Robust TDOA/FDOA estimation from emitter signals for hybrid localization using UAVs

This paper considers the time difference of arrival (TDOA) and frequency difference of arrival (FDOA)estimation problem for joint localization using unmanned aerial vehicles (UAVs),involving range migration (RM) and Doppler ambiguity within observation interval.A robust estimation method based on interpolation and resampling is proposed.Specifically,the interpolation artificially increases the pulse repetition frequency (PRF).After that,the resampling eliminates the coupling between range frequency and slow time.Finally,a coherent integration step based on inverse discrete Fourier transform (IDFT) is used to achieve parameter estimation and suppress the grating lobes caused by interpolation.The proposed method could be efficiently implemented by fast Fourier transform (FFF),inverse FFT (IFFF) and non-uniform FFT (NUFFT) without parameter searching procedures.Numerical experiments indicate that the proposed method has nearly optimal anti-noise performance but much lower computational complexity than the maximum likelihood estimator,which makes it more competitive in practical applications.     

The Cyprus puzzle and the Greek - Turkish arms race: Forecasting developments using genetically evolved fuzzy cognitive maps

The scope of this paper is to forecast the extent to which a settlement of the Cyprus issue may be possible given the decisions taken during the Copenhagen EU summit. It aims, in addition, at investigating the possibilities of improvement in Greek-Turkish relations which may lead, in turn, to reducing the arms race between the two countries. The paper uses a Genetically Evolved Certainty Neuron Fuzzy Cognitive Map algorithm to consider a number of scenarios examining the possible reactions of all sides involved in the Cyprus issue, namely Greece, Turkey, Cyprus, the Turkish-Cypriot community and the international environment. All simulation exercises suggest that the Greek and the Cypriot side should not necessarily rely on the decisions taken during the Copenhagen summit conference. The forecasts point out, in addition, that the optimism of the Greek government concerning the outlook of its relations with Turkey, and a subsequent reduction of the arms race against it, is far from being justified.     

Domestic political and external security determinants of the demand for greek military expenditure

By European Union and NATO standards, Greece consistently allocates substantial human and material resources to defence. The Greek defence burden (i.e. military expenditure as a share of GDP) has invariably been appreciably higher than the EU and NATO averages. The paper applies an autoregressive distributed lag model (ARDL) to present cointegrated estimates of the demand function for Greek military expenditure, in which domestic political factors and external security determinants are incorporated. Our empirical findings suggest that Greek defence spending over the period 1960-1998 has been influenced by both external security concerns, namely Turkey, as well as changes in the domestic political scene.     

复杂电磁环境下通信抗干扰的信息筛选算法

根据复杂电磁环境下通信联络的特点,基于大规模通信数据的涌现,采用一种能够在大量干扰和背景信号中筛选出有用信息的算法。通过对覆盖算法的研究,利用概率理论对其算法进行了优化和改进,为应用覆盖算法构建了一个实用的有限混合的概率模型,而后采用最大似然的原理进行优化计算,实现覆盖算法的优化实用化。将这种数据筛选算法应用到受到干扰条件下短波通信的海量信息的挖掘中,取得了良好的效果,验证了其有效性。     

基于CMM的指挥控制能力成熟度模型

分析了美军与北约等外军对指挥控制能力成熟度模型的研究现状,借鉴软件生产能力成熟度模型(CMM)的相关方法,提出了我军指挥控制能力成熟度的研究思路和指挥控制能力成熟度模型总体架构与评价方法,阐述和展望了该模型的应用。     

基于状态空间模型的航天器装配角偏误差研究

装配过程的误差建模是分析装配误差的重要手段之一。通过分析影响航天器装配结果的尺寸和形位误差、装夹定位误差,将其装配的偏差源分为夹具装夹误差和舱段制造误差两类。并将不同形式的误差通过虚拟夹具的概念进行了统一的表达,进而基于误差流理论针对航天器舱段建立其误差传播的状态空间模型,求出了该过程的状态空间表达式,应用该模型对装配过程中的角偏误差进行了分析。将分析得到的结果同蒙特卡洛仿真的结果进行了比较,两种方法的相对误差小于3%,说明了该方法的可行性。该方法的优势在于它不仅可以分析复杂装配过程,还可以对各工位的装配效果进行观测,从而进行向后分析。     

基于抽象隐马尔可夫模型的CGF路径规划识别

路径规划识别是一种以位置信息为输入的在线识别。为了使CGF能在仿真中识别对手的路径和终点目标,在分析路径规划层次的基础上引入了抽象隐马尔可夫模型的识别框架。针对标准模型在对手更改终点目标和自上而下规划时无法识别的问题,提出了一种顶层策略可变的抽象隐马尔可夫模型。为模型的顶层策略增加初始分布和策略终止变量,更改了策略终止变量间的依赖关系,使下层策略能被强制终止。给出了改进后DBN结构,并通过推导条件概率更新和RB变量抽样流程实现了模型的近似推理。仿真实验表明,改进模型能准确识别给定环境下的各类典型航迹,不仅在终点目标不变时能较好地维持标准模型的识别准确率,在提供足够的观测数据后还能很好地解决变目标识别问题。     

力导向模型的复杂网络社区挖掘算法

在复杂网络中发现和刻画社区结构是近年来复杂网络研究的重点方向之一。提出了一种社区挖掘的新思路,即根据力导向模型的原理,通过计算社区与节点之间的作用力来决定节点的社区归属。根据该思路设计了基于力导向模型的算法框架FDCD(Force-directed Community Detect),并利用FR模型、KK模型、LL模型和Q模型进行了验证。实验表明,基于FDCD算法框架的多种不同算法不仅能较好地识别社区结构,而且基于LL模型的FDCD算法达到了线性计算复杂度,能适用于大规模网络的社区挖掘。     

导弹攻防对抗仿真中的分布表现环境设计

本文针对导弹攻防对抗仿真的特殊需求，讨论了分布表现环境中的若干问题，提出了基于表现模型的、支持层次化表现的系统设计方案。     

基于HLA/RTI 的仿真系统设计

结合雷达电子对抗仿真实例，论述了基于ＨＬＡ／ＲＴＩ的分布交互式多机仿真系统的体系结构、底层通信网络、运行支持系统、仿真应用对象模型和仿真运行管理及其设计与实现问题。