面向深空通信的分布式系统Raptor码传输机制

为缓解深空探测器与地面站之间的超远距离和星体遮挡,而导致巨大的信号衰减以及链路频繁中断的问题,基于容迟/容断网络（DTN）协议框架,利用轨道器进行多跳中继组网传输,设计了多个探测器经过轨道器向地面传输场景下的分布式系统Raptor编码传输方案（DSRC）。提出了联合译码简化方案,理论分析推导了DSRC方案及改进方案的性能参数,并与现有分布式无速率纠删方案进行仿真比较,在译码冗余为5%时达到了0.01的译码失败率。     

结合深空机动的多次行星借力轨道设计

行星借力技术是减小星际探测任务发射能量的有效途径,传统的行星借力模型不能保证探测器借力前后的速度矢量转角达到理想要求。为此,进行了行星借力建模,并基于该模型,推导了探测器飞出借力天体影响球的双曲线超速矢量。针对轨道设计参数的强耦合性,提出了一种全局-局部混合搜索算法,并对地球-金星-地球-火星-木星转移轨道进行了设计。仿真结果验证了轨道模型的正确性和有效性,表明该文方法可以有效地对多次行星借力轨道进行设计。     

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。     

基于显式制导的月地返回轨道中途修正研究

月地返回轨道存在各种摄动误差,终端约束复杂,有必要对其进行中途修正研究。显式制导法通过二体轨道与精确轨道之间的差别进行多次迭代求解给定时刻所需的修正速度。文章利用显式制导法,采用月球段及地球段分段进行中途修正的策略,给出了基于分段落点预报显式制导的月地返回轨道中途修正方案。该方案无需计算雅克比矩阵,算法简单、计算快速、实用性强,能满足再入点参数要求。算例仿真与蒙特卡洛仿真验证了该方案的适用性。     

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.      

深空组阵Eigen算法及其低信噪比合成性能分析

根据深空组阵信号模型,分析了Eigen最优合成采用的两种准则即最大输出功率和最大 信噪比准则。为了快速计算最优权值,给出了两种迭代算法即PM和PMFM算法,同时为了改善 微弱信号合成效果,在PMFM算法中引入记忆因子,提出一种可以自适应跟踪信号相位变化的 自适应Eigen算法。仿真分析了基于最大输出功率准则的Eigen合成算法和自适应Eigen算法 对低信噪比组阵接收信号的合成性能,仿真结果表明自适应Eigen算法不但具有良好的合成 效果和自适应特性而且运算量小,具有重要的工程应用价值。
     

深空通信中提示否定确认型CFDP协议延时估算

为确定空间数据咨询委员会（CCSDS）建议高级在轨系统中CCSDS文件传输协议（CFDP）在深空通信环境中的适应性,研究了CFDP中提示否定确认型文件传输协议（Prompt NAK CFDP）的传输机理。给出了此传输方式的文件传输时延估算方法。分析了误码率、传输速率、协议数据单元的大小与数量,以及提示信息数等对传输时延的影响,获得了深空通信对误码率的要求。研究表明：CFDP可用于深空通信,为其进一步应用和改进提供了参考。     

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.     

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.     

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.