防空导弹尾追拦截目标的遭遇点预测方法

为充分发挥导弹武器系统的全向拦截能力,防空导弹需要面对拦截发射时即处于尾追逃逸态势目标的问题。结合防空导弹任务特点,设计了一种兼顾迎击、尾追拦截态势的遭遇点预测方法。根据导弹与目标在发弹时刻和拦截过程中的相对运动关系,建立常规迎击态势下的遭遇点预测模型。针对尾追拦截的特殊情况,分析预测模型对弹目相对运动关系描述的适用性,并进一步研究目标初始参数对预测模型收敛性的影响。在此基础上优化运动几何关系描述模型,结合收敛条件设计迭代算法,形成尾追拦截态势下遭遇点的预测方法。该方法修正了目标穿越发射点上空引起的模型适用性问题。仿真结果表明:迭代算法对迎击、尾追目标态势均快速收敛,预测精度满足工程应用要求,为导弹全向拦截时的遭遇点预测提供了有效的解决途径。     

梯度投影法与改进简约梯度法的关系

对带有线性等式和不等式约束非线性规划提出一种改进简约梯度法。通常的方法需增加松弛变量将不等式约束化为等式约束，从而增加原问题的维数。新方法通过引入一个松弛向量，不增加原问题的维数。文中给出了改进的简约梯度法与Ｒｏｓｅｎ’ｓ梯度投影法之间关系。     

Measuring reliability under epistemic uncertainty:Review on non-probabilistic reliability metrics

In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used non-probabilistic reliability metrics are critically reviewed, i.e., evidence-theory-based reliability metrics, interval-analysis-based reliability metrics, fuzzy-interval-analysis-based reliability metrics, possibility-theory-based reliability metrics (posbist reliability) and uncertainty-theory-based reliability metrics (belief reliability). It is pointed out that a qualified reli-ability metric that is able to consider the effect of epistemic uncertainty needs to (1) compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and (2) satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications. The five commonly used non-probabilistic reliability metrics are compared in terms of these two properties, and the comparison can serve as a basis for the selection of the appropriate reliability metrics.     

A novel variable-lag probability hypothesis density smoother for multi-target tracking

It is understood that the forward-backward probability hypothesis density (PHD) smoothing algorithms proposed recently can significantly improve state estimation of targets. However, our analyses in this paper show that they cannot give a good cardinality (i.e., the number of targets) estimate. This is because backward smoothing ignores the effect of temporary track drop- ping caused by forward filtering and/or anomalous smoothing resulted from deaths of targets. To cope with such a problem, a novel PHD smoothing algorithm, called the variable-lag PHD smoother, in which a detection process used to identify whether the filtered cardinality varies within the smooth lag is added before backward smoothing, is developed here. The analytical results show that the proposed smoother can almost eliminate the influences of temporary track dropping and anomalous smoothing, while both the cardinality and the state estimations can significantly be improved. Simulation results on two multi-target tracking scenarios verify the effectiveness of the proposed smoother.     

Reliability analysis based on a novel density estimation method for structures with correlations

Estimating the Probability Density Function (PDF) of the performance function is a direct way for structural reliability analysis,and the failure probability can be easily obtained by integration in the failure domain.However,efficiently estimating the PDF is still an urgent problem to be solved.The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation,whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs.While in fact,structures with correlated inputs always exist in engineering,thus this paper improves the maximum entropy method,and applies the Unscented Transformation (UT) technique to compute the frac tional moments of the performance function for structures with correlations,which is a very efficient moment estimation method for models with any inputs.The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations.Besides,the number of function evaluations of the proposed method in reliability analysis,which is determined by UT,is really small.Several examples are employed to illustrate the accuracy and advantages of the proposed method.     

非结构混合网格高雷诺数流动计算中一种改进的LU-SGS隐式格式(英文)

The lower-upper symmetric Gauss-Seidel (LU-SGS) implicit relaxation has been widely used because it has the merits of less dependency on grid topology,low numerical complexity and modest memory require...     

基于误差估计的伴随网格自适应方法

网格自适应是一种有效减少解与网格相关性,改善计算结果的重要途径。给出了一种基于误差估计的伴随网格自适应计算技术,定义了基于误差估计的自适应准则,给出了非结构四面体网格单元细化剖分规则,以及一般的网格自适应流程,介绍了一种基于Rechardson外推的网格收敛技术,运用本文提供的方法对NLR7301翼型进行了数值计算研究,数值试验表明给出的网格自适应具有较高的可有效改善计算结果。     

定义于Hilbert空间中星形集上的非扩张映像

假设H是一个实Hilbert空间,C是H的一个非空弱闭星形子集,T：C→C为非扩张映像。研究了T的不动点的存在性及其迭代算法的收敛性,本文结果推广了关于非扩张映像的已有相关结果。     

夹具定位误差的概率分析计算

用概率方法分析夹具的定位误差,并与常用的极值法进行比较,从而得出概率分析方法的特点。     

多变量自校正控制的虚拟等价系统

给出多变量确定性对象自校正控制系统的虚拟等价系统分析方法和结论,用以理解、分析和判别其稳定性、收敛性．得出了不依赖于参数估计算法和控制律的通用性判据。作为本文判据的应用,在不使用关键性技术引理的前提下,推出了Goodwin等人关于直接一步超前自校正控制系统的稳定性和收敛性结果。