高分辨率光学影像成像往往产生扭曲,从而影响影像的定位及信息提取精度。针对当前颤振下影像成像扭曲补偿的问题,提出一种基于线加速度计测量平台颤振下的稳态重成像模型实现高分辨率卫星颤振扭曲影像的重建。采用受平台颤振影响而扭曲变形的高分某型号卫星全色影像数据进行验证。分析结果表明:提出的线加速度计可以有效检测并测量出平台的颤振,设计的颤振影像地面重建模型可以有效提高光学影像成像质量,补偿后影像扭曲变形现象明显消除。     

飞越北极航行时间模型的研究

对飞越北极,缩短航线,节省航行时间问题进行了研究。采用了多种算法,对其有效性、适用性和复杂性进行分析讨论。假设"在旋转椭球体中,以通过球心和该椭球体上任意两点所构成的平面截此椭球体所得轨迹弧长作为曲面上两点间最短距离的近似值",在此基础上,通过运用数学软件计算得出结论:从北京出发,飞越北极抵达底特律的飞行时间可节省4.079 6h,从而使问题得到了进一步的验证。     

SAR卫星偏航导引补偿效果分析

通过建立"SAR卫星—地球—目标点"几何模型,得到多普勒中心频率的精确值;简化模型,求得卫星的偏航导引规律;分析简化前后两模型,从而得出偏航导引的补偿效果。