融合神经网络与超像素的候选区域优化算法

为解决目标检测中候选区域召回率低的问题,提出融合神经网络与超像素的目标候选区域算法。该算法利用神经网络提取更能清楚表达目标边界的特征,并使用聚类、相似性等策略,计算每个滑动窗口所含有的边缘信息量;将待测图像使用简单线性迭代聚类算法分割成若干个超像素,并利用超像素的空间位置、完整性、相邻超像素间的对比度信息,计算各个超像素的显著性得分及每个滑动窗口的显著性得分;根据每个滑动窗口的边缘信息及显著性得分筛选滑动窗口。在PASCAL VOC 2007测试集上进行对比实验,其实验结果表明:所述算法能够快速产生定位质量高的候选区域。     

Fuzzy recognition of missile borne multi-line array infrared detection based on size calculating

In order to improve the infrared detection and discrimination ability of the smart munition to the dy-namic armor target under the complex background, the multi-line array infrared detection system is established based on the combination of the single unit infrared detector. The surface dimension features of ground armored targets are identified by size calculating solution algorithm. The signal response value and the value of size calculating are identified by the method of fuzzy recognition to make the fuzzy classification judgment for armored target. According to the characteristics of the target signal, a custom threshold de-noising function is proposed to solve the problem of signal preprocessing. The multi-line array infrared detection can complete the scanning detection in a large area in a short time with the characteristics of smart munition in the steady-state scanning stage. The method solves the disadvan-tages of wide scanning interval and low detection probability of single unit infrared detection. By reducing the scanning interval, the number of random rendezvous in the infrared feature area of the upper surface is increased, the accuracy of the size calculating is guaranteed. The experiments results show that in the fuzzy recognition method, the size calculating is introduced as the feature operator, which can improve the recognition ability of the ground armor target with different shape size.     

Weapon effectiveness and the shapes of damage functions

This paper provides a review of methods of assessing a fragmentation weapon's effectiveness against a point target or an area target with keeping the focus on the necessity of using the Carleton damage function with the correct shape factor.First,cookie-cutter damage functions are redefined to preserve the shape factor of and to have the same lethal area as the corresponding Carleton damage function.Then,closed-form solutions of the effectiveness methods are obtained by using those cookie-cutter damage functions and the Carleton damage function.Finally,the closed-form solutions are applied to calculate the probability of damaging a point target and the expected fractional damage to an area target for several attack scenarios by using cookie-cutter damage functions and the Carleton damage functions with different shape factors.The comparison of the calculation results shows that using cookie-cutter damage functions or the Carleton damage function with a wrong shape factor results in quite signifi-cant differences from using the original Carleton damage function with a correct shape factor when weapon's delivery error deviations are less than or comparable to the lengths of the lethal area and the aim point is far from a target.The effectiveness methods improved in this paper will be useful for mission planning utilizing the precision-guided munitions in circumstances where the collateral damage should be reduced.     

Visual SLAM in dynamic environments based on object detection

A great number of visual simultaneous localization and mapping (VSLAM) systems need to assume static features in the environment. However, moving objects can vastly impair the performance of a VSLAM system which relies on the static-world assumption. To cope with this challenging topic, a real-time and robust VSLAM system based on ORB-SLAM2 for dynamic environments was proposed. To reduce the influence of dynamic content, we incorporate the deep-learning-based object detection method in the visual odometry, then the dynamic object probability model is added to raise the efficiency of object detection deep neural network and enhance the real-time performance of our system. Experiment with both on the TUM and KITTI benchmark dataset, as well as in a real-world environment, the results clarify that our method can significantly reduce the tracking error or drift, enhance the robustness, accuracy and stability of the VSLAM system in dynamic scenes.     

知识图谱的预警探测体系探测效能贝叶斯评估方法

战争中,预警探测体系作为典型的复杂系统,其探测效能发挥情况的有效评估一直是亟需人们研究解决的重要现实问题.突破了传统效能评估方法的局限,在分析了知识图谱技术、贝叶斯评估方法基本原理的基础上,提出了基于两者综合运用的预警探测体系探测效能评估新方法,利用专家知识和实验数据构建知识图谱,并进一步使用贝叶斯网络方法实施知识推理...     

用于纯方位机动目标跟踪的机动探测法

假设目标在某时刻发生折线机动,并且目标在机动前后都是做匀速直线运动。所提出的机动探测算法通过探测这种变化得到探测时刻。这种算法是基于对方位预测误差的均值变化进行分析的。然后估计出目标机动时刻,并从机动时刻起重新设置滤波器,估计出目标机动后的运动参数。典型的机动TMA态势仿真结果表明,该算法对于一般的目标折线机动可以有效地进行跟踪。     

时敏打击指挥控制技术初探

分析了时敏目标打击链,介绍了压缩打击链的主要途径,描述了图像处理、战场数据管理、武器动态分配、智能代理集成等有关时敏打击指挥控制技术,为时敏打击指挥控制系统的研究提供参考。     

增强路由器安全性的一种措施

路由器是军用电子信息系统的关键互联设备,提高路由器自身的安全性非常必要。首先对路由器涉及到的安全问题作了较为详细地分析,然后给出一种增强路由器安全性的技术措施。该措施重点处理终点包对路由器的威胁,将入侵检测模块与数据包过滤模块进行联动,通过入侵预防、入侵时的检测和响应、入侵后的快速分析与恢复等三个环节,提高路由器抗攻击的能力。最后探讨了该措施对路由器性能的影响。     

舰载雷达发现目标的效能概率计算

根据舰载雷达保障火炮射击任务的要求,结合火炮自身使用特点,提出舰载雷达发现目标的效能概率计算问题。应用概率分析方法,对多种距离上舰载雷达发现目标保障火炮系统有效射击的概率进行了推导,得出舰载雷达保障火炮系统有效射击的概率计算公式,并进行了实例分析。实际作战运用中,可以应用此算法对火炮系统的射击概率计算,可以较好地保障火炮系统的射击准备时间,但影响实际火炮射击的因素很多,表征雷达发现目标的效能指标也很多,应综合考虑。     

三坐标雷达目标真实高度估计算法研究

在目标跟踪领域,通过三坐标雷达的测量值(斜距、仰角及方位角)来估算目标的真实高度一直是个难点。目前主要有两类处理方法:坐标转换法和等效地球半径法。前者把与雷达天线相关的三坐标测量值转换到大地坐标系统来计算目标高度;后者充分考虑地球曲率以及大气折射的特性,通过增加地球半径来估算目标的高度。最后对上述的两类方法进行总结、比较与分析。