From Nationalism to Factionalism: Faultlines in the Naga Insurgency

Do ceasefires or peace talks create fragmentation in the insurgent groups? Rather than proposing claims that can offer predictions about armed groups behaviour under ceasefires or peace processes, the analysts tend to focus largely on the dynamics between state and non-state actor. The experts pay little attention to overtime changes in social and local political context which might contribute to propelling a rebel group towards fragmentation and factionalism. The present study intends to fill this gap by exploring the shifting role of public opinion and ethnic support for the peace talks to ascertain whether it can increase the likelihood of factionalism in rebel groups or not. This article applies this approach to the case of Naga National Movement (1947–2015) in India, and finds that the proposed variable appears to have increased the frequency of factionalism in the movement.     

The SSA-BP-based potential threat prediction for aerial target considering commander emotion

The target's threat prediction is an essential procedure for the situation analysis in an aerial defense system. However, the traditional threat prediction methods mostly ignore the effect of commander's emotion. They only predict a target's present threat from the target's features itself, which leads to their poor ability in a complex situation. To aerial targets, this paper proposes a method for its potential threat prediction considering commander emotion (PTP-CE) that uses the Bi-directional LSTM (BiLSTM) network and the backpropagation neural network (BP) optimized by the sparrow search algorithm (SSA). Furthermore, we use the BiLSTM to predict the target's future state from real-time series data, and then adopt the SSA-BP to combine the target's state with the commander's emotion to establish a threat prediction model. Therefore, the target's potential threat level can be obtained by this threat prediction model from the predicted future state and the recognized emotion. The experimental results show that the PTP-CE is efficient for aerial target's state prediction and threat prediction, regardless of commander's emotional effect.     

基于GAHP的模糊综合评判法在潜艇作战方案评估中的应用

潜艇作战方案评估是辅助对潜指挥员决策的重要方法,而评估的科学性对决策的有效性影响很大。利用多人层次分析法（GAHP）和模糊综合评判相结合的方法,对潜艇作战方案进行评估,评估的结果可信度高,有利于对潜指挥员的正确决策。最后,通过实例证明了方法的有效性。     

舰载雷达对水面目标发现概率研究

为了提高舰载雷达的作战效能,研究了舰载雷达发现水面目标的概率模型,采用了数学建模方法,结合舰载雷达发现目标接收机输入端的信噪比,利用发现距离与发现概率之间的关系,建立了舰载雷达发现水面目标的概率模型,对于提高舰载雷达信息作战能力具有实践意义。     

基于改进TOPSIS法和蚁群算法的反TBM 目标群目标分配研究*

基于改进的TOPSIS法和蚁群算法,以弹道导弹目标群为研究对象,研究了反导指控系统对目标群的目标分配问题。首先通过改进的TOPSIS法确定TBM目标群威胁排序并基于拦截排序准则确定拦截排序;其次使作战效能最大化,基于蚁群算法确定目标的最优分配方案;最后通过仿真实例验证了在考虑目标威胁值排序前提下采用此算法,可使目标群分配方案更加科学有效和符合反导作战实际。     

基于随机森林的重要性测度指标体系

重要性测度分析可以找出重要特征变量,从而降低输入空间的维数,节约运算成本.基于随机森林重要性测度的分析原理,探寻随机森林的重要性测度指标与基于方差的全局灵敏度指标之间的联系,得到求解方差灵敏度主指标Si及其总指标STi的新途径.建立基于随机森林的单变量、组变量重要性测度指标,并明确具体的求解过程,完善基于随机森林的重要...     

基于全脉冲分段转发的LFM雷达干扰方法

线性调频(LFM)脉冲雷达输出信号时延敏感于输入信号频率,基于此,文中提出了一种基于雷达全脉冲信号分段转发的干扰方法,通过对雷达完整脉冲信号的合理分段并排序转发,在LFM脉冲压缩雷达匹配滤波处理后形成多假目标干扰。利用群延迟原理揭示了脉冲分段转发干扰机理;根据干扰信号频谱和匹配滤波原理,推导了多假目标输出形式;给出了假目标幅度不低于真目标时脉冲分段数计算公式及假目标数目最多时对应的转发次序要求;仿真实验验证了理论分析的正确性。     

基于邻域灰度分布的IR弱小目标检测

图像中邻域内灰度起伏程度越大 ,各点灰度值占邻域内总灰度值的比率的平方和越大 ,由此提出了一种基于邻域灰度分布的弱小目标检测方法。同时考虑到复杂自然背景 ,特别是背景中含有大量边缘和高频点的情况 ,提出了目标检测的改进方法。最后 ,利用邻域判决法实现运动目标的进一步分离。实验表明该方法能够极大地减少候选目标点数 ,准确有效地检测复杂自然背景中的红外运动弱小目标 ,适合于实时和多目标的检测     

调频斜率极性捷变SAR欠采样转发干扰

针对传统欺骗干扰难以对调频斜率极性捷变SAR形成有效干扰的问题,研究了对调频斜率极性捷变SAR进行欠采样转发干扰的方法。通过建立调频斜率极性捷变SAR有限时长欠采样转发干扰信号模型,分析欠采样转发干扰对调频斜率极性捷变SAR的干扰效果。给出假目标数目、位置以及幅度的理论计算公式,在此基础上讨论欠采样周期对干扰效果的影响。利用数字仿真验证了理论分析的正确性。     

MPP数据并行FORTRAN汇编代码模拟环境的设计与实现

本文阐述了一种在单机上模拟ＭＰＰ机执行并行汇编代码的方法。这种并行汇编代码由ＭＰＰＦＯＲＴＲＡＮ编译器生成。由于在一个大型工程中，编译生成的目标代码运行环境不一定能及时具备，所以，研制汇编代码模拟环境ＤＰＦＡＳ有助于及早验证编译目标代码的正确性和完备性。本文通过共享进程组在ＳＧＩ工作站上实现多机环境模拟和远程地址访问模拟。此模拟环境的实现对ＭＰＰ数据并行ＦＯＲＴＲＡＮ编译器的正确性验证和效率评估有一定的帮助。