一种无人直升机地面监控系统仪表的设计

无人机地面航空仪表在地面站人机界面环境中占有重要地位。本文介绍了该航空仪表的设计思想和实现方法。设计中,使用先进的计算机硬件设备和计算机图形动态显示技术,实时、准确地在屏幕上显示仪表的动态数据     

有控飞行力学在无人飞行器研制和使用中的作用

本文从工程实践观点出发，结合无人飞行器，特别是战术导弹和制导兵器的特点，扼要讨论了与此密切相关的有控习行力学研究工作的某些进展情况，文中将有控习行力学问题分为两大类，即典型的飞行力学问题和相关的飞行力学问题，强调了多学科交 对飞行力学研究的重要意义；同时，还指出了有控飞行力学在未来軎与研制和使用中的作用。     

飞行器合理传递参数的解法

本文基于矢量矩阵分析法,建立了含气动、结构和飞行参数及其偏量的数学模型,它可用来分析飞行器的合理传递参数。按此方法不仅可以同时调整若干设计参数,而且还可简化计算机辅助设计的程序。为选择合理传递参数,列出了设计参数的调整准则。 取用动态因子和转换因子,使所得方法对于正常式、鸭式、旋转弹翼式和弹道式导弹都是适用的。     

利用小波分析识别空间目标的轨道机动

空间目标的轨道机动是与机械能的变化联系在一起的。机械能无法直接测量，只能通过空间目标的位置与速度计算。通过地面雷达可以得到空间目标的测距与测角信息，可以将其转为位置信息。空间目标的速度也不易直接测量，需要根据位置信息，通过微分平滑处理获得。由于测量噪声的影响，机动引起的机械能的变化淹没在噪声中，不容易识别。小波分析可以在一定程度上将淹没在噪声中的机械能变化揭示出来，提高轨道机动的识别能力。利用二进小波在不同尺度下分析机械能随时间的变化，尺度由小至大时真实信号含量增加，噪声含量受到抑制。观察小波系数曲线随小波分析尺度的变化趋势就可以快速判定是否存在轨道机动。仿真结果验证了识别方法的可行性。     

机载遥测发射天线的安装技术

从航空飞行试验的特点出发，阐明了安装机载遥测发射天线的基本原则及安装质量检验方法，介绍几种天线的具体安装方案，提出用三维计算技术定位机载发射天线的设想。     

遥测计算机字的自动判读

以导弹模拟飞行原理为基础 ,建立了简化弹道模型 ,分析了导弹遥测计算机字各参数的大小范围、变化规律 ,根据确定的范围和变化规律编制了遥测计算机字自动判读软件 ,并用曲线图的形式直观地显示了遥测计算机字的变化。     

惯性/图像组合导航中的双模态双滤波器研究

在简要介绍了飞行器视觉图像定位导航原理及模型的基础上，针对其非线性模型的推广Kalman滤波的收敛与初始条件有关的问题，将其定位导航的两种模型（线性与非线性模型）组合，提出了双模态双滤波器滤波方法。这种滤波能很好地解决非线性推广Kalman滤波的收敛问题。通过第一个线性滤波器的滤波估计给第二个非线性滤波器提供滤波初值，使这一非线性滤波收敛，并能取得较高的滤波精度。     

基于AOE网的过站航班保障进程优化

航班地面保障是机场运行的重要环节，为了提升航班地面保障效率，针对某机场航班地面保障流程构建AOE 网，通过该机场A-CDM 系统记录的航班节点数据求出该机场航班地面保障作业的“关键路径”。通过对关键路径上可压缩工序的分析，对该机场的地面保障作业流程进行优化。以我国西南地区某机场航班地面保障的实际数据为基础，剔除不可抗力造成的不正常数据，分别计算保障流程优化前后的航班过站时间。结果表明：在33 组航班数据中，该机场使用AOE 网络优化后的保障作业流程比优化前平均减少地面保障作业时长6.1 分钟/架次，说明通过合理地优化航班地面保障进程，可以有效提高机场的运行效率。     

Sleep and cognitive function of crewmembers and mission controllers working 24-h shifts during a simulated 105-day spaceflight mission

The success of long-duration space missions depends on the ability of crewmembers and mission support specialists to be alert and maintain high levels of cognitive function while operating complex, technical equipment. We examined sleep, nocturnal melatonin levels and cognitive function of crewmembers and the sleep and cognitive function of mission controllers who participated in a high-fidelity 105-day simulated spaceflight mission at the Institute of Biomedical Problems (Moscow). Crewmembers were required to perform daily mission duties and work one 24-h extended duration work shift every sixth day. Mission controllers nominally worked 24-h extended duration shifts. Supplemental lighting was provided to crewmembers and mission controllers. Participants' sleep was estimated by wrist-actigraphy recordings. Overall, results show that crewmembers and mission controllers obtained inadequate sleep and exhibited impaired cognitive function, despite countermeasure use, while working extended duration shifts. Crewmembers averaged 7.04±0.92 h (mean±SD) and 6.94±1.08 h (mean±SD) in the two workdays prior to the extended duration shifts, 1.88±0.40 h (mean±SD) during the 24-h work shift, and then slept 10.18±0.96 h (mean±SD) the day after the night shift. Although supplemental light was provided, crewmembers’ average nocturnal melatonin levels remained elevated during extended 24-h work shifts. Naps and caffeine use were reported by crewmembers during ∼86% and 45% of extended night work shifts, respectively. Even with reported use of wake-promoting countermeasures, significant impairments in cognitive function were observed. Mission controllers slept 5.63±0.95 h (mean±SD) the night prior to their extended duration work shift. On an average, 89% of night shifts included naps with mission controllers sleeping an average of 3.4±1.0 h (mean±SD) during the 24-h extended duration work shift. Mission controllers also showed impaired cognitive function during extended duration work shifts.These findings indicate that extended duration work shifts present a significant challenge to crewmembers and mission support specialists during long-duration space mission operations. Future research is needed to evaluate the efficacy of alternative work schedules and the development and implementation of more effective countermeasures will be required to maintain high levels of performance.     

Prediction of nonlinear pilot-induced oscillation using an intelligent human pilot model

This paper proposes a method to predict nonlinear Pilot-Induced Oscillation (PIO) using an intelligent human pilot model. This method is based on a scalogram-based PIO metric, which uses wavelet transforms to analyze the nonlinear characteristics of a time-varying system. The intelligent human pilot model includes three modules: perception module, decision and adaptive module, and execution module. Intelligent and adaptive features, including a neural network receptor, fuzzy decision and adaptation, are also introduced into the human pilot model to describe the behavior of the human pilot accommodating the nonlinear events. Furthermore, an algorithm is proposed to describe the procedure of the PIO prediction method with nonlinear evaluation cases. The prediction results obtained by numerical simulation are compared with the assessments of flight test data to validate the utility of the method. The flight test data were generated in the evaluation of the Smart-Cue/Smart-Gain, which is capable of reducing the PIO tendencies considerably. The results show that the method can be applied to predict the nonlinear PIO events by human pilot model simulation.