小天体软着陆自主光学导航与制导方法研究

针对小天体软着陆任务自主性、实时性的需求,对软着陆小天体自主导航与制导问题 进行了研究。提出了一种利用激光测距仪和光学导航相机跟踪目标着陆点的自主导航方案, 利用测距矢量以及目标点之间的几何关系,确定着陆平面法向方向和目标点位置。分析期望 的探测器下降轨迹特点,给出了一种基于制导变量的脉冲控制制导律,通过对目标点视线与 着陆平面法向矢量之间夹角的控制,将软着陆小天体控制分解为切向控制与法向控制两部分 。最后,通过数学仿真对自主导航制导系统的性能进行了验证,结果表明该方法能够满足垂 直软着陆的任务需要,实现高精度软着陆。     

深空探测器小天体交会段自主导航方法研究

针对深空探测任务中,与小行星交会段的自主导航问题,首先建立探测器在交会段的轨道动力学模型,并提出了2种导航观测方案:1)利用目标天体图像作为观测量;2)利用目标天体视线方向和目标天体夹角作为观测量.然后结合动力学模型和观测模型推导了2种导航方法的滤波算法公式.最后通过蒙特卡罗数值仿真分析方法,估算了2种导航方法的误差值,结果表明误差值在可接受精度范围内,验证了2种自主导航方法是可行的.     

应用灰度特征的行星陨石坑自主检测方法与着陆导航研究

针对陨石坑阴影不明显的行星着陆导航图像,提出了基于图像灰度值特征的陨石坑自主检测方法,通过兴趣区快速确定陨石坑边缘分布,解决了一般陨石坑检测方法对图像太阳高度角的依赖问题。利用检测出的陨石坑视线信息,采用非线性预测滤波方法估计着陆器着陆阶段的位置和姿态;鉴于视觉着陆导航对照了场景状况的高度依赖性,提出了一种利用分形理论和相邻点分级方法的天体随机地景建模方法。最后验证了所提方法的有效性。     

电离层闪烁对导航接收机性能的影响

为定量分析电离层闪烁对接收机环路的影响,利用信号在电离层闪烁影响下的等效传输信道模型,通过数值仿真对比分析了电离层闪烁对接收信号幅度、载波相位、码相位、载噪比和I/Q支路跟踪值的性能影响。结果表明：电离层闪烁会使接收载噪比出现深度的快速衰落,严重时会出现高达5dB的突降,从而显著地影响用户的定位性能;在相同的电离层闪烁强度下,较小的环路带宽会发生较弱的载波相位周跳。     

Rapid and robust initialization for monocular visual inertial navigation within multi-state Kalman filter

Sensor-fusion based navigation attracts significant attentions for its robustness and accuracy in various applications. To achieve a versatile and efficient state estimation both indoor and outdoor, this paper presents an improved monocular visual inertial navigation architecture within the Multi-State Constraint Kalman Filter (MSCKF). In addition, to alleviate the initialization demands by appending enough stable poses in MSCKF, a rapid and robust Initialization MSCKF (I-MSCKF) navigation method is proposed in the paper. Based on the trifocal tensor and sigma-point filter, the initialization of the integrated navigation can be accomplished within three consecutive visual frames. Thus, the proposed I-MSCKF method can improve the navigation performance when suffered from shocks at the initial stage. Moreover, the sigma-point filter is applied at initial stage to improve the accuracy for state estimation. The state vector generated at initial stage from the proposed method is consistent with MSCKF, and thus a seamless transition can be achieved between the initialization and the subsequent navigation in I-MSCKF. Finally, the experimental results show that the proposed I-MSCKF method can improve the robustness and accuracy for monocular visual inertial navigations.     

Optimal Earth’s reentry disposal of the Galileo constellation

Nowadays there is international consensus that space activities must be managed to minimize debris generation and risk. The paper presents a method for the end-of-life (EoL) disposal of spacecraft in Medium Earth Orbit (MEO). The problem is formulated as a multiobjective optimisation one, which is solved with an evolutionary algorithm. An impulsive manoeuvre is optimised to reenter the spacecraft in Earth’s atmosphere within 100?years. Pareto optimal solutions are obtained using the manoeuvre $\mathrm{\Delta }v$ and the time-to-reentry as objective functions to be minimised. To explore at the best the search space a semi-analytical orbit propagator, which can propagate an orbit for 100?years in few seconds, is adopted. An in-depth analysis of the results is carried out to understand the conditions leading to a fast reentry with minimum propellant. For this aim a new way of representing the disposal solutions is introduced. With a single 2D plot we are able to fully describe the time evolution of all the relevant orbital parameters as well as identify the conditions that enables the eccentricity build-up. The EoL disposal of the Galileo constellation is used as test case.     

Prospects of sea launches for Chinese cryogenic liquid-fueled medium-lift launch vehicles

This paper introduces the sea-launch technology of a cryogenic liquid-fueled medium-lift rocket. It first reviews the current state of sea launch technology, and then gives a brief introduction of China’s New Generation Medium-lift Launch Vehicle (NGMLV). The innovations in the NGMVL, such as responsive test and launch control, a H³ launch model, and unmanned operations, provide convenience for sea launches. Based on these innovations, this paper proposes a sea launch scheme, including the system configuration, test and launch processes, and an improved adaptive design for the rocket. Then, the launch platform is discussed in detail, which integrates the functions of sea transportation, assembly and test, as well as technical and launch areas. The layout and function divisions, fluid filling, gas supply and distribution systems, and lossless storage technology of LH2 are described in order. This breakthrough in sea launch technology will enable China to launch medium and large satellites and constellations ‘both on land and sea’, especially into low-inclination Low-Earth Orbits (LEOs), and it allows China to remain competitive in the fast-paced space industry.     

A Carrier Synchronization Algorithm for Autonomous Radio Receiver in Deep Space

The carrier synchronization algorithm of the autonomous radio for deep space is studied. When the signal modulation is unknown, this paper improves the existing universal carrier synchronization loop for multiple modulations, expands the frequency tracking range of the loop, proposes a Tong detection-based M-ary Phase Shift Keying (M-PSK) signal locking detection algorithm to rapidly and effectively determine whether the current phase discrimination mode matches the modulation mode, so as to independently choose whether to switch the phase discrimination mode. Through theoretical analysis and comparison, it is described that the total detection probability of the algorithm proposed in this paper is significantly higher than the probability of single lock detection. Simulation results show that the algorithm has high detection probability and low computational complexity at a low signal to noise ratio.      

UAV navigation in high dynamic environments: A deep reinforcement learning approach

Unmanned Aerial Vehicle (UAV) navigation is aimed at guiding a UAV to the desired destinations along a collision-free and efficient path without human interventions, and it plays a crucial role in autonomous missions in harsh environments. The recently emerging Deep Reinforcement Learning (DRL) methods have shown promise for addressing the UAV navigation problem, but most of these methods cannot converge due to the massive amounts of interactive data when a UAV is navigating in high dynamic environments, where there are numerous obstacles moving fast. In this work, we propose an improved DRL-based method to tackle these fundamental limitations. To be specific, we develop a distributed DRL framework to decompose the UAV navigation task into two simpler sub-tasks, each of which is solved through the designed Long Short-Term Memory (LSTM) based DRL network by using only part of the interactive data. Furthermore, a clipped DRL loss function is proposed to closely stack the two sub-solutions into one integral for the UAV navigation problem. Extensive simulation results are provided to corroborate the superiority of the proposed method in terms of the convergence and effectiveness compared with those of the state-of-the-art DRL methods.     

NPF算法在X射线脉冲星导航中的应用研究

针对X射线脉冲星导航中航天器模型的强非线性、高阶模型不确定性等问题,提出应用非线性预测滤波(NPF)算法实时估计航天器的轨道信息。首先,建立具有模型不确定性的X射线脉冲星导航定轨指标函数,优化得到满足指标函数最小的系统模型误差值,通过降低模型不确定性的影响来提高航天器自主定轨精度。对STK生成的“火星探路者”和“金星快车”及“北斗一号”三种航天器轨道数据进行分析,仿真结果表明,该算法比EKF算法具有更高的定轨精度,能够满足深空以及近地轨道航天器的自主定轨精度指标要求。