基于误差估值累加开环校正的诱导式欺骗检测方法

诱导式卫星欺骗干扰可诱导航空器逐渐偏离预定航迹，难以被发现，因此及时有效地检测干扰是飞行安全的保障。在现有紧组合导航体制基础上，设计了一种基于误差估值累加开环校正的紧组合导航结构，并证明了其性能与传统闭环校正紧组合导航性能等效。在此结构中，将紧组合导航系统与自适应序贯概率比检测方法结合，提出了一种基于误差估值累加开环校正的诱导式欺骗检测方法，融合紧组合导航信息与其他不受欺骗影响的导航信息，构建欺骗检测统计量进行诱导式欺骗检测。仿真结果表明，开环校正结构可避免随时间累加的惯性导航系统误差所导致的组合导航滤波器发散问题，同时欺骗检测方法可进一步提高算法对“最坏”情形下微小诱导式欺骗的检测效果。     

Perception‐aware autonomous mast motion planning for planetary exploration rovers

Highly accurate real‐time localization is of fundamental importance for the safety and efficiency of planetary rovers exploring the surface of Mars. Mars rover operations rely on vision‐based systems to avoid hazards as well as plan safe routes. However, vision‐based systems operate on the assumption that sufficient visual texture is visible in the scene. This poses a challenge for vision‐based navigation on Mars where regions lacking visual texture are prevalent. To overcome this, we make use of the ability of the rover to actively steer the visual sensor to improve fault tolerance and maximize the perception performance. This paper answers the question of where and when to look by presenting a method for predicting the sensor trajectory that maximizes the localization performance of the rover. This is accomplished by an online assessment of possible trajectories using synthetic, future camera views created from previous observations of the scene. The proposed trajectories are quantified and chosen based on the expected localization performance. In this study, we validate the proposed method in field experiments at the Jet Propulsion Laboratory (JPL) Mars Yard. Furthermore, multiple performance metrics are identified and evaluated for reducing the overall runtime of the algorithm. We show how actively steering the perception system increases the localization accuracy compared with traditional fixed‐sensor configurations.     

基于船载卫星通信三轴天线的跟踪搜索技术

针对船载卫星通信三轴天线跟踪系统,介绍了船载三轴天线的系统组成,提出了一种基于捷联惯导的船载三轴天线跟踪搜索技术。天线以目标地理角为中心,通过坐标转换将目标地理角转换为天线的目标甲板角,调整AEC三轴使其及时准确地跟随目标甲板角。目前,该方法已经成功应用于多种船载三轴天线。实践表明,该方法能够快速准确地搜索到目标卫星,并实现对目标卫星的稳定跟踪。     

Sarcopenia: Molecular Pathways and Potential Targets for Intervention

Aging is associated with sarcopenia. The loss of strength results in decreased muscle mass and motor function. This process accelerates the progressive muscle deterioration observed in older adults, favoring the presence of debilitating pathologies. In addition, sarcopenia leads to a decrease in quality of life, significantly affecting self-sufficiency. Altogether, these results in an increase in economic resources from the National Health Systems devoted to mitigating this problem in the elderly, particularly in developed countries. Different etiological determinants are involved in the progression of the disease, including: neurological factors, endocrine alterations, as well as nutritional and lifestyle changes related to the adoption of more sedentary habits. Molecular and cellular mechanisms have not been clearly characterized, resulting in the absence of an effective treatment for sarcopenia. Nevertheless, physical activity seems to be the sole strategy to delay sarcopenia and its symptoms. The present review intends to bring together the data explaining how physical activity modulates at a molecular and cellular level all factors that predispose or favor the progression of this deteriorating pathology.     

基于GsMAP的尼洋河流域降水时空分布特征研究

鉴于尼洋河地区实测降雨资料缺乏,卫星降雨产品具有显著优势,基于GsMAP降雨产品数据和地面观测站点数据,利用降雨量年内分配特征的δ方法建立卫星降雨校正公式,分析流域降雨量的时空分布特征。结果表明,实测站点月降雨量校正结果较好,相关系数达0.954,年尺度的站点降雨相关系数为0.54,降雨量空间分布呈现出自西向东递增的特点。卫星降雨观测在西部地区存在低估,东部地区有一定程度的高估,在降雨梯度分布上,流域在3500~4000m高程段降雨量呈上升趋势,其他高程段均为显著下降,整体变化率为-104mm/km。流域的年均面平均降雨量为699mm,降雨多集中于夏季,且有逐年增加趋势。     

Inverse reinforcement learning-based time-dependent A* planner for human-aware robot navigation with local vision

In an environment where robots coexist with humans, mobile robots should be human-aware and comply with humans' behavioural norms so as to not disturb humans' personal space and activities. In this work, we propose an inverse reinforcement learning-based time-dependent A* planner for human-aware robot navigation with local vision. In this method, the planning process of time-dependent A* is regarded as a Markov decision process and the cost function of the time-dependent A* is learned using the inverse reinforcement learning via capturing humans' demonstration trajectories. With this method, a robot can plan a path that complies with humans' behaviour patterns and the robot's kinematics. When constructing feature vectors of the cost function, considering the local vision characteristics, we propose a visual coverage feature for enabling robots to learn from how humans move in a limited visual field. The effectiveness of the proposed method has been validated by experiments in real-world scenarios: using this approach robots can effectively mimic human motion patterns when avoiding pedestrians; furthermore, in a limited visual field, robots can learn to choose a path that enables them to have the larger visual coverage which shows a better navigation performance.     

Study on Thermal Deformation Measurement of Optical Remote Sensing Satellite Platform Based on Machine Vision

To solve the special requirements of the high orbit optical remote sensing-satellite for the thermal deformation of the platform, the thermal deformation test and measurement scheme of the satellite platform is designed. Through the comparative analysis of test results, the rationality of the thermal deformation design of the platform structure is verified. The results of thermal deformation measurement show that the maximum deformation of A camera mounting surface is 57.5~〃, and the maximum deformation of B camera mounting surface points to 79.3~〃, which can be used as the basis for thermal deformation prediction of satellite during the orbit operation.     

Modeling and analysis for multilayered complex communication network of satellite navigation system

This study is extended to construct the network model, the node model, and the link model of complex communication network for satellite navigation system (CCN‐SNS) based on the hierarchical architecture. Firstly, a method called snapshots was proposed to describe the dynamic topology for CCN‐SNS; secondly, another method was put forward to model the different nodes of the CCN‐SNS; thirdly, the different links between every two different nodes were modeled. Therefore, based on the OPNET tools, a simulation for the CCN‐SNS, which contains the models that proposed earlier used to analyze the navigation accuracy and network transmission performance, was performed.     

车载移动测量系统定位准确度测试方法研究

阐述了移动测量系统的定位准确度需求,对圆概率法、均方差法和中误差法三种位置准确度评估方法进行分析比较,并在标准试验场内开展了车载GNSS/INS定位准确度测试。实验证明:中误差法的评估结果最准确,其误差小于1 m,明显优于圆概率法和均方差法。