记录可寻址随机访问文件的设计与实现

记录可寻址随机访问文件是一种新型ＦＯＲＴＲＡＮ文件,它集中了顺序与直接文件两者的优点,为用户随机访问文件中不等长记录提供了更为有效的手段。本文不仅介绍了其使用方法,而且还讨论了实现中的有关问题。     

再入飞行器落点准确度的统计分析

本文研究再入飞行器的落点准确度(系统性偏差)的检验和估计方法。首先,文中引入了准确度的容许限的概念,在此基础上给出了Bayes验后加权概率比检验方法。关于落点系统偏差的估计,讨论了Bayes估计方法及带有约束的Bayes估计方法。文中注意了充分运用试验前的信息,以便使落点系统偏差的评估能在小子样场合下进行。     

Discrete stochastic optimization using variants of the stochastic ruler method

We present two random search methods for solving discrete stochastic optimization problems. Both of these methods are variants of the stochastic ruler algorithm. They differ from our earlier modification of the stochastic ruler algorithm in that they use different approaches for estimating the optimal solution. Our new methods are guaranteed to converge almost surely to the set of global optimal solutions under mild conditions. We discuss under what conditions these new methods are expected to converge faster than the modified stochastic ruler algorithm. We also discuss how these methods can be used for solving discrete optimization problems when the values of the objective function are estimated using either transient or steady‐state simulation. Finally, we present numerical results that compare the performance of our new methods with that of the modified stochastic ruler algorithm when applied to solve buffer allocation problems. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

宽频带随机振动环境的疲劳强度强化机理

全轴随机振动环境的疲劳强化机理问题是可靠性强化试验研究的关键技术之一。针对该振动环境的宽带特性对疲劳失效的强化作用进行了讨论,首先研究影响随机应力疲劳强化效能的相关统计参数,然后分析随机应力的频谱带宽如何影响这些统计参数,最后得到频谱带宽对疲劳强化效能的影响,由此揭示全轴随机振动环境宽频带特性的疲劳强化机理。     

辅助变量法消除纯方位目标运动参数估计偏倚

由于测量噪声与观测阵统计相关,使得纯方位系统伪线性后的最小二乘估计是有偏的.理论分析证明,构造适当的辅助变量可以消除这种偏倚.可以将前3个时刻的测量值的预测值作为辅助变量,从统计上解耦达到消除偏倚的目的.计算机仿真计算的结果表明,该方法相当稳定,受收敛问题的困扰较少,可以达到消除估计有偏的目的,同时提高了对目标参数估计的精度,因此该做法被验证是有效的.     

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     

混沌随机频率步进信号分析与处理

混沌具有类随机性、对初值敏感、易于产生和控制,频率步进信号易于工程实现和处理,结合二者的优势,提出一种基于混沌序列的随机频率步进雷达信号。介绍了信号产生模型,从理论上推导、分析了该信号的模糊函数和互相关函数性能,给出了信号直接相关和先排序存储、后匹配滤波两种回波处理方法。应用四种典型混沌进行数值仿真,并和已有的线性频率步进信号、高斯和均匀随机频率步进信号进行对比分析。结果表明,混沌随机频率步进信号具有较优良的性能,是一种有潜力的雷达信号。     

尺度自适应特征压缩跟踪

为在复杂环境中对目标进行长时间精确跟踪,提出一种尺度自适应特征压缩跟踪算法。通过结构约束性采样,获取不同尺度不同位置的扫描窗,离线计算不同尺度下的稀疏随机感知矩阵。在线跟踪时利用这些矩阵感知对应尺度的图像采样块,实现特征降维,提高运算速度。利用朴素贝叶斯分类器对降维特征判决,在线学习更新分类器参数,找出具有最高分类得分的采样块作为新的跟踪结果,实现跟踪位置及尺度的自适应更新。实验结果表明,该算法能适应目标的基本姿态变化及尺度缩放,不依赖于目标初始跟踪区域尺度选取,跟踪结果具有较强的鲁棒性。     

基于随机集理论的多目标跟踪方法

多目标跟踪问题通常包括目标信号的检测与目标状态的估计,同时还涉及到对探测范围内目标数量的确定。传统的跟踪方法将目标检测、状态估计与数量确定分别使用独立的模块或算法来处理。在这种模式下,每个模块仅考虑测量数据中与其功能直接相关的信息,模块之间没有信息的交互,因而很难得到全局最优的解。基于随机集理论的多目标跟踪方法将场景内的全部目标看作一个全局变量,目标状态与目标测量分别构成各自的随机有限集。从而多目标跟踪问题可以放在一个随机集模型下的贝叶斯滤波框架中研究。在每一个滤波周期内,通过对随机集的处理,实时地估计目标的数量、状态与类型,实现多目标的联合检测、跟踪与识别。     

群决策理论在多机协同空战机动决策中的应用

针对近距空战中多架战机对空中的多个敌对目标进行协同攻击的机动决策问题进行了研究。将群决策理论引入多机协同空战机动决策,首先确定了决策成员与候选方案,然后基于战场态势评估提出了采用风险决策准则的偏好排序确定方法,给出了集结偏好的序数型群决策方法。在不同空战想定条件下进行仿真,结果表明,该方法合理、可行,具有良好的应用前景。