对辐射源信号到达角的自适应跟踪估计

为提高信号到达角(AOA)的测量精度,采用修正的窗函数加权平均算法和基于机动加速度的非零均值时间相关模型的自适应卡尔曼滤波算法,将信号到达角的变化轨迹看作是一种做加速度机动的运动,实现对连续变化信号到达角的参数估计.计算机仿真验证了算法的有效性和可行性,证明该方法有一定的应用价值.     

一种新的时频分析方法

首先分析了传统时频分析方法的特点及其局限性,而后评述了一种最新的适用于非平稳、非线性信号的通用的时频分析方法--基于经验的模式分解及希尔伯特变换谱,指出了该方法需进一步研究的有关问题     

基因表达缺失值的加权回归估计算法

在基因芯片实验中,数据缺失客观存在,并在一定程度上影响芯片数据后续分析结果的准确性。在不增加实验次数的情况下,缺失值估计是降低缺失数据对后续分析影响的有效方法。利用相似性信息的核加权函数来实现缺失值回归估计的局部化,提出了基于加权回归估计的基因表达缺失值估计算法。在两个不同类型的基因芯片数据上,将新方法与几种已知的方法进行了比较分析。实验结果表明,新的估计算法具有比传统缺失值估计算法更好的稳定性和估计准确度。     

多输出性能下的重要性测度指标及其求解方法

针对基于马氏距离的重要性测度存在的问题,提出了基于谱分解加权摩尔彭罗斯马氏距离的重要性测度指标,通过构造多输出协方差阵的广义逆矩阵以及谱分解的策略,有效解决了协方差阵求逆奇异情况以及由于未能充分考虑多输出之间的相互关系而导致的错误识别重要变量的问题,克服了基于马氏距离指标的局限性。数值算例与工程算例结果表明:所提重要性测度可以更加准确地获得输入变量对结构系统多输出性能随机取值特征贡献的排序,从而为可靠性设计提供充分的信息。     

Parallel machine scheduling with eligibility constraints: A composite dispatching rule to minimize total weighted tardiness

We study a parallel machine scheduling problem, where a job j can only be processed on a specific subset of machines M_j, and the M_j subsets of the n jobs are nested. We develop a two‐phase heuristic for minimizing the total weighted tardiness subject to the machine eligibility constraints. In the first phase, we compute the factors and statistics that characterize a problem instance. In the second phase, we propose a new composite dispatching rule, the Apparent Tardiness Cost with Flexibility considerations (ATCF) rule, which is governed by several scaling parameters of which the values are determined by the factors obtained in the first phase. The ATCF rule is a generalization of the well‐known ATC rule which is very widely used in practice. We further discuss how to improve the dispatching rule using some simple but powerful properties without requiring additional computation time, and the improvement is quite satisfactory. We apply the Sequential Uniform Design Method to design our experiments and conduct an extensive computational study, and we perform tests on the performance of the ATCF rule using a real data set from a large hospital in China. We further compare its performance with that of the classical ATC rule. We also compare the schedules improved by the ATCF rule with what we believe are Near Optimal schedules generated by a general search procedure. The computational results show that especially with a low due date tightness, the ATCF rule performs significantly better than the well‐known ATC rule generating much improved schedules that are close to the Near Optimal schedules. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 249–267, 2017     

基于改进平方根UKF双向滤波的单站无源定位算法

针对单站无源定位可观测性弱、观测噪声大而导致的定位精度低、稳定性差和收敛速度慢等问题,在结合平方根无迹卡尔曼滤波(Square-Root Unscented Kalman Filter,SRUKF)以及后向平滑思想的基础上,提出了一种改进SRUKF的双向滤波算法。该算法采用Q-R分解的形式,使用误差协方差的平方根代替协方差参与递推运算,提高了算法的稳定性与运算效率。同时,该算法对状态向量进行扩维,将过程噪声与观测噪声通过非线性系统传播,降低了噪声对滤波精度的影响,并利用当前时刻滤波结果通过Rauch-Tung-Striebel(RTS)后向平滑得到再次前向滤波更高精度的起始值,提高了算法的定位精度与收敛速度。仿真结果表明,新算法在保证实时性的基础上改善了单站无源定位的性能。     

一种快速确定GPS整周模糊度的方法

GPS初始整周模糊度的求解是利用载波相位进行测量时的关键问题,采用了对系数矩阵进行QR分解的方法,用以降低矩阵的维数。模糊度搜索时,针对Z变换可能会引入多余误差,采用了对称三角分解法对协方差矩阵进行去相关处理。实验与仿真结果表明,定位误差在0.5 cm以内,方位角和仰角误差在0.1°以内。     

Stochastic scheduling subject to machine breakdowns: The preemptive‐repeat model with discounted reward and other criteria

We consider the problem of scheduling a set of jobs on a single machine subject to random breakdowns. We focus on the preemptive‐repeat model, which addresses the situation where, if a machine breaks down during the processing of a job, the work done on the job prior to the breakdown is lost and the job will have to be started from the beginning again when the machine resumes its work. We allow that (i) the uptimes and downtimes of the machine follow general probability distributions, (ii) the breakdown process of the machine depends upon the job being processed, (iii) the processing times of the jobs are random variables following arbitrary distributions, and (iv) after a breakdown, the processing time of a job may either remain a same but unknown amount, or be resampled according to its probability distribution. We first derive the optimal policy for a class of problems under the criterion to maximize the expected discounted reward earned from completing all jobs. The result is then applied to further obtain the optimal policies for other due date‐related criteria. We also discuss a method to compute the moments and probability distributions of job completion times by using their Laplace transforms, which can convert a general stochastic scheduling problem to its deterministic equivalent. The weighted squared flowtime problem and the maintenance checkup and repair problem are analyzed as applications. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

最小交互熵谱估计在反坦克导弹系统仿真模型验证中的应用

针对反坦克导弹系统动态过程仿真的输出具有短时序、低信噪比的特点 ,研究了应用最小交互熵谱估计验证导弹系统仿真模型有效性的方法 ,并结合某型号滚转稳定的反坦克导弹系统的仿真数据和理论计算数据给出了最小交互熵谱估计的应用结果。     

Approximation of multiclass queueing networks with highly variable arrivals under deterministic routing

In this paper, we present the heavy‐traffic bottleneck phenomenon under multiclass deterministic routing and discuss how it can be addressed by decomposition approximation. Examples show that Bitran and Tirupati's method and Whitt's enhancements for deterministic routing may not properly account for this phenomenon. We propose refinements to these methods based on Whitt's variability functions. Results of numerical experiments on simple networks and semiconductor manufacturing process show significant improvement in the approximation of expected waiting time at bottleneck stations. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.