基于占有率的信号相位交通状态实时判别模型

在国内交通检测手段的现实背景下,各种道路交通状态判别模型的可靠性和实用性一直不足。因此基于车道战略检测器和战术检测器的时间占有率提出了一种新的实用的相位交通状态判别模型,其中包括检测器的布设,占有率阈值的确定,相位交通状态的判别方法。通过VISSIM4.2仿真实验证明,该模型可以准确地判定符合人们主观判断的相位交通状态,并且可以很好地应用目前普遍采用的检测手段,实用性强。     

基于锁相环的GNSS授时接收机钟差校准算法

GNSS(全球卫星导航系统)授时接收机利用卫星导航信号获取钟差并校准本地时钟,从而与GNSS系统时间同步。提出了全新的基于锁相环的GNSS授时接收机钟差校准算法,将钟差校准过程等效为传统的锁相环模型,鉴相器的功能由PVT(位置、速度与时间)解算实现,压控振荡器的功能由本地时间调整接口实现,环路将本地秒相位与GNSS系统的秒相位锁定。分析了环路总误差的组成,以及环路参数与各误差项的关系,给出了误差最小的环路优化设计准则。在北斗二号卫星导航接收机平台上进行了对比实验,验证了算法的有效性。     

距离伪量测的空基平台单站无源定位算法

针对空中观测单站平台对海面、地面目标的测向定位问题,提出一种基于距离伪量测的最小二乘-不敏卡尔曼滤波(LSE-UKF)两阶段滤波算法。首先利用单次的测角信息以及目标离地高度的约束条件计算出目标的距离,采用最小二乘法对距离量进行滤波,得到较为准确的距离量。进一步将滤波所得距离量视为伪量测信息,结合观测所得的角度信息进行不敏卡尔曼滤波。仿真实验表明该算法提高了定位精度并且具有较快收敛速度。     

一种实时对中监测装置原理及误差分析研究

设计出了一种可实现实时对中监测的装置。该装置可以在静态和设备运行时进行对中状态监测,还可对设备或轴系引起的对中状态改变量进行测量。介绍了该装置的结构原理,并对其结构误差进行了讨论,结果表明,该装置的误差很小,可以很好满足工程需要。同时,还对该装置的装配误差进行了分析。     

Hilbert谱分析和平稳度

提出了本征模式函数IMF成员相应的幅度及频率时间函数的计算方法。由函数的Hilbert谱可获得相关的边缘谱,边缘谱确定了几乎连续的能量分布,从而提供了通过每个频率值测量总能量的方法。根据能量-频率-时间分布,就可以定量确定平稳性,平稳性是物理过程的一个复杂属性,其由平稳度DS和统计平稳度DSS进行度量,同时给出了DS和DSS的计算公式。     

基于半实物仿真的HLA／RTI关键技术研究

分析了基于HLA/RTI的半实物仿真中实践管理、数据收集能力、RTI通用性以及网络传输安全等问题,研究了新的时间管理策略,提出了合理设置lookahead的算法,设计了数据收集的层次框架,并制定了研发RTI的通用原则和安全有效的网络传输方案,为现代半实物系统仿真提供了理论借鉴。     

电子时间引信解除保险距离试验研究

通过测量弹丸炮口速度和引信解除保险时间的方法得出电子时间引信远解距离。在介绍某型电子时间引信实现远距离解除保险的方法和机构工作过程的同时,对远解距离进行理论分析,并对试验引信改装的实现方法作了详细说明。在此基础上,进行了电子时间引信解除保险距离测试试验并对试验结果作了分析。     

Dynamic lot‐sizing model with production time windows

We consider a dynamic lot‐sizing model with production time windows where each of n demands has earliest and latest production due dates and it must be satisfied during the given time window. For the case of nonspeculative cost structure, an O(nlogn) time procedure is developed and it is shown to run in O(n) when demands come in the order of latest production due dates. When the cost structure is somewhat general fixed plus linear that allows speculative motive, an optimal procedure with O(T⁴) is proposed where T is the length of a planning horizon. Finally, for the most general concave production cost structure, an optimal procedure with O(T⁵) is designed. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

On the effectiveness of top‐down strategy for forecasting autoregressive demands

We investigate the relative effectiveness of top‐down versus bottom‐up strategies for forecasting the demand of an item that belongs to a product family. The demand for each item in the family is assumed to follow a first‐order univariate autoregressive process. Under the top‐down strategy, the aggregate demand is forecasted by using the historical data of the family demand. The demand forecast for the items is then derived by proportional allocation of the aggregate forecast. Under the bottom‐up strategy, the demand forecast for each item is directly obtained by using the historical demand data of the particular item. In both strategies, the forecasting technique used is exponential smoothing. We analytically evaluate the condition under which one forecasting strategy is preferred over the other when the lag‐1 autocorrelation of the demand time series for all the items is identical. We show that when the lag‐1 autocorrelation is smaller than or equal to 1/3, the maximum difference in the performance of the two forecasting strategies is only 1%. However, if the lag‐1 autocorrelation of the demand for at least one of the items is greater than 1/3, then the bottom‐up strategy consistently outperforms the top‐down strategy, irrespective of the items' proportion in the family and the coefficient of correlation between the item demands. A simulation study reveals that the analytical findings hold even when the lag‐1 autocorrelation of the demand processes is not identical. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007.     

Exact expected values of variance estimators for simulation

We formulate exact expressions for the expected values of selected estimators of the variance parameter (that is, the sum of covariances at all lags) of a steady‐state simulation output process. Given in terms of the autocovariance function of the process, these expressions are derived for variance estimators based on the simulation analysis methods of nonoverlapping batch means, overlapping batch means, and standardized time series. Comparing estimator performance in a first‐order autoregressive process and the M/M/1 queue‐waiting‐time process, we find that certain standardized time series estimators outperform their competitors as the sample size becomes large. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007