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.     

一种空间极低温吸附制冷机的设计与实现

针对极低温吸附制冷技术的热沉制冷系统,系统分析了极低温吸附制冷的特性,研究了热沉温度对极低温吸附制冷性能的影响,研制了一台极低温吸附制冷机样机,工质气体为氦4,在1.5W@4.2K G-M制冷机基础上实现了50μW@0.8K的制冷性能,验证了基于机械制冷系统的更高热沉温度技术的可行性,这一成果为深空探测和载人空间站相关研究提供了技术支撑。     

弱太阳闪烁中深空探测信道的自适应控制

为提高探测器发射机功率利用率,在探测器和地球间建立可靠的传输链路,弱太阳闪烁中的深空信道的自适应控制十分重要。根据CCSDS规范,提出了一种基于连续功率控制和离散速率控制策略的深空信道自适应控制方法。数学分析和计算机仿真表明,(1) 太阳闪烁越强,自适应功率控制效果越明显;(2) 当太阳闪烁引起的信号衰减不大,小于9.4dB时,MPSK自适应控制信道容量高于非自适应控制信道容量。
     

基于CNN 与BiLSTM 的退化设备剩余使用寿命预测

针对DC-DC 变换器难以建立物理退化模型的问题,提出了一种基于卷积神经网络和双向长短期记忆 神经网络的剩余寿命预测算法。首先,通过对DC-DC 变换器中关键器件进行失效模式分析,得到DC-DC 变换 器的失效特征参数;然后,采用卷积神经网络对多传感器信号进行融合和特征提取,获得百分比指数退化指标; 其次,将获得的健康指标输入到融合注意力机制的双向记忆神经网络中,利用注意力机制对输出结果进行加权 融合,利用不同的权重值优化预测模型,最后,利用蒙特卡洛丢弃法获得剩余寿命的区间估计,并通过仿真数 据验证了所提出方法的有效性。     

一种深空探测器自主天文导航新方法及其可观测性分析

天文导航是一种适用于深空探测器的完全自主的导航方法,与传统的直接利用天体观测信息进行滤波的方法不同,针对深空探测器,提出了一种首先利用天文观测信息通过几何解算得到一个初步的定位结果,再结合轨道动力学方程利用多模自适应(MM)滤波方法对初步结果进行再处理的自主天文导航新方法,仿真计算的结果表明,该方法可以明显提高导航定位精度,同时从可观测性和可观测度的角度,分析了应用该方法提高导航定位精度的原因和机理。     

Regression model for civil aero-engine gas path parameter deviation based on deep domain-adaptation with Res-BP neural network

The variations in gas path parameter deviations can fully reflect the healthy state of aero-engine gas path components and units; therefore, airlines usually take them as key parameters for monitoring the aero-engine gas path performance state and conducting fault diagnosis. In the past, the airlines could not obtain deviations autonomously. At present, a data-driven method based on an aero-engine dataset with a large sample size can be utilized to obtain the deviations. However, it is still difficult to utilize aero-engine datasets with small sample sizes to establish regression models for deviations based on deep neural networks. To obtain monitoring autonomy of each aero-engine model, it is crucial to transfer and reuse the relevant knowledge of deviation modelling learned from different aero-engine models. This paper adopts the Residual-Back Propagation Neural Network (Res-BPNN) to deeply extract high-level features and stacks multi-layer Multi-Kernel Maximum Mean Discrepancy (MK-MMD) adaptation layers to map the extracted high-level features to the Reproduce Kernel Hilbert Space (RKHS) for discrepancy measurement. To further reduce the distribution discrepancy of each aero-engine model, the method of maximizing domain-confusion loss based on an adversarial mechanism is introduced to make the features learned from different domains as close as possible, and then the learned features can be confused. Through the above methods, domain-invariant features can be extracted, and the optimal adaptation effect can be achieved. Finally, the effectiveness of the proposed method is verified by using cruise data from different civil aero-engine models and compared with other transfer learning algorithms.     

深空导航相位参考干涉测量技术研究

针对深空导航不断提高的测角精度需求和传统无线电干涉测量技术所面临的局限,介绍了相位参考干涉技术用于深空导航的优势,重点分析了该技术的基本原理和两个关键观测参数的影响,综述了该技术在国外的研究进展情况,最后介绍了我国开展该技术研究的软硬件基础和利用嫦娥三号任务数据开展的相位参考干涉测量试验情况,试验结果表明了基于我国深空测控资源开展该技术研究的可行性和高精度,有助于推动该技术转向实际工程应用,提高我国深空导航无线电干涉测量水平。     

一种基于纯天文观测的火星车自主导航方法

提出了一种基于纯天文观测的火星车自主天文导航新方法.该方法仅需利用由星敏感器视场内测量得到的火星卫星(火卫一、火卫二)和某一恒星之间的星光角距,结合火星车的运动模型,通过Unscented粒子滤波方法,即可获得高精度的火星车实时位置信息.计算机仿真结果表明了该方法的有效性,同时对几个关键的精度影响因素进行了仿真分析.      

精确动力学模型中的行星引力辅助轨道设计

轨道设计分为初步设计和精确模型迭代两步,初步设计基于等效脉冲模型,用圆锥曲线拼接法确定时间窗口和引力辅助产生的速度脉冲。精确模型中引力辅助看作是一个连续的过程,将简化模型得到的引力辅助双曲线轨道化为行星心目标B平面参数,以地心逃逸速度作为设计变量,通过微分修正的方法进行求解。通过算例对比分析了简化模型和精确模型设计结果之间的关系,结果表明,引力辅助脉冲等效模型精度较好。     

萤火一号深空测控设备

深空测控通信是实施深空探测的关键技术, 萤火一号探测器是中国第一个深空探测器. 本文介绍了深空测控通信的特点、存在的技术困难及需要攻克的关键技术, 描述了萤火一号火星探测器的测控通信技术方案及星载测控设备的功能分配, 给出了星载测控设备的基本配置情况及主要技术指标. 萤火一号探测器的测控和数传采用一体化设计方案, 在10 kg重量约束条件下, 实现了上行遥控通道及下行遥测通道, 具备科学数据传输通道及测定轨信号发送的功能, 而且每个通道均具有冗余备份设备.