平行航路安全评估新方法(英文)

首先提出了一种平行航路安全评估新方法,即从空中交通管制的安全防护体系入手,将潜在飞行冲突看作空中相撞事故的初因事件,提炼出管制员指挥、短期冲突告警、飞行员目视避让及机载防撞系统告警四层安全防护,进而将平行航路碰撞风险问题分解为潜在飞行冲突计算和各防护层的失效概率分析.然后,推导了管制员干预次数计算模型,采用CREAM方法解决了管制员调配飞行冲突失误概率计算问题,建立了STCA防护失效和TCAS防护失效故障树模型.最后,以京沪平行航路为例进行计算,得出了雷达管制环境下的京沪平行航路碰撞风险.结果表明该航路满足安全要求.     

一种新型车辆智能避撞预警模型设计

针对目前单阈值避撞模型所具有可反应时间单一的缺点,设计了一种基于多级报警规则的避撞预警模型,为驾驶员提供了一个渐进的反应时间,在紧急情况下使其有更多时间来避免碰撞发生.对车辆行驶过程中驾驶员的信息感知特性进行分析,为模型的建立提供相应的理论基础.设计了基于多级报警规则的避撞预警模型,并对模型的设计过程进行了详细的论述.利用实测数据对给出的模型进行了实证研究,结果表明多级报警避撞预警模型能使驾驶员更加舒适的驾驶车辆,并为智能避撞预警系统的建立提供了良好的模型基础.      

基于ANFIS的避撞算法

应用自适应神经模糊推理系统(ANFIS)建立了车辆避撞算法模型,为加快收敛速度,运用线性递归最小二乘法(RLSE)和最陡下降法(SD)组成的混合算法通过前向和后向通道分别进行了模型的前提参数和结论参数的辨识.为取得模型训练所需的数据对,设计了两车跟随的实验,试验中尝试性的采用GPS来获取两车的车间距和车速差,经过模型训练和仿真输出,该方法能够模仿驾驶员的操作,并且操作更为平滑.这种方法改变了以往采用经验来确定隶属函数的缺陷,使模型的建立更为可靠.      

星座设计中避免卫星碰撞问题的研究

随着小卫星技术的发展 ,越来越多的航天任务采用小卫星星座来完成 ,在星座的设计过程中需要考虑的因素众多。本文从星座运行的安全性角度 ,分析了星座中卫星发生碰撞的机会和碰撞概率 ,对星座中存在的卫星之间可能发生的碰撞问题进行了研究 ,并提出了解决方法     

空间碎片预警中的碰撞概率方法研究

由于空间碎片对飞行在地球轨道上的航天器危害日益严重,所以必须采取一些有效的防护措施,对于那些直径大于10 cm的碎片,通常是采用主动规避的方法来进行防护.为了避免传统的Box判据造成的过多错误预警,碰撞概率模型开始被应用于空间碎片预警,本文以空间站为例,将碰撞概率方法与传统Box区域判定法进行比较,介绍碰撞概率计算模型的建立方法,基于位置误差矩阵的碰撞概率Pc的算法,并针对实际交会事例进行了计算和分析.      

Uncertainty-aware Cube algorithm for medium-term collision risk assessment

The number of Earth orbiting objects is constantly growing, and some orbital regions are becoming risky environments for space assets of interest, which are increasingly threatened by accidental collisions with other objects, especially in Low-Earth Orbit (LEO). Collision risk assessment is performed by various methods, both covariance and non-covariance based. The Cube algorithm is a non-covariance-based method used to estimate the collision rates between space objects, whose concept consists in dividing the space in cubes of fixed dimension and, at each time instant, checking if two or more objects share the same cube. Up to now its application has been limited to the long-term scenarios of orbital debris evolutionary models, where considering the uncertainties is not necessary and impractical. Within operative contexts, instead, medium-term collision risk analysis may be an important task, in which the propagation-related uncertainties play a prominent role, but the timescale poses challenges for the application of standard covariance-based conjunction analysis techniques. In this framework, this paper presents an approach for the evaluation of the medium-term collision frequency for objects in LEO, called Uncertainty-aware Cube method. It is a modified version of the Cube, able to take the possible errors in the space objects’ position into account for the detection of the conjunctions. As an object’s orbit is propagated, the along-track position error grows more and more, and each object could potentially be in a different position with respect to the one determined by numerical propagation and, thus, in a different cube. Considering the uncertainties, at each time instant the algorithm associates more than one cube to each object and checks if they share at least one cube. If so, a conjunction is detected and a degree of confidence is evaluated. The performance of the method is assessed in different LEO scenarios and compared to the original Cube method.     

Robust formation control for missiles with obstacle avoidance

This paper investigates the robust formation control for missiles with obstacle avoidance.A sliding mode surface that is asymptotically stable is firstly presented by the collision avoidance potential function and hyperbolic tangent function. Based on the sliding mode surface, a robust formation controller with obstacle avoidance is designed for missiles. To improve the convergence rate,a finite-time controller which can deal with the formation control for missiles is given using an improved sli...     

基于人工势场的星群松散编队控制

利用低成本的微纳卫星组成星群协同执行空间任务,近年来引起了航天界的广泛关注.针对星群松散编队控制任务,将人工势场法和基于相对运动动力学方程的速度反馈控制相结合,在各颗卫星和目标之间构造吸引势场,在各颗卫星之间建立基于位置信息的避碰势场,在空间障碍物附近建立避障势场,同时引入速度反馈控制律,综合实现星群松散编队控制,并通过仿真算例验证了控制方法的有效性.     

室内多移动机器人协同建图与路径规划

多机器人协同定位与路径规划是协同侦察、作战等场景中的首要问题,其难点在于如何在未知环境下完成自主定位。提出了将多机器人同步定位与构图(Simultaneous Localization and Mapping,SLAM)系统应用于室内环境,,以解决此问题。针对机器人定位存在的相关定位误差,采用了增加惯性测量单元的方法,以进行修正。为解决单个机器人在构建地图时速度较慢的问题,将基于坐标变换的方法用于多机器人的地图融合。此外,基于冲突检测和冲突规避思想,对多机器人路径规划方法进行了研究,并将其部署在了多机器人系统中。实验结果表明,采用多机器人协作进行环境探测,在确保全局地图信息完备的同时,可以提高构图效率。基于冲突规避的多机路径规划方法,可以为机器人个体规划出无碰撞路径,机器人可以根据该路径到达目标位置。