潜艇目标指示效能

针对潜艇作战使用的特点,研究了潜艇利用"三角法"测量敌人的位置,对敌进行导弹攻击时,为己方编队提供目标指示的效能.进行目标指示效能的评估时,通过综合考虑某类导弹攻击目标的条件,确定该类导弹截获目标的概率,最终给出潜艇进行导弹攻击时目标指示的效能.具体指示效能评估在观察系统效能评估的层面上进行,用水声设备截获被打击目标的概率来表示,为保障潜艇导弹攻击目标指示组织指挥提供了科学的依据.     

预警机指挥多机群空战的协同战术决策

分析了预警机指挥下的多机群协同空战的战术决策方法,建立起了它的战术编队、威胁评估以及目标分配模型,并进行了仿真计算,结果表明此战术决策方法对于提高多机群协同空战的作战效能有着显著的作用,对于未来无人作战飞机多编队协同作战也具有很好的参考价值.     

防空兵确定被保卫目标重要性的一种方法

防空兵正确确定被保卫目标的重要性,是正确构建防空火力配系的基础.首先全面梳理了确定被保卫重点的六条依据,然后,在分析目标选定因素的基础上,给出了利用层次分析法确定各个指标权重的方法,同时,建立了防空兵评价被保卫重点目标重要性的数学模型,并结合一个实例验证了方法的应用.     

一种基于地形分析的多目标关联算法

利用低时空分辨率的卫星遥感观测进行目标群关联,由于目标群运动状态转变的规律性不好寻找,目标群的精确属性特征难于获取,增加了利用目标属性进行关联的实现难度.考虑到地形特征对目标群运动影响的特点,提出了基于地形栅格分析的多目标关联算法.     

An infrared target intrusion detection method based on feature fusion and enhancement

Infrared target intrusion detection has significant applications in the fields of military defence and intelligent warning. In view of the characteristics of intrusion targets as well as inspection difficulties, an infrared target intrusion detection algorithm based on feature fusion and enhancement was proposed. This algorithm combines static target mode analysis and dynamic multi-frame correlation detection to extract infrared target features at different levels. Among them, LBP texture analysis can be used to effectively identify the posterior feature patterns which have been contained in the target library, while motion frame difference method can detect the moving regions of the image, improve the integrity of target regions such as camouflage, sheltering and deformation. In order to integrate the advantages of the two methods, the enhanced convolutional neural network was designed and the feature images obtained by the two methods were fused and enhanced. The enhancement module of the network strengthened and screened the targets, and realized the background suppression of infrared images. Based on the experiments, the effect of the proposed method and the comparison method on the background suppression and detection performance was evaluated, and the results showed that the SCRG and BSF values of the method in this paper had a better performance in multiple data sets, and it’s detection performance was far better than the comparison algorithm. The experiment results indicated that, compared with traditional infrared target detection methods, the proposed method could detect the infrared invasion target more accurately, and suppress the background noise more effectively.     

An air cavity method for increasing the underwater acoustic targets strength of corner reflector

In order to improve the underwater acoustic target strength of corner reflectors, according to the principle of acoustic impedance mismatch of the boundary layer, the method of using air cavity to increase the underwater acoustic target strength of corner reflectors is proposed. The acoustic reflection coefficients of underwater air layer and single layer metal sheet are calculated and compared. The results show that the reflection coefficient of single layer metal sheet is greatly affected by frequency and incidence angle, and the reflection coefficient of air layer in water is large and little affected by frequency and incidence angle. On this basis, a new kind of airfilled cavity corner reflector is designed. The acoustic scattering characteristics of underwater airfilled cavity corner reflector are calculated cumulatively, and the results are compared with the monolayer metal sheet corner reflector. The simulation results show that the acoustic reflection effect of the airfilled cavity corner reflector is better. In order to verify the correctness of the method, the test was carried out in the silencing tank. The experimental results show that the simulation results are in good agreement with the experimental results, and the airfilled cavity can improve on acoustic reflection performance of the underwater corner reflector.     

基于复杂度特征的干扰识别算法

复杂度可以用来刻画信号的波形变化特征。文中使用了L-Z复杂度和分形维数这两种复杂度作为干扰识别的特征参数并结合支持向量机对干扰进行分类。仿真结果表明L-Z复杂度和分形维数计算复杂度低,且具有较好的类别差异度,同时文中提出的算法具有较高的识别准确率。     

用结构自适应前馈网络解算多目标导弹攻击区

多目标导弹攻击区的实时解算是机载多目标攻击武器系统得以技术实现的中心环节。阐述了“多目标导弹攻击区”的概念 ,探索了其解算的技术途径 ,提出了“实时、高精度和低存储”的解算要求。根据上述技术要求 ,设计了基于网络灵敏度统计分析的多层前馈网络结构自适应算法 ,以用于训练合适规模的多层前馈网络逼近器。在此基础上 ,进行了系统仿真研究 ,研究的结果表明了该方案的应用前景。     

多传感器多目标定位与跟踪技术研究

针对炮兵打击目标的特性和获取目标信息所采用的侦察设施 ,研究了多传感器多目标定位和跟踪问题。在闭圆和聚类概念的基础上 ,提出了一种多传感器多目标融合算法 ,并给出了状态估计的最优解。仿真结果证明了这种算法的有效性。这一模型的物理实现正在进一步研究之中。     

多目标数据关联的神经网络方法

数据关联是多目标跟踪的关键问题。基于 Hopfield神经网络的 JPDA是解决这一关键问题的有效方法之一 ,但此方法的难点在于优化系数的整定。提出一种改进算法 ,用于解决优化系数在线自适应整定问题。首先重新构造了李雅普诺夫能量函数 ,接着引入变化的优化系数因子 ,并给出了优化系数求解的迭代公式 ;最后对已有和改进的算法进行了仿真研究。结果表明改进的方法和原有的方法相比 ,一方面具有在线整定优化系数的功能 ,另一方面可以获得和原有算法非常接近的估计误差。