智能时代的军事训练变革

随着智能技术的发展,人类已逐步迈入智能时代,而智能时代催生了军事训练变革。本文从智能技术影响军事训练典型领域的角度,分析了智能时代背景下,以大数据和人工智能为核心的智能技术,如何影响军事训练的理念、内容、方式及管理,并催生了这些领域的变革。研究表明,智能时代发展背景下,军事训练理念将更加先进,训练内容更加融合,训练方式更加有效,训练管理更加精准。     

改进BAS-TIMS算法在空战机动决策中的应用

针对当前空战机动决策精确度低、实时性差的缺点,对天牛须搜索-战术免疫机动系统(Beetle Antennae Search-Tactical Immune Maneuver System, BAS-TIMS)算法进行改进,并应用于空战机动决策中。增加左爬升、右爬升、左俯冲、右俯冲4种机动,对传统的机动策略库进行扩充,设计了11种基本机动策略并给出了相应的控制方法。基于距离、高度、速度、角度和战机性能优势函数,利用非参量法构造战机机动决策综合优势函数。针对天牛须搜索算法在全局搜索和收敛速度上存在的缺陷,引入蒙特卡洛概率迭代的方法对算法进行改进,并和战术免疫机动系统进行融合,将改进的BAS-TIMS算法用于空战机动决策。设计算例进行仿真分析,并将结果和博弈论法、改进共生生物免疫进化算法、传统BAS算法和传统TIMS模型的计算结果进行对比,验证所提算法的有效性。仿真结果表明:改进BAS-TIMS算法在空战机动决策的收敛精度、收敛速度和全局搜索能力上更加具有优势。     

Democratic control of Romanian intelligence after three decades: quis custodiet ipsos custodes?

ABSTRACT

Romania faced one of the most dramatic transitions from authoritarian communism to become a democracy and a member of the North-Atlantic Treaty Organization (NATO) and the European Union (EU). The backbone of building a democratic society has been civilian control of the military. This article briefly describes the norms and institutions of democratic control of the intelligence services in Romania and assesses how the mechanisms of democratic control have worked in practice after almost three decades of reform. We argue that many of the post-1989 reforms have been only superficial implemented and monitored, particularly after Romania joined NATO and the EU. The article concludes that the democratic control of intelligence in Romania is an unfinished business. There are structural shortcomings embedded in the process of democracy consolidation that need to be addressed.     

智能化电子对抗装备发展

当前,智能化武器装备成为世界各国发展的重点,而电子对抗作为新型作战力量将直接影响战争的胜负。文章分析当前电子对抗装备存在的显著不足,论证发展智能化电子对抗装备的迫切性和必要性,明确提出发展智能化电子对抗装备的若干关键技术,阐述智能化电子对抗装备对未来信息化战争的直接影响,以及智能化电子对抗装备未来的发展方向。     

A Question of ‘Government’ Control: Afghanistan DDR Programs Since 2001

Since the fall of the Taliban in late 2001, the Islamic Republic of Afghanistan (GIRoA), the United States, the United Nations, and the International Security Assistance Force (ISAF) have funded and led three different Disarmament, Demobilization, and Reintegration (DDR) programs. Despite a significant investment in time and treasure, all of them have failed to significantly reduce the number of insurgents or arbaki (militia). This article explores why these programs failed despite incorporating ideas from the prominent DDR schools of thought. Utilizing Stathis Kalyvas’ theory of The Logic of Violence in Civil War as a lens, this article argues that GIRoA and ISAF did not have sufficient control of territory to entice insurgents or arbaki to reconcile and/or reintegrate with the government. Further, in areas GIRoA nominally controlled in northern and western Afghanistan, regional powerbrokers who controlled these areas balked at these programs.     

Empirical Biases and Some Remedies in Estimating the Effects of Selective Reenlistment Bonuses on Reenlistment Rates

Researchers have, for decades, been attempting to estimate the effects of Selective Reenlistment Bonuses (SRBs) on the probability of reenlistment for the military services. SRBs are targeted to specific military occupations for which reenlistment rates are lower (or expected to be lower) than what is needed. This article first identifies four primary sources of biases affecting these models: reverse causality from supply shifts (a negative bias), the endogeneity of the decision point causing coded SRBs to be higher for reenlisters than leavers (a positive bias), measurement error (a likely negative bias), and excess supply preventing the full effect of an SRB change to materialize (a positive or negative bias). The report proceeds to develop a model that attempts to address the first two biases. With U.S. Navy data from FY2001-FY2008, I examine the extent to which these two biases are affecting the estimated SRB effects. Despite these corrections, the difficulty of addressing the other biases calls into doubt studies that examine the effects of retention bonuses or even the effects of the structure of military pay in general.     

基于整体变分和数学形态学的空间非合作目标边缘检测

非合作目标不提供已知的目标标识器和敏感器件,无疑增加了检测识别的难度.CCD相机能够提供大量包含有非合作目标的尺寸、形状、相对位置和相对姿态等信息的高分辨率图像,用常规方法进行非合作目标图像分割时,由于空间环境的影响,使得目标的轮廓线非常零碎,常掩埋在杂乱的背景分割线中.为了克服这种问题,提出了一种保持边界的整体变分方法和数学形态学相结合的方法.先用整体变分方法对图像进行平滑的同时可以最大限度地保留图像中的轮廓、边缘等特征信息以增强目标的边缘,然后采用数学形态学的方法对其进行膨胀、腐蚀以滤除众多的背景噪声.经大量的实验验证,这种方法可以有效地提取出非合作目标的边缘信息,并可滤除大量噪声,为进一步开展非合作目标识别工作奠定基础.     

粒子滤波GPS/SINS组合导航系统动基座传递对准

在SINS(捷联式惯性导航系统)与GPS(全球定位系统)组合传递对准时,航向角的可观测性较弱,经过卡尔曼滤波后,航向角误差虽有所改善,但仍呈发散趋势,针对GPS/SINS组合系统特点,提出了一种动基座传递对准方案,依靠GPS测量信息进行速度匹配,完成动基座传递对准.该方案采用粒子滤波方法解决对准过程中的非线性问题.仿真结果表明该方案的对准精度(1σ)可以达到东向失准角误差为5角分,北向失准角误差为2角分,方位失准角误差为6角分.     

一种改进的宏块层码率控制策略

利用DCT域中交流系数的均方和代替像素域的方差,作为宏块运动复杂度的表征,并将改进后的码率模型运用于H.264的码率控制策略.仿真结果表明,与现有的码率控制算法相比,改进方案可以在不同的目标码率下更有效地控制码率的波动,改善了PSNR增益.在图像质量方面更平稳,有效地改善了主观视觉质量.     

基于人眼视觉机理的红外图像边缘提取

在描叙了On型感受野特性的基础上,结合Bubble函数和负高斯-拉普拉斯二阶微分函数,给出了实用的On型感受野数学模型;探索性地描叙了人眼微动产生中央凹区信息精细处理、周边区域保持适度警觉的机理,据此提出了大尺度On型感受野与小尺度Off型感受野相结合的人眼微动精细处理模型,并利用该模型对红外图像进行了边缘提取,显示出对弱小目标处理的快速性和精确性.