自适应分块的改进最小费用网络流解缠算法

相位解缠是进行精确差分干涉测绘的关键步骤,在相位解缠算法中,最小费用网络流(MCF)是当前常用的算法,该算法具有精度高、限制残差点误差扩散、优先将误差限制在低相干区域的优点,但随着残差点数量的增多,其计算效率也随之降低。改进的MCF算法通过对其做分块,有效提升了算法效率,但块尺寸的选取影响最后的准确度与效率。本文提出一种自适应分块的改进MCF解缠算法,通过自适应寻优的方式选取合适的分割块,将相干性较高的点集中在同一块内,使得在准确度不受过多影响的情况下有效地提升算法效率。     

行星着陆动力下降段相对视觉导航方法

针对行星着陆动力下降段视觉导航自然路标匮乏的问题,提出了一种相对视觉导航方法。该方法利用相机和雷达的测量信息构建相对导航坐标系并求解随机视觉特征点在该坐标系下的位置矢量,利用求解得到的特征点为导航参考,设计相对导航系统,估计着陆器在相对导航坐标系下的位置、速度及姿态信息。同时,构建可观性矩阵,解耦分析位置和姿态的可观性。通过可观性分析可知利用相对导航坐标系下的一个随机特征点即可实现着陆器全状态可观。最后通过仿真分析着陆器状态误差,验证了可观测度理论分析及导航性能。该相对导航方法无需行星地形数据库,且可以实现着陆器全状态的高精度估计,满足行星精确软着陆的需求。     

行星软着陆GPS有模型强化学习制导方法

由于距离地球较远、测控延时误差较大、飞行环境十分复杂且难以提前预测，行星软着陆的自主制导技术目前存在水平位置估计困难、导航参考信息匮乏、复杂地形着陆困难等挑战。针对行星软着陆存在的困难和挑战，提出了基于引导策略搜索算法的有模型强化学习制导方法，实现了着陆器在初始状态受到扰动时，无需重新规划，仍能在满足约束条件的情况下降落在指定位置。该方法将迭代线性二次调节器作为控制器，产生初始轨迹；其次，使用多层神经网络拟合制导策略；最后，利用控制器监督策略学习，进而收敛产生可行策略。针对行星表面软着陆的仿真验证结果显示该算法仅通过几次循环，即可以实现初始状态变化的快速软着陆。一方面表明了基于有模型强化学习的数据高效利用率，另一方面也证明了强化学习方法在深空探测领域中具有广阔的应用前景。     

Mars entry guidance using a semi-analytical method

Future Mars missions may require improved landed accuracy to facilitate the landing site selection and finally access a region of complex terrain with high scientific return. This paper is to develop a novel, robust, and precision entry guidance algorithm for Mars entry vehicles with low lift-to-drag ratios. In the presence of large uncertainties, the entry terminal point controller algorithm can encounter severe performance degradation due to: (1) the small perturbation assumption, and (2) theoretically ignoring deviations in the atmospheric-density model, aerodynamic-force model, etc. Based on numerical technologies and the classical variation method (VM), this work develops a semi-analytical (SA) algorithm, in which combined effects of several dynamic uncertainties now can be addressed. The terminal-downrange error is predicted by a numerical predictor such that the dependence on the reference trajectory can be reduced and then the issue caused by the small perturbation assumption can be addressed. Such a predicted terminal-downrange error is finally corrected by an analytical corrector, which is designed by the VM. It is indicative that there can be no numerical iterations in the SA algorithm. Numerical results demonstrate the effectiveness of the SA algorithm.     

Threshold Selection Method Based on Reciprocal Gray Entropy and Artificial Bee Colony Optimization

Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional（2-D）histogram region oblique division and artificial bee colony（ABC）optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional（1-D）method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization（NCPSO）,the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.     

Fuel-optimal and Energy-optimal guidance schemes for lunar soft landing at a desired location

Two guidance schemes (i) fuel-optimal (ii) energy-optimal to realize soft landing at a desired location on the moon are developed using the optimal control laws. The optimal control laws are obtained by solving a two-point boundary value problem formulated based on Pontryagin’s principle. The guidance laws, adapted from the optimal control laws, are obtained as a function of unknown co-state variables. Differential Transformation (DT) technique is employed to determine the unknown co-states at each time instant of landing trajectory using the information on the current vehicle state, target landing site (loaded on-board apriori) and the time-to-go. The numerical integration of co-state dynamics is avoided due to the DT based approach. The time-to-go, a critical parameter for any guidance scheme, is computed and updated real time using a simple strategy which uses the current and end states. The simple strategy for time-to-go works well even when the shape of the trajectory is nonlinear. Extensive analysis is carried out to evaluate and compare the proposed guidance schemes. Further, the proposed schemes are compared with other popular guidance schemes. The DT based proposed schemes help quantify the landing masses for fuel-optimal and energy-optimal objectives. Other features of the proposed schemes are that they do not assume constant gravity field and independent of reference trajectory.     

自动着舰的控制构型研究

在参考美军自动着舰系统(ACLS)的基础上,研究工程上最合适的ACLS控制构型。首先,分析了垂直速度指令和俯仰角指令在轨迹控制本质上的不同点和相同点;然后,将上述两种指令控制结构与两种动力补偿系统(速度保持APCS和迎角保持APCS)一对一组合成4种控制构型,仿真比较了这4种构型在指令响应、风扰抑制上的性能差异,分析了其物理原因。结果表明,H·指令加迎角保持APCS的控制构型对飞机纵向控制更有利,特别是对轨迹、高度要求严格的着舰任务。这与美军的实际试飞结论相同。     

国外单组元变推力发动机应用与关键技术

介绍了国外单组元变推力发动机的应用现状,阐释了单组元变推力发动机的结构和设计原理,总结了研制和改进过程中的关键技术,主要包括径向双层夹套催化床设计、径向喷注器设计、流量稳定调节技术和催化床空穴控制技术等。美国为火星软着陆研制的MR-80和MR-80B无水肼单组元变推力发动机分别应用于“海盗”号和“好奇”号着陆器下降级推进系统。MR-80发动机可实现275~2835 N变推力调节,推力变比为10∶1,比冲为205 s,呈120°均布于“海盗”号着陆器三角形基座的长边。“好奇”号下降级推进系统由2个高压氦气瓶、3个推进剂贮箱、8台单组元变推力发动机、8台单组元250 N姿控发动机、1个压力控制组件和3个推进剂控制组件组成,MR-80B发动机可产生31~3603 N的真空推力,推力变比达到100∶1,比冲范围为204~223 s。     

无人机编队支撑网络的协同通信中继策略

针对无人机编队支撑网络优化选择中继成员进而提高编队协同通信能力问题，基于端到端技术（Device-to-Device，D2D），提出了一种同时考虑无人机编队成员的邻近域及编队成员间的社会性依存关系来优化选择中继成员的中继策略，旨在既能保证无人机编队的基本通信能力，又能同时优化提高编队的吞吐量，从而进一步提升编队支撑网络的整体性能。研究结果表明，所提的无人机编队支撑网络中继成员优化选择策略在系统吞吐量方面较已有方法具有明显优势。     

Material selection for a CubeSat structural bus complying with debris mitigation

The increasing number of commercial, technological and scientific missions for CubeSats poses several concerns about the topic of space junk and debris mitigation. As no regulation is currently in place, innovative solutions are needed to mitigate the impact that Low Earth Orbit objects can have during uncontrolled re-entry and the associated potential events of surface collision. We investigated the requirements, in terms of materials selection, for the development of a 3D-printed structural bus able to withstand loads during launch and in-orbit operations, with the objectives to be as light as possible and requiring the least amount of heat for demise during atmospheric re-entry. The selection indicated magnesium alloys as the best candidates to improve the reference material, aluminium 6061 T6, resulting in both mass-reduction and improved demisability. We also analysed how the relative importance of these two objectives can modify the selection of materials: if minimizing the heat to disintegration were valued more highly than lightness, for example, the new best candidates would become tin alloys. Our analysis, furthermore, suggested the importance of Liquid Crystal Polymer as the sole plastic material approaching the performance of the best metal choices. This contribution, thus, provides novel insight in the field of 3D-printed materials for the fast-growing CubeSat segment, complying with the debris mitigation initiatives promoted by space agencies and institutions.