一种连续修正速度方向的导引方法

考虑制导炮弹由身管武器发射，其飞行控制能力和导引信息量有限，基于预测落点位置偏差量来修正速度方向并在控制时间内连续分配导引指令的思想，提出了一种新的三维末制导方法。根据非线性弹道方程组的级数解预测弹丸落点位置，得到落点与目标的偏差，并提出了两种通过此偏差解算当前速度方向修正量的方法。取剩余飞行时间为修正时间，通过将速度方向修正量分配到整个剩余导引段建立了加速度修正公式，以减小导引指令饱和的可能性。通过连续地预测落点和分配加速度指令来实时地导引飞行。仿真结果表明：该导引方法简单可行，精度高，对控制能力要求较低，且具备较好的制导效果和毁伤效果，为该体制制导炮弹的应用提供参考依据。     

某飞行仿真系统虚拟教员软件研究

针对训练基地飞行模拟改装训练的特点和需求,提出了一种智能评分和虚拟教员实时提示方法。根据训练大纲建立模拟飞行课目专家库,建立分阶段优化评估模型,对不同阶段的关键评价指标进行综合评分,同时依据专家库和模拟飞行参数实时对飞行学员的操作提出虚拟建议,以文字和声音的方式发送给飞行员,最后给出评分结果。虚拟教员能对模拟训练进行实时干预、指导,方便学员进行自主训练,受到训练基地飞行员尤其是新训改装飞行员的广泛欢迎。     

Growth recovery after civil conflict: a fractional integration approach

Using recent econometric techniques based on fractional integration, we find that developing countries recover their economic growth faster than developed countries in response to a shock. Following this methodology, we find that longer civil conflicts are associated with a faster recovery process. We further investigate this issue by exploring correlations with components of GDP, military spending, institutions and aid and find heterogeneous effects of these channels by duration of conflict. Higher government spending is correlated with faster recoveries post longer conflicts, and higher consumption spending is linked to faster recoveries following shorter conflicts. Military spending appears to be driving the government expenditure that makes countries recover from longer conflicts. More democratic institutions are associated with faster recoveries post short wars but slower recoveries following long wars.     

基于RCS序列的助推段弹道导弹识别

在弹道导弹的助推段,通过低分辨率雷达得到RCS序列作为识别的重要信息。由于运动特性和电磁散射特性的差异,弹道导弹在助推段的RCS序列与其他目标相比具有可识别性,但需要对其RCS序列进行处理。基于目标识别技术,详细阐述能从RCS序列中提取出的特征参数,并通过直方图、N点截图等方法给出了直观的反映。最后,将弹道导弹助推段特征与飞机、燃料舱等典型目标进行对比,得到可以作为识别参量的特征参数,并通过类内类间距离验证了有效性。     

一种高速实时数据采集处理系统设计

针对目前高速数据采集中的实时性和同步性问题,提出了一种高速实时数据采集处理设计方案。根据上述方案进行了系统的硬件和软件设计,该系统以FPGA器件作为下位机控制核心,设计了时钟同步、数据采集、数据处理、数据缓存、数据通讯等功能模块;整个系统采用ARM微处理器作为上位机控制核心,基于嵌入式Linux 2.6内核进行软件编程,负责向FPGA发送设置参数和控制指令,同时对数据前端采样和处理数据进行存储、显示、统计等。经测试验证,该方案具有高速率、高精度、同步测量、实时处理、体积小、功耗低等优点。     

时间管理在实时仿真中的改进

时问是分布仿真中的核心概念;时间管理是分布交互仿真的关键技术.探讨了分布交互仿真中高层体系结构(HLA)的时间管理机制,针对HLA在实时系统仿真方面的不足,分析其原因,提出了时间管理在实时仿真中的改进方法,对HLA在实时系统仿真中的应用有一定的参考价值.     

Estimating failure time distribution and its parameters based on intermediate data from a Wiener degradation model

Instead of measuring a Wiener degradation or performance process at predetermined time points to track degradation or performance of a product for estimating its lifetime, we propose to obtain the first‐passage times of the process over certain nonfailure thresholds. Based on only these intermediate data, we obtain the uniformly minimum variance unbiased estimator and uniformly most accurate confidence interval for the mean lifetime. For estimating the lifetime distribution function, we propose a modified maximum likelihood estimator and a new estimator and prove that, by increasing the sample size of the intermediate data, these estimators and the above‐mentioned estimator of the mean lifetime can achieve the same levels of accuracy as the estimators assuming one has failure times. Thus, our method of using only intermediate data is useful for highly reliable products when their failure times are difficult to obtain. Furthermore, we show that the proposed new estimator of the lifetime distribution function is more accurate than the standard and modified maximum likelihood estimators. We also obtain approximate confidence intervals for the lifetime distribution function and its percentiles. Finally, we use light‐emitting diodes as an example to illustrate our method and demonstrate how to validate the Wiener assumption during the testing. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

空间目标RCS序列的R/S分析

RCS包含了目标丰富的信息.分析了空间目标RCS序列产生混沌的机理,并非线性理论中的功率谱法引入空间目标RCS序列的分析中,用重整标度分析法(R/S)分析了空间目标RCS序列的混沌特性,仿真结果表明,与旋转目标相比,三轴稳定目标RCS序列较复杂和不规则,这与实际分析的情况相符合,证明了该方法的有效性.     

基于时间序列分析的火灾发生规律研究

在时间序列分析建模思想的基础上,基于全国2007年24小时火灾起数建立时间序列模型,对火灾发生趋势进行分析,并从预防控制时间上提出相应的防控建议。     

The effects of model parameter deviations on the variance of a linearly filtered time series

We consider a general linear filtering operation on an autoregressive moving average (ARMA) time series. The variance of the filter output, which is an important quantity in many applications, is not known with certainty because it depends on the true ARMA parameters. We derive an expression for the sensitivity (i.e., the partial derivative) of the output variance with respect to deviations in the model parameters. The results provide insight into the robustness of many common statistical methods that are based on linear filtering and also yield approximate confidence intervals for the output variance. We discuss applications to time series forecasting, statistical process control, and automatic feedback control of industrial processes. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010