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.     

Vision-based pose estimation for cooperative space objects

Imaging sensors are widely used in aerospace recently. In this paper, a vision-based approach for estimating the pose of cooperative space objects is proposed. We learn generative model for each space object based on homeomorphic manifold analysis. Conceptual manifold is used to represent pose variation of captured images of the object in visual space, and nonlinear functions mapping between conceptual manifold representation and visual inputs are learned. Given such learned model, we estimate the pose of a new image by minimizing a reconstruction error via a traversal procedure along the conceptual manifold. Experimental results on the simulated image dataset show that our approach is effective for 1D and 2D pose estimation.     

Promising roadmap alternatives for the SpaceLiner

The paper describes the vision and potential roadmap alternatives of an ultrafast intercontinental passenger transport based on a rocket powered two-stage reusable vehicle. An operational scenario and the latest technical lay-out of the configuration's preliminary design including flight performance are described. The question of how the revolutionary ultrafast transport can be realized is addressed by an assessment of the different technological and programmatic roadmap alternatives.     

A low-thrust transfer between the Earth–Moon and Sun–Earth systems based on invariant manifolds

A low-energy, low-thrust transfer between two halo orbits associated with two coupled three-body systems is studied in this paper. The transfer is composed of a ballistic departure, a ballistic insertion and a powered phase using low-thrust propulsion to connect these two trajectories. The ballistic departure and insertion are computed by constructing the unstable and stable invariant manifolds of the corresponding halo orbits, and a complete low-energy transfer based on the patched invariant manifolds is optimized using the particle swarm optimization (PSO) algorithm on the criterion of smallest velocity discontinuity and limited position discontinuity (less than 1 km). Then, the result is expropriated as the boundary conditions for the subsequent low-thrust trajectory design. The fuel-optimal problem is formulated using the calculus of variations and Pontryagin's Maximum Principle in a complete four-body dynamical environment. Then, a typical bang–bang control is derived and solved using the indirect method combined with a homotopic technique. The contributions of the present work mainly consist of two points. Firstly, the global search method proposed in this paper is simply handled using the PSO algorithm, a number of feasible solutions in a fairly wide range can be delivered without a priori or perfect knowledge of the transfers. Secondly, the indirect optimization method is used in the low-thrust trajectory design and the derivations of the first-order necessary conditions are simplified with a modified controlled, restricted four-body model.     

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.     

应用GPS载波确定载体姿态

本文简述了利用GPS载波相位技术进行载体姿态确定的原理，比较了目前已有的多种整周模糊度求解算法，选用最小二乘法进行了载体定姿实践，减少了备选整周模糊度的组合数，并采用多种约束信息来剔除不正确的模糊度组合，结合实验，指出了载体姿态变化和整周模糊度搜索速度的关系，提出了一种模糊度确定的辅助方法，并给出了应用算例。     

语用学视角下的工程硕士英语听说能力培养策略

语用学从具体使用语言的情景出发，结合人、社会、文化等去解释语言的意义。语用能力作为交际能力的重要组成部分，与听说能力密不可分。文章结合语用学基本理论探讨其对全日制硕士学位研究生英语听说技能培养的启示，并提出相关策略，旨在提高工程硕士的英语听说能力，培养实践应用型人才。     

环首都经济圈河北省居民体育生活方式现状与发展对策研究

本文采用文献资料法、问卷调查法,针对河北省14县市区的体育生活方式进行了调查研究,目的是为了改善居民不良的生活方式,培育居民科学、健康、文明的体育生活方式,为促进河北省全民健身计划的顺利实施提供有利的保障。     

地源热泵技术在建筑节能中的应用

本文探讨如何通过地源热泵技术实现建筑节能。研究通过地源热泵来实现一机多用,使其既能用于冬季供暖,又可以用于夏季制冷。同时也讨论了如何与太阳能相配合,来实现地热平衡。文中还给出了通过插值法和曲线拟合法对测量数据进行处理获得变温带和增温带的温度-深度曲线的方法。     

Aircraft engine health management via stochastic modelling of flight data interrelations

A novel engine health management (EHM) scheme is introduced. It uses flight-level, instead of thermodynamic, data to cost-effectively augment the onboard EHM redundancy. For a nominal healthy aircraft, fault-sensitive interrelations among flight data are globally modelled inside a flight regime via Constant-Coefficient Pooled Nonlinear AutoRegressive with eXogenous (CCP-NARX) excitation representations. Single or sequential engine faults perturb these interrelations. Statistically evaluating the perturbation-induced effects draws reliable conclusions on the engine?s health. Validation and comparisons with Kalman filter-based alternatives are made throughout the regime under various operational conditions.