A data driven approach for detection and isolation of anomalies in a group of UAVs

The use of groups of unmanned aerial vehicles(UAVs) has greatly expanded UAV’s capabilities in a variety of applications, such as surveillance, searching and mapping. As the UAVs are operated as a team, it is important to detect and isolate the occurrence of anomalous aircraft in order to avoid collisions and other risks that would affect the safety of the team. In this paper, we present a data-driven approach to detect and isolate abnormal aircraft within a team of formatted flying aerial vehicles, which removes the requirements for the prior knowledge of the underlying dynamic model in conventional model-based fault detection algorithms. Based on the assumption that normal behaviored UAVs should share similar(dynamic) model parameters, we propose to firstly identify the model parameters for each aircraft of the team based on a sequence of input and output data pairs, and this is achieved by a novel sparse optimization technique. The fault states of the UAVs would be detected and isolated in the second step by identifying the change of model parameters.Simulation results have demonstrated the efficiency and flexibility of the proposed approach.     

Improved specular point prediction precision using gradient descent algorithm

Global Navigation Satellite Systems Reflectometry (GNSS-R) utilizes GNSS signals reflected off the Earth surface for remote sensing applications. Due to weak power of reflected signals, GNSS-R receiver needs to track reflected signals by open loop. The first step is to calculate the position of specular point. The specular point position error of the existing algorithm—Quasi-Spherical Earth (QSE) Approach—is about 3 km which may cause troubles in data post-processing. In this paper, gradient descent algorithm is applied to calculate position of specular point and the calculation is based on World Geodetic System 1984 (WGS 84) ellipsoid in geodetic coordinate. The benefit of this coordinate is that it is easy to investigate the effect of real surface’s altitude. Learning rate—the key parameter of the algorithm—is adaptively adjusted according to initial error, latitude and gradient descent rate. With self-adaptive learning rate strategy, the algorithm converges fast. Through simulation and test on Global Navigation Satellite System Occultation Sounder II (GNOS II), the performances of the algorithm are validated. The specular point position error of the proposed algorithm is about 10 m. The speed of the proposed algorithm is competitive compared with the existing algorithm. The test on GNOS II shows that the proposed algorithm has good real-time performance.     

Radial distribution of galactic cosmic rays at solar maximum

In this paper we analyze the spatial distribution of galactic cosmic rays during periods of maximum solar activity of the cycles 21, 22 and 23. We have used a two dimensional model to solve the cosmic ray transport equation. This model includes all relevant physical processes: diffusion, convection, drift and shock effects on cosmic ray propagation inside the heliosphere. We focused on the study of the radial distribution of galactic cosmic rays, and compare our results with the spacecraft observations for two energies (175 MeV H and 265 MeV/n He). Although the radial intensities of galactic cosmic rays can be explained qualitatively with all three local interstellar spectra (LISs) used in this work, we applied a reduced chi-squared analysis to investigate the best LIS that could fit the data.     

功能梯度材料悬臂梁受复杂载荷作用的分层剪切理论

本文采用分层剪切变形理论对功能梯度材料层梁进行了分析，对立了功能梯度材料悬臂梁模型。取材料为非均质性，材料弹性系数随梯度变化，应用边界条件，层间连续条件，得出梁结构的变形与应力。结果表明，存在优化的梯度因子使得悬臂梁具有最佳的承载能力，载荷分布对结构应力场温度场有效大的影响。     

梯度热障涂层的设计和性能与失效研究

介绍了梯度热障涂层的表层、底层及梯度过渡层材料的选用和设计原则,对梯度热障涂层的抗热震性能、抗氧化性能和力学性能的研究成果作了综述，探讨了梯度热障涂层的失效机理，并指出了需进一步研究的问题。     

梯度铝基复合材料层间结合强度研究

陶瓷梯度增强铝基复合材料是大功率发动机活塞理想增强材料。本文采用挤压铸造法制造出梯度复合材料,对其显微组织进行了观察;对梯度层间结合强度进行了测定。试验结果可为复合材料活塞的结构设计提供参考。     

Collaborative optimization design of process parameter and structural topology for laser additive manufacturing

High-resolution laser additive manufacturing (LAM) significantly releases design freedom, promoting the development of topology optimization (TO) and advancing structural design methods. In order to fully take advantage of voxelated forming methods and establish the quantitative relationship between the mechanical properties of printing components and multiple process factors (laser- and process- parameters), the concurrent optimization design method based on LAM should cover the process-performance relationship. This study proposes a novel artificial intelligence-facilitated TO method for LAM to concurrently design microscale material property and macroscale structural topology of 3D components by adopting heuristic and gradient-based algorithms. The process–structure–property relationship of selective laser sintering is established by the back propagation neural network, and it is integrated into the TO algorithm for providing a systematic design scheme of structural topology and process parameter. Compared with the classical optimization method, numerical examples show that this method is able to improve the mechanical performance of the macrostructure significantly. In addition, the collaborative design method is able to be widely applied for complex functional part design and optimization, as well as case studies on artificial intelligence-facilitated product evaluation.     

飞行倾斜角对时差测向精度的影响

以时差体制测向原理为基础,分析了飞行倾斜角对双基线时差测向精度的影响,旨在为机载测向系统试验提供帮助。     

基于态势评估及DDPG算法的一对一空战格斗控制方法

已有的空中格斗控制方法未综合考虑基于专家知识的态势评估及通过连续性速度变化控制空战格斗的问题。基于深度确定性策略梯度（DDPG）强化学习算法,在态势评估函数作为强化学习奖励函数的基础上,设计综合考虑飞行高度上下限、飞行过载以及飞行速度上下限的强化学习环境;通过全连接的载机速度控制网络与环境奖励网络,实现DDPG算法与学习环境的交互,并根据高度与速度异常、被导弹锁定时间以及格斗时间设计空战格斗结束条件;通过模拟一对一空战格斗,对该格斗控制方法在环境限制学习、态势评估得分以及格斗模式学习进行验证。结果表明：本文提出的空战格斗控制方法有效,能够为自主空战格斗进一步发展提供指导。     

Quantitative analyses of complexity and nonlinear trend of radio refractivity gradient in the troposphere

In this paper, the complexity and nonlinear trends of Radio Refractivity Gradient (RRG) in the troposphere over selected locations in Nigeria are analyzed and discussed extensively. The RRG is an important parameter in estimating path clearance and propagation effects such as ducting, surface reflection and multi-path on terrestrial line of-sights links. Also, radio wave signal propagating in the troposphere is affected by unpredictability of a weather condition which includes the variations of meteorological parameters such as temperature, pressure and relative humidity. The complex state of the atmosphere, which is the medium for the transmission of radio signals tend to have very strong influence such as scintillation and ducting on the quality of the radio signal, amplitude and phase. Variations in the meteorological parameters also induce variations in the refractive index of the atmosphere which in-turn results in the effect known as radio refractivity. For effective prediction and modeling of radio signal propagation, one should be able to characterize the nature and predictability of the computed RRG information. Chaotic Quantifiers (CQ) such as Phase Plot Reconstruction (PPR), Average Mutual Information (AMI), False Nearest Neighbor (FNN), Recurrence Plot (RP) and Recurrence Quantification Analyses (RQA) are used to assess the RRG. The information reveal, however, is based on the prediction techniques, design and frequency planning of microwave networks which may be useful for optimum performances during atmospheric turbulence.