基于中低轨星座对弹道导弹监视的可探测模型

分析了中低轨卫星及星载红外传感器对导弹目标的可探测性因素,提出了几何可见、光学可见和设备可见的概念,建立了单星对导弹的可观测模型。对Walker-δ星座的3*7,7*3两种构型进行了仿真,讨论了传感器工作模式和作用距离的影响,以及可见率的数值特性,并演示了3个任务对单弹道接力跟踪的典型情形。     

小推力最优轨迹协态估计的高效机器学习方法

针对变比冲小推力轨迹间接优化中的协态变量初值猜测问题,提出了一种基于机器学习的协态变量初值高精度高效估计方法。首先,基于标称最优轨迹延拓,建立了状态量边值高扰动上限情形下的数据集生成方法,并分析了扰动上限对求解效率的影响。然后,构建了基于位置速度、轨道根数和改进春分点轨道根数多形式状态量组合输入的人工神经网络(ANN)映射关系,分析并优化了神经网络结构。将提出的方法应用于深空探测小推力转移场景,仿真结果表明该方法相对于标称轨迹直接扰动的数据集生成方法及单一形式状态量输入的人工神经网络映射方法,均有效地提升了求解收敛率,能够高效高精度地估计协态变量初值,实现轨迹快速优化。     

面向木星卫星交会任务的探测器飞行路径规划

针对探测器在木星系统内多次借力的飞行路径和轨道优化设计问题,提出了一种基于三层优化思想的飞行路径规划方法,该方法可根据给定的任务约束和交会目标,自动搜索探测器在木星系统内的借力飞行序列,同时完成标称飞行轨道的优化设计。首先,文章在给定轨道动力学模型和木卫借力模型基础上,建立了面向木卫交会任务的两次借力飞行轨道优化设计模型和求解方法;然后,采用结合遗传算法、全局遍历和贪婪算法的三层优化设计思路,给出了一种环木飞行路径规划方法;最后,以木星四颗卫星的交会任务为例进行了仿真分析。仿真结果表明：针对木卫的交会任务,探测器速度增量需求随木卫借力次数的增多,呈现先显著减小后逐渐增大的现象;探测器采用多次木卫借力的策略,可显著降低探测器的速度增量需求;探测器速度增量达到最优之后,借力目标收敛于交会目标,且速度增量随借力次数的进一步增多而逐渐增大。     

面向中末交接班的临近空间拦截弹弹道优化

针对反高超声速目标拦截弹中末制导交接班窗口小、变化快引起的交接班难题,设计了带终端位置和速度指向约束的拦截弹中制导弹道.首先,考虑交接班时间、动压、热流、过载、控制量以及终端弹道倾角等约束,建立了拦截弹纵向平面中制导弹道优化模型;其次,构建了中制导段的弹目拦截几何,提出了能量受限的侧窗探测拦截弹中末制导交接班窗口概念,...     

吸气式高超声速飞行器助推-巡航轨迹优化

针对吸气式高超声速巡航飞行器建立了纵向平面内的二维轨迹优化模型(包括火箭助推段和吸气式飞行段),其中大气模型、气动力模型和发动机模型均建立了比较详细的模型,能够比较全面、准确地描述吸气式高超声速巡航飞行器的特征;基于配点法建立了适用于高超声速巡航飞行器助推-巡航轨迹优化的方法,在求解非线性规划时引入了规范化处理、稀疏分析和偏导数计算方法等,以提高优化效率;对吸气式高超声速飞行器助推-巡航轨迹进行了优化研究,分析了典型设计参数变化对最优轨迹的影响。仿真结果表明:所建立的方法能够快速、高精度求解吸气式高超声速巡航飞行器轨迹优化问题,并且能够方便地分析设计参数变化对最优轨迹的影响,可用于吸气式高超声速飞行器飞行剖面设计与优化。     

Behavior pattern mining based on spatiotemporal trajectory multidimensional information fusion

Trajectory data mining is widely used in military and civil applications, such as early warning and surveillance system, intelligent traffic system and so on. Through trajectory similarity measurement and clustering, target behavior patterns can be found from massive spatiotemporal trajectory data. In order to mine frequent behaviors of targets from complex historical trajectory data, a behavior pattern mining algorithm based on spatiotemporal trajectory multidimensional information fusion is proposed in this paper. Firstly, spatial–temporal Hausdorff distance is proposed to measure multidimensional information differences of spatiotemporal trajectories, which can distinguish the behaviors with similar location but different course and velocity. On this basis, by combining the idea of k-nearest neighbor and density peak clustering, a new trajectory clustering algorithm is proposed to mine behavior patterns from trajectory data with uneven density distribution. Finally, we implement the proposed algorithm in simulated and radar measured trajectory data respectively. The experimental results show that the proposed algorithm can mine target behavior patterns from different complex application scenarios more quickly and accurately compared to the existing methods, which has a good application prospect in intelligent monitoring tasks.     

考虑移动目标不确定行为方式的轨迹预测方法

针对现有方法难以预测出符合飞行移动目标不确定行为方式轨迹的问题,提出基于逆强化学习的飞行移动目标轨迹预测方法,通过学习目标行为偏好以及模拟目标行为决策过程的方式预测目标的移动轨迹。首先基于深度神经网络建立目标的行为决策模型与行为偏好模型,然后通过最大熵逆强化学习方法交替地学习模型参数。为了有效地学习目标的不确定行为特征,采用监督学习的方法学习出目标示例轨迹概率分布模型,用于指导目标行为偏好模型的训练以及初始化目标行为决策模型,同时通过对目标行为偏好模型进行预训练的方式提高其训练质量。仿真结果表明,提出的飞行移动目标轨迹预测方法可通过学习到的目标行为决策模型较为准确地模拟目标的行为方式,预测的目标轨迹分布与真实的目标轨迹分布在Kullback Leibler(KL)散度下的相似度可达0.24。     

Trajectory prediction in pipeline form for intercepting hypersonic gliding vehicles based on LSTM

The interception problem of Hypersonic Gliding Vehicles (HGVs) has been an important aspect of missile defense systems. In order to provide interceptors with accurate information of target trajectory, a model based on an improved Long Short-Time Memory (LSTM) network for trajectory prediction pipeline is proposed for the interception of a skip gliding hypersonic target. Firstly, for trajectory prediction required by intercepting guidance laws, the altitude, velocity and velocity direction of the target are formulated in the form of analytic functions, consisting of linear decay terms and amplitude decay sinusoidal terms. Then, the dynamic characteristics of the model parameters are analyzed, and the target trajectory prediction pipeline is proposed with the prediction error considered. Finally, an improved LSTM network is designed to estimate parameters in a dynamically-updated manner, and estimation results are used for the calculation of the final trajectory prediction pipeline. The proposed prediction algorithm provides information on the velocity vector for midcourse guidance with the effect of prediction errors on interception taken into account. Simulation is conducted and the results show the high accuracy of the algorithm in HGVs’ trajectory prediction which is conducive to increasing the interception success rate.     

Trajectory optimisation in electrical discharge machining of three-dimensional curved and twisted channels

Numerical control electrical discharge machining(NC EDM) is one of the most widely used machining technologies for manufacturing a closed blisk flow path, particularly for three-dimensional(3D) curved and twisted flow channels. In this process, tool electrode design and machining trajectory planning are the key factors affecting machining accessibility and efficiency. Herein, to reduce the difficulty in designing the electrode and its motion path in the closed curved and twisted channels, a heur...     

Path,feedrate and trajectory planning for free-form surface machining: A state-of-the-art review

Nowadays, free-form surfaces have been widely used in various industrial fields. They are usually machined by CNC machine tools, but recently have also begun to be manufactured by industrial robotic arm manipulators, thanks to low cost, large operation reaching space and high machining flexibility of robot. So far, various methodologies have been proposed to improve efficiency and quality of free-form surface machining, thus this paper aims at providing a state-of-the-art review on research advances in free-form surface machining. In this review, tool path generation, feedrate scheduling in Cartesian space and trajectory planning in joint space are focused for both CNC machining and robot machining, and their research statues, existing difficulties and key issues are discussed in detail. Finally, the feasible routes, breakthrough points and future development trend are also expounded.