基于纯比例导引的拦截碰撞角约束制导策略

拦截碰撞角约束制导是当前导弹制导研究的关键问题之一。首先基于理想比例导引（IPN）律拦截非机动目标的解析解,推导了纯比例导引律（PPN）拦截固定目标的解析解,得到了弹目相对距离、制导指令加速度和导弹前置角的显示表达式,并进一步得到了拦截碰撞角与弹目相对运动状态和比例导引系数之间的解析表达式。其次,基于该解析表达式,提出了基于PPN的拦截碰撞角约束制导策略（PPNIACG）,并探讨了在铅垂面内进行落角约束打击和水平面内进行拦截碰撞角约束打击的2种实现方式。最后,以弹道成型制导律（TSG）和最优碰撞角约束制导律（OIACG）为参考,通过数值仿真算例,对PPNIAC的拦截性能进行了对比分析,验证了所提出制导策略的有效性和正确性。     

小型固定翼无人机集群综述和未来发展综述

围绕小型固定翼无人机集群这一难度高、发展快、应用前景广阔、多学科交叉的新方向,从集群系统内涵、现有典型项目、关键技术3个角度综述了国内外小型固定翼无人机集群的研究现状。在系统梳理集群系统内涵和应用优势的基础上,从集群协同模式探索、分布指挥体系构建、核心关键技术突破和集群验证等4个视角总结现有典型项目,从体系架构、通信组网、决策与规划、飞机平台、集群飞行、集群安全与集群指控等7个核心点综述了技术研究现状。最后,综合小型固定翼无人机集群中亟需解决的关键技术,展望了这一领域未来的发展趋势。     

多飞行器再入段时间协同弹道规划方法

提出了一种多飞行器再入段时间协同弹道规划方法。首先,在纵向平面内规划满足航程与终端约束的纵向标称轨迹。随后,在采用轨迹跟踪律跟踪纵向标称轨迹的同时,运用考虑初始横侧向状态的多边界航向偏差角走廊策略控制飞行器的横侧向机动,以满足到达时间约束与终端约束,进而实现单枚飞行器到达时间约束下的轨迹规划。在此基础上,完成了飞行器的到达时间分布与飞行能力分析,给出了最小与最大到达时间的分析计算方法,并根据多飞行器协同再入的任务需求完成了协同飞行时间决策。最后,多飞行器协同再入与扰动条件下的仿真结果表明,该方法能够规划出满足到达时间与终端约束的协同再入轨迹,具备良好的计算精度与鲁棒性。     

Coactive design of explainable agent-based task planning and deep reinforcement learning for human-UAVs teamwork

Unmanned Aerial Vehicles (UAVs) are useful in dangerous and dynamic tasks such as search-and-rescue, forest surveillance, and anti-terrorist operations. These tasks can be solved better through the collaboration of multiple UAVs under human supervision. However, it is still difficult for human to monitor, understand, predict and control the behaviors of the UAVs due to the task complexity as well as the black-box machine learning and planning algorithms being used. In this paper, the coactive design method is adopted to analyze the cognitive capabilities required for the tasks and design the interdependencies among the heterogeneous teammates of UAVs or human for coherent collaboration. Then, an agent-based task planner is proposed to automatically decompose a complex task into a sequence of explainable subtasks under constrains of resources, execution time, social rules and costs. Besides, a deep reinforcement learning approach is designed for the UAVs to learn optimal policies of a flocking behavior and a path planner that are easy for the human operator to understand and control. Finally, a mixed-initiative action selection mechanism is used to evaluate the learned policies as well as the human’s decisions. Experimental results demonstrate the effectiveness of the proposed methods.     

Optimal guidance for reentry vehicles based on indirect Legendre pseudospectral method

Development of a feasible guidance scheme for reentry vehicles is a challenge because of its significant nonlinearity and multi-constraints. A method for the implementation of three-degree-of-freedom guidance for constrained reentry vehicle is presented in the paper. First, the constrained trajectory is generated by Legendre pseudospectral method (LPM) and then the feasibily of the trajectory is validated. Based on the obtained reference trajectory, the guidance problem is converted into a trajectory state regulation problem which is a linear time varying system. A robust state feedback guidance law is generated in real time using indirect Legendre pseudospectral feedback method. Finally, simulation results illustrate that the overall guidance scheme can lead to a very accurately controlled flight with all the constraints satisfied even in the presence of initial state uncertainty.     

Regularized robust filter for attitude determination system with relative installation error of star trackers

As one of the most critical issues for high-accuracy satellite attitude determination, the relative installation error of star tracker usually leads to inconsistency of the output attitude information. In this paper, an approach named regularized robust filter algorithm is proposed to control the relative installation error of star tracker in the attitude measurement data. Based on the uncertainty model established for the attitude measurement system, the weighted least square solution is presented and the regularized robust filter is deduced firstly. The algorithm parameters are then optimized with the design indices in order to minimize the upper boundary for the variance of the estimated error. Compared with the traditional Kalman filter, the regularized robust filter takes into consideration the effects of model uncertainty, which can be used to optimize the filter parameters during its design stage. Thus, the information of both the system model and the measurement data can be applied effectively. Moreover, the existence conditions need not be validated in the proposed filter algorithm, which is convenient for on-orbit application. Finally, simulation results demonstrate the validity and efficiency of the proposed method. The relative installation error of attitude determination is mostly reduced and the estimation precision is improved greatly.     

Matching suitable feature construction for SAR images based on evolutionary synthesis strategy

In the paper,a set of algorithms to construct synthetic aperture radar（SAR）matching suitable features are frstly proposed based on the evolutionary synthesis strategy.During the process,on the one hand,the indexes of primary matching suitable features（PMSFs）are designed based on the characteristics of image texture,SAR imaging and SAR matching algorithm,which is a process involving expertise;on the other hand,by designing a synthesized operation expression tree based on PMSFs,a much more flexible expression form of synthesized features is built,which greatly expands the construction space.Then,the genetic algorithm-based optimized searching process is employed to search the synthesized matching suitable feature（SMSF）with the highest effciency,largely improving the optimized searching effciency.In addition,the experimental results of the airborne synthetic aperture radar ortho-images of C-band and P-band show that the SMSFs gained via the algorithms can reflect the matching suitability of SAR images accurately and the matching probabilities of selected matching suitable areas of ortho-images could reach 99±0.5%.     

联合星间测距和测速的导航星座自主定轨研究

导航卫星通过星间观测完成定位,是提高星座生存能力的一项重要技术。在测距资料的基础上,增加测速资料进行定轨。给出了基于星间观测的定轨数学模型,证明了联合测距和测速的定轨同样存在秩亏问题,使用参数加权平差算法,顾及先验信息对星间观测资料进行平差,以Walker星座为例对算法性能进行评估。结果表明:增加测速资料后,星座位置精度略有提高,速度精度显著提高。     

强光光学零件加工误差频谱分析与控制方法研究

本文利用功率谱密度分析磁流变抛光表面的敏感频率误差,发现走刀步距与中高频误差具有直接的关联性,通过小波算法确定其分布区域后,采用大束径的光顺抛光法对敏感频率误差进行控制,测试结果表明中高频误差得到了有效控制。本研究对强光光学零件加工误差的频谱分析、表征和控制具有指导意义。     

Trajectory correction maneuver design using an improved B-plane targeting method

A spacecraft for interplanetary mission is usually perturbed by some disturbance sources. The trajectory correction maneuver (TCM) is required to adjust this trajectory error, and the B-plane targeting method is widely used in this field. However, this B-plane targeting method is based on the differential correction algorithm, and a numerical Jacobian matrix is usually used for this algorithm. Therefore, our main goal in this paper is to suggest the improved B-plane targeting method to overcome the disadvantages of the conventional B-plane method which requires a numerical Jacobian matrix for the initial perturbation selection and iterations. For this improvement, an analytical Jacobian matrix is introduced instead of the numerical Jacobian matrix. Then, another B-plane approach that offers an analytical solution is suggested using the target eccentricity instead of the target time of closest approach (TCA). Using a modified Kepler's equation, the previous B-plane targeting approach can be replaced with the new method through the analytical solution.