基于不确定度的专家评价综合方法

针对群决策中专家评价信息的综合处理问题,应用多位专家评价的评价样本不确定度,提出了基于不确定度的数据综合处理方法。该方法能够有效应用于群决策问题,尤其是参与决策人员(专家)较多时,出现专家相对权重可信度不明确而导致评价准确度低的问题,科学地简化了群决策中专家权重的确定过程,便于应用,具有坚实的理论依据和应用价值。通过算例分析,该方法的有效性得到了验证。     

基于滑模自适应鲁棒控制的四旋翼飞行器轨迹跟踪

针对四旋翼飞行器的稳定性在实际应用环境中会受到不同程度的破坏,不易对其进行高精度轨迹跟踪,提出一种滑模自适应鲁棒控制算法.系统整体采用内外环控制思想,将位置部分作为外环子系统,将姿态部分作为内环子系统,对两部分分别进行控制器的设计;通过运用李雅普诺夫稳定性分析判断控制算法是否能够使系统最终达到渐进稳定;最后进行仿真和实验研究,通过仿真和实验结果证明了此算法的有效性和优越性.     

光学波导中原子干涉的加速度测量

提出一种水平方向、光学波导中原子干涉的加速度测量方案。详细介绍了光路结构、原子团制备以及光学波导的绝热装载等。通过实验手段对测量方案进行验证,首先将~(87)Rb原子团冷却至50 nK的玻色爱因斯坦凝聚态,随后对超冷原子团施加布拉格光进行分束、合束,完成原子干涉过程。实验结果显示,所提干涉测量系统能够实现单轴加速度测量,对未来高精度多轴加速度测量系统的研制具有指导借鉴意义。     

MF-CFI: A fused evaluation index for camouflage patterns based on human visual perception

The evaluation index of camouflage patterns is important in the field of military application. It is the goal that researchers have always pursued to make the computable evaluation indicators more in line with the human visual mechanism. In order to make the evaluation method more computationally intelligent, a Multi-Feature Camouflage Fused Index (MF-CFI) is proposed based on the comparison of grayscale, color and texture features between the target and the background. In order to verify the effectiveness of the proposed index, eye movement experiments are conducted to compare the proposed index with existing indexes including Universal Image Quality Index (UIQI), Camouflage Similarity Index (CSI) and Structural Similarity (SSIM). Twenty-four different simulated targets are designed in a grassland background, 28 observers participate in the experiment and record the eye movement data during the observation process. The results show that the highest Pearson correlation coefficient is observed between MF-CFI and the eye movement data, both in the designed digital camouflage patterns and large-spot camouflage patterns. Since MF-CFI is more in line with the detection law of camouflage targets in human visual perception, the proposed index can be used for the comparison and parameter optimization of camouflage design algorithms.     

基于迭代误差补偿的发射点坐标精确求解方法

针对已知目标点坐标和射程射向情况下的发射点坐标精确计算问题,提出一种基于迭代误差补偿的非典型大地主题正解方法.该方法利用发射点方位角粗略计算目标点方位角,并调用大地主题正解方法,计算初始的发射点坐标和发射点方位角,将已知的发射点方位角和计算得到的发射点方位角之间的偏差作为负反馈,用于修正目标点方位角,通过迭代求解的方式得到发射点坐标.通过利用大地主题解算方式对非典型大地主题正解方法进行检验,得出发射点与目标点坐标之间的方位角偏差为10-7°,计算精度满足工程应用中的发射点坐标误差要求,能够用于军事指挥信息系统中发射点精确计算.     

一种无人机连发型电磁弹射系统的设计

为了满足集群作战条件下无人机快速连续地弹射起飞的要求,提出了一种无人机连发型电磁弹射系统的方案,阐述了系统的功能指标、结构以及控制策略和混合储能等技术,它具有机动性强、隐蔽性好、全程可控、弹射间隔短、发射成本低等特点,能根据不同要求弹射起飞不同的无人机,有效地解决无人机集群弹射起飞方式存在的局限性问题,对集群作战实现有力支撑.     

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.     

装备保障信息分类与代码设计研究

根据装备保障信息化建设的需要,分析了装备保障信息的特点,探讨了信息分类的要求并提出了装备保障信息分类方法;阐述了装备保障信息代码设计的要求、分类、形式．提出了代码设计方法。     

基于PLC的油泵车检测调控系统研究

油泵车作为管线系统重要的供油装备,具有牵一发而动全身的地位,为了保持管线系统稳定的工况和为下游泵站提供足够流量和进口压力,文中利用参数检测及报警系统、动力结合互锁系统、安全保护系统、嵌入式工况记录及数字化接口系统等信息化技术,使油泵车在不断提高自身作业能力、环境适应能力等机械性能与管线系统性能配套的同时,提高了其智能化水平和作业效率。     

油料装备信息接入和传输网络设计

在将油料装备从逻辑上划分为基础层、系统层、决策层3个层次的基础上,提出并设计了从基础层到系统层信息接入的网络方式,以及系统层到决策层信息传输的联网形式,从而为油料装备信息化提供了一个可行的网络解决方案。