基于SIFT和仿射变换的航空器起飞图像跟踪方法

针对机场监视的需要,结合航空器起飞特征,研究了尺度不变特征变换( SIFT)算法和仿射变换模型,在对图像进行灰度图像序列处理的基础上,提出了将SIFT特征点跟踪与仿射变换相结合对航空器起飞信息识别、跟踪的方法。以滨海国际机场的一个起飞过程为例,对图像序列进行了运动目标识别和帧间特征点的匹配,验证了方法的可行性,为机场航空器的起飞跟踪方法提供参考。     

系统可靠性优化方法

介绍了性优化的各种模型：组合优化模型、两类失效模式优化模型、可靠必优化分配模型、多目标优化模型以及可靠性模糊优化模型等。分析了可靠性优化分配模型各种解法的优缺点。研究认为，蒙特卡罗法具有简单和广泛适用性特点，因而推荐使用该法。     

便携式红外寻的防空导弹——单通道控制的自动驾驶仪

导弹采用单通道控制，虽然系统简单，但控制技术复杂。从这类自动驾驶仪特点出发，在介绍其功能、组成、控制方式基础上，对设计、分析、试验中遇到的技术问题提出了解决途径和方法，并对此类驾驶仪的数字化问题提出了设想和看法。     

从美的流变浅析美的本质

自从十八世纪中页鲍姆嘉通为美学奠定基础以来,众多哲学家、美学家写了无数论著来探讨美的含义.那么,美的本质究竟是什么呢?为什么美的问题会如此难以明晰?直到马克思主义美学产生后,这一美学命题才得到突破性地进展.马克思主义美学以实践为基础,认为实践是人类存在和发展的本质特征,从而提出"美是人的本质力量的对象化."将审美主体和审美客体有机地统一起来.     

Aerodynamic database development of the ESA intermediate experimental vehicle

This work deals with the aerodynamic database development of the Intermediate Experiment Vehicle.     

Sailing at the brink – The no-limits of near-/now-term-technology solar sails and SEP spacecraft in (multiple) NEO rendezvous

Near-Earth object (NEO) in-situ exploration can provide invaluable information for science, possible future deflection actions and resource utilisation. This is only possible with space missions which approach the asteroid from its vicinity, i.e. rendezvous. This paper explores the use of solar sailing as means of propulsion for NEO rendezvous missions. Given the current state of sail technology, we search for multiple rendezvous missions of up to ten years and characteristic acceleration of up to 0.10 mm/s². Using a tree-search technique and subsequent trajectory optimisation, we find numerous options of up to three NEO encounters in the launch window 2019–2027. In addition, we explore steerable and throttleable low-thrust (e.g. solar-electric) rendezvous to a particular group of NEOs, the Taurid swarm. We show that an acceleration of 0.23 mm/s² would suffice for a rendezvous in approximately 2000 days, while shorter transfers are available as the acceleration increases. Finally, we show low-thrust options (0.3 mm/s²) to the fictitious asteroid 2019 PDC, as part of an asteroid deflection exercise.     

Improving orbit prediction accuracy through supervised machine learning

Due to the lack of information such as the space environment condition and resident space objects’ (RSOs’) body characteristics, current orbit predictions that are solely grounded on physics-based models may fail to achieve required accuracy for collision avoidance and have led to satellite collisions already. This paper presents a methodology to predict RSOs’ trajectories with higher accuracy than that of the current methods. Inspired by the machine learning (ML) theory through which the models are learned based on large amounts of observed data and the prediction is conducted without explicitly modeling space objects and space environment, the proposed ML approach integrates physics-based orbit prediction algorithms with a learning-based process that focuses on reducing the prediction errors. Using a simulation-based space catalog environment as the test bed, the paper demonstrates three types of generalization capability for the proposed ML approach: (1) the ML model can be used to improve the same RSO’s orbit information that is not available during the learning process but shares the same time interval as the training data; (2) the ML model can be used to improve predictions of the same RSO at future epochs; and (3) the ML model based on a RSO can be applied to other RSOs that share some common features.     

多媒体智能数据库系统MIDS／BUAA

ＩＤＢ（智能数据库）思想的提出，预示着人类的信息处理即将步入一个崭新的时代．ＩＤＢ将计算机科学中近年来日趋发展成熟的五大主要技术，ΟΟ（面向对象）技术、ＤＢ（数据库）技术、ＡＩ（人工智能）、Ｈｙｐｅｒｔｅｘｔ／Ｈｙｐｅｒｍｅｄｉａ（超文本／超媒体）和正文数据库与联机信息检索技术，集成为一体．其中ΟΟ、ＡＩ和ＤＢ是ＩＤＢ中的三大支柱技术．本文论述ＭＩＤＳ／ＢＵＡＡ数据模型（Ｄａｔａｍｏｄｅｌｉｎｇ）的哲学，并介绍ＭＩＤＳ／ＢＵＡＡ系统的设计思想、动机、核心数据模型，系统的功能构成和它的Ｃｌｉｅｎｔ／Ｓｅｒｖｅｒ体系结构．     

异质网上互操作—从数据交换到程序交换

对分布式计算和软件集成中的互操作性问题进行了讨论，叙述了遵循特定的标准解决互操作性的办法，比较几种常见的互操作标准，包括ＳＴＥＰ／ＳＤＡＩ，ＣＯＲＢＡ和Ｊａｖａ，描述了Ｊａｖａ语言出现后程序交换的新特点，并对互操作标准的现状作了评述。     

基于改进YOLOv3和卡尔曼滤波器的飞机检测追踪方法

精确的飞机检测与追踪方法可以有助于提升我国军事实力,但是目前对小目标飞机进行有效追踪方法较少。基于深度学习的目标追踪方法较传统的方法性能更佳优越,因此针对传统方法对于小目标追踪性能不佳,本文提出了一种基于YOLOv3以及卡尔曼滤波器的飞机追踪方法以获得更好的追踪性能,该算法首先通过改进的YOLOv3算法对视频中的图像进行检测,在识别到视频中的飞机之后,通过卡尔曼滤波器对飞机的运动轨迹进行预测,并通过匈牙利算法进行数据关联。实验结果显示,该算法对小尺度飞机的检测性能较传统的YOLOv3有接近5%的提升,且对飞机的追踪效果精度高且实时性能,具有较高的军事应用价值。