建模仿真主计划及其关键技术

综述了建模仿真主计划 (MSMP)的目的和内容 ,着重阐述该计划中的公共技术框架 ,分析该计划对军事领域内建模仿真活动的影响 ,并对其中某些关键技术问题提出了解决思路或方法     

Parametric study of single confined fragment launch explosive device

In this article, parametric study of single confined fragment launch device was carried out. The configuration proposed was further studied to derive the empirical relationship for effect of fragment size, charge size, confinement thickness on fragment velocity. The simulations were carried out using ANSYS-AUTODYNE explicit solver. Fragment velocities were estimated as a function of different parametric combinations of explosive quantities, charge length to diameter ratio, fragment height to diameter ratio, confinement thickness, fragment material and fragment mass. The data was further converted to charge to metal ratio under fragment and confinement. It was observed that, increase in confinement thickness, charge quantity and decrease in fragment height increases the fragment velocity. It is also noted that, charge to metal mass ratio under fragment significantly affects the fragment velocity. At the end, an empirical relationship for fragment velocity interms of all these parameters was established. Using these relations, two velocities 1831.92 m/s and 2523.9 m/s required for NATO STANAG 4496 IM test were estimated. The design parameters for these velocities are presented. Also, the results estimated using the empirical relationship has been compared with published experimental data. Error in the predicted velocities is within the acceptable range. The empirical relationship proposed will be useful for finalization of design of the fragment launch device.     

基于混合矩的多输出模型确认指标研究

针对随机不确定性条件下多输出计算模型与物理实验数据之间一致性难以量化度量这一问题,本文提出一组新的基于混合矩的多输出模型确认指标。在不确定情况下,同时考虑到多维输出之间的相关关系和单输出的均值,构建了由多输出数学期望列阵和协方差矩阵组成的多输出模型确认局部混合矩指标和全局混合矩指标。其中局部混合矩指标包括绝对指标(LA-3M)和相对指标(LR-3M),它们适合固定位置的多输出局部模型确认;全局混合矩指标也包括绝对指标(GA-3M)和相对指标(GR-3M),它们适合多点位置的多输出全局模型确认。通过数字算例和工程算例,并与PIT和t-pooling 面积指标进行对比,结果表明本文所提指标可行有效,能够方便地度量计算模型和物理实验之间的差异程度。     

Defence R&D expenditure: The crowding-out hypothesis

The impact of defence expenditure on the economy has been widely studied through different types of models. However, the results from these studies have not reached definitive conclusions, and have left a gap in the analysis of the impact of defence R&D expenditure at the economy level. Defence R&D has specific characteristics, which lead to market failures: public good, high risk and uncertainty, national security. Also, defence R&D creates two types of externalities: negative (crowding-out), and positive (spin-off). Crowding-out is the major economic debate about defence R&D. This paper analyses the crowding-out hypothesis by applying three types of models for the UK case: supply, demand, and demand-supply models. From these three models the most reliable is chosen and applied to the individual cases of France, Germany, Japan and USA. The paper also reports the results for the pooled data of these five countries, and for four error component models. The results from estimating such models shed light on the defence R&D crowding-out hypothesis.     

Asymmetric effects of military expenditure between Turkey and Greece

One of the major topics of the defense economics literature regarding Turkey and Greece has been the empirical modeling of various aspects of arms racing. However, despite a considerable amount of research, little evidence has been found in favor of an arms race between the two countries. In the literature, this failure of applied studies has been attributed, among other reasons, to the sensitivity of the results to the underlying model specification, to small sample size, and to measurement issues. This study uses novel, nonlinear, models to investigate the possible relationship between the military expenditures of the two countries. It is assumed that if there are two regimes characterizing the low (or negative) and high-growth military expenditure periods, the growth rates of one country's military expenditure may have distinct effects on the military expenditure regimes of the other country or may contribute to the change from one regime to another. The nonlinear models examined are Smooth Transition Regression models (STRs). Strong evidence of nonlinearity for Greece is found, with asymmetry relating to two distinct regimes through lagged Turkish military expenditure changes.     

The Demand for Turkish Defence Expenditure

Although a number of studies concerning Turkish defence-growth relation have been published in recent years, little attention is given the demand for Turkish defence expenditure. This is an important issue for understanding which variables contribute to the determination of the demand for military expenditure. However, it is difficult to develop a general theory or a standard empirical approach for the determination of the demand military expenditure. This study models and estimates the demand for Turkish defence expenditure for the period 1951-1998 using autoregressive distributed lag approach to cointegration (ARDL) following the methodology outlined in Pesaran and Shin (1999). This procedure can be applied regardless of the stationary properties of the variables in the sample and allows for inferences on long-run estimates, which is not possible under alternative cointegration procedures. The findings suggest that Turkish defence spending is determined by NATO's defence spending, Greece's defence spending and some security considerations.     

CODE新光压模型对北斗混合导航星座精密轨道确定的影响分析

基于国防科技大学自主研制的卫星定轨软件工具包NUDTTK，分析了CODE新光压模型EECOM对北斗二代混合导航星座精密轨道确定的影响。研究表明：对GEO卫星而言，EECOM模型能够明显改善定轨精度，相比于传统的ECOM-9和ECOM-5模型，卫星激光测距检核精度分别提高17.4%和35.1%。对IGSO和MEO卫星而言，采用ECOM-5模型的定轨精度要优于EECOM和ECOM-9模型，新光压模型EECOM并不能有效改善IGSO和MEO卫星的定轨精度。与IGS数据分析中心WHU、GFZ和CODE的轨道产品互比对结果（3D RMS）显示：目前，国防科技大学北斗精密轨道产品中，GEO卫星的定轨精度为1~4 m，IGSO卫星的定轨精度为25~30 cm，MEO卫星的定轨精度为10~20 cm。     

Does Terrorism Increase after a Natural Disaster? An Analysis based upon Property Damage

Does an emergency such as a natural disaster lead to a surge of terrorism? This paper contributes to the emerging literature on this issue. We consider the experience of 129 countries during the period 1998–2012 to determine the effect of a natural disaster on both domestic as well as transnational terrorism. We also control for endogeneity using expenditure on health care and land area in a country as instruments. In contrast to the existing literature, we measure the extent of terrorism by the value of property damage. The results indicate that after natural disasters, (a) transnational terrorism increases with a lag, and (b) a statistically significant impact on domestic terrorism is not observed.     

基于EMD和二叉树支持向量机的调制识别算法

针对数字调制模式识别问题,提出了一种基于经验模式分解(EMD)和二叉树支持向量机的识别算法。该算法通过对数字信号进行经验模式分解,利用分解得到的本征模式函数构造分类特征,再运用二叉树支持向量机作为分类器实现了6种信号的分类。仿真结果表明,该算法具有很好的识别性能。     

A novel signal feature extraction technology based on empirical wavelet transform and reverse dispersion entropy

Feature extraction is an important part of signal processing, which is significant for signal detection, classification, and recognition. The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields. Reverse dispersion entropy (RDE) proposed by us recently, as a nonlinear dynamic analysis method, has the advantages of fast computing speed and strong anti-noise ability, which is more suitable for measuring the complexity of signal than traditional permutation entropy (PE) and dispersion entropy (DE). Empirical wavelet transform (EWT), based on the theory of wavelet analysis, can decompose a complex non-stationary signal into a number of empirical wavelet functions (EWFs) with compact support set spectrum, which has better decomposition performance than empirical mode decomposition (EMD) and its improved algorithms. Considering the advantages of RDE and EWT, on the one hand, we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy; on the other hand, we use RDE as the features of EWFs to improve the signal separability and stability. Finally, we propose a novel signal feature extraction technology based on EWT and RDE in this paper. Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals. Moreover, it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.