车速台速度脉冲信号的处理方法研究

在简单介绍车速表检测的必要性以及车速表检测台分类基础上,讲解了霍尔元件测量速度脉冲的原理;结合实际应用中出现的问题,针对大量的试验数据结果进行分析研究后,得出一种科学合理的脉冲信号测量处理方法,使测量结果得到明显改善。     

飞行器散射中心的超分辨力诊断

高/超分辨力微波成像诊断测量是隐身飞行器设计的重要手段。本文讨论飞行器的超分辨力微波成像诊断测量技术,研究了四种微波成像算法,给出了微波暗室测量条件下,利用各种算法对飞机模型成像的结果。     

Reliability and safety analysis of redundant vehicle management computer system

Redundant techniques are widely adopted in vehicle management computer （VMC） to ensure that VMC has high reliability and safety. At the same time, it makes VMC have special characteristics, e.g., failure correlation, event simultaneity, and failure self-recovery. Accordingly, the reliability and safety analysis to redundant VMC system （RVMCS） becomes more difficult. Aimed at the difficulties in RVMCS reliability modeling, this paper adopts generalized stochastic Petri nets to establish the reliability and safety models of RVMCS. Then this paper analyzes RVMCS oper- ating states and potential threats to flight control system. It is verified by simulation that the reli- ability of VMC is not the product of hardware reliability and software reliability, and the interactions between hardware and software faults can reduce the real reliability of VMC obviously. Furthermore, the failure undetected states and false alarming states inevitably exist in RVMCS due to the influences of limited fault monitoring coverage and false alarming probability of fault mon- itoring devices （FMD）. RVMCS operating in some failure undetected states will produce fatal threats to the safety of flight control system. RVMCS operating in some false alarming states will reduce utility of RVMCS obviously. The results abstracted in this paper can guide reliable VMC and efficient FMD designs. The methods adopted in this paper can also be used to analyze other intelligent systems＇ reliability.     

Highly reliable relative navigation for multi-UAV formation flight in urban environments

Formation flight of multiple Unmanned Aerial Vehicles (UAVs) is expected to bring significant benefits to a wide range of applications. Accurate and reliable relative position information is a prerequisite to safely maintain a fairly close distance between UAVs and to achieve inner-system collision avoidance. However, Global Navigation Satellite System (GNSS) measurements are vulnerable to erroneous signals in urban canyons, which could potentially lead to catastrophic consequences. Accordingly, on the basis of performing relative positioning with double differenced pseudoranges, this paper develops an integrity monitoring framework to improve navigation integrity (a measure of reliability) in urban environments. On the one hand, this framework includes a fault detection and exclusion scheme to protect against measurement faults. To accommodate urban scenarios, spatial dependence in the faults are taken into consideration by this scheme. On the other hand, relative protection level is rigorously derived to describe the probabilistic error bound of the navigation output. This indicator can be used to evaluate collision risk and to warn collision danger in real time. The proposed algorithms are validated by both simulations and flight experiments. Simulation results quantitatively reveal the sensitivity of navigation performance to receiver configurations and environmental conditions. And experimental results suggest high efficiency and effectiveness of the new integrity monitoring framework.     

Optimal trajectory and downlink power control for multi-type UAV aerial base stations

Unmanned Aerial Vehicles (UAVs) enabled Aerial Base Stations (UABSs) have been studied widely in future communications. However, there are a series of challenges such as interference management, trajectory design and resource allocation in the scenarios of multi-UAV networks. Besides, different performances among UABSs increase complexity and bring many challenges. In this paper, the joint downlink transmission power control and trajectory design problem in multi-type UABSs communication network is investigated. In order to satisfy the signal to interference plus noise power ratio of users, each UABS needs to adjust its position and transmission power. Based on the interactions among multiple communication links, a non-cooperative Mean-Field-Type Game (MFTG) is proposed to model the joint optimization problem. Then, a Nash equilibrium solution is solved by two steps: first, the users in the given area are clustered to get the initial deployment of the UABSs; second, the Mean-Field Q (MFQ)-learning algorithm is proposed to solve the discrete MFTG problem. Finally, the effectiveness of the approach is verified through the simulations, which simplifies the solution process and effectively reduces the energy consumption of each UABS.     

经验Bayes岭估计在GINS车载试验工具误差辨识中的应用

在利用车载试验进行GINS工具误差辨识过程中,由于输入加速度很小使得系统存在严重的复共线性。应用传统的最小二乘方法会出现增大最小二乘估计量的方差、参数估计值不稳定、产生弃真错误等问题。本文引入经验Bayes岭估计方法来进行GINS车载试验工具误差辨识工作。仿真结果表明,和传统最小二乘方法相比,经验Bayes岭估计的辨识精度有所提高,并可克服系统存在的复共线性的影响。     

高超声速冲压发动机-飞行器计力体系讨论

从吸气式高超声速飞行器受力分析出发,讨论如何统计飞行器受力的问题,建议在研究中使用增量法。这种方法将冲压发动机冷、热工况产生的力(力矩)增量视为飞行器运动分析中所需的"发动机推力或拉力",这个力或力矩分别叠加在飞行器冷通气状态的力或力矩上。这样,就与传统的飞行器运动方程中的力建立了一一对应的关系,可最大限度地使用以往建立的数据获取方法、分析软件、实验技术体系,将给后续工作带来极大的便利。另外,使用此方法,实验容易获得高质量的数据,通过大量容易组织的冷态实验也可使数值模拟的准确度大大提高,使未来飞行器的运动分析结果更可信。在这个体系下,内流道的冷工况阻力(轴向力)是高超声速冲压发动机与飞行器一体化需考虑的重要问题,一方面飞行器总体任务设计需限定内流道冷阻范围,另一方面要使发动机在要求的冷阻范围内高效工作,后者是高超声速发动机研究面临的严峻挑战。     

基于INS/前视声纳组合的输水隧洞AUV巡检定位方法

当潜航器(AUV)进行输水隧洞巡检时,多普勒测速仪(DVL)声波会对前视声纳图像产生干扰,针对这一问题提出了一种从AUV上卸载DVL,直接从前视声纳图像中提取栽体速度,而后和惯性测量单元(IMU)进行组合导航的方法.该方法根据前视声纳成像原理,建立起每相邻两帧声纳图像间载体的相对位移与配对特征点的图像坐标之间的联系,针对水底为局部平坦区域的情况,对特征点仰角进行了估算.通过惯导速度约束和随机抽样一致(RANSAC)算法,剔除误差较大的配对点,然后利用提取出的载体速度作为观测量进行卡尔曼滤波.经实际数据测试,惯性导航系统(INS)/前视声纳组合的总体性能和INS/DVL组合非常接近,以输水隧洞内的接缝线作为定位基准,INS/前视声纳组合导航在沿隧洞方向上的最大相对定位误差小于行程的1％.     

Aerial-ground collaborative routing with time constraints

The advancement of autonomous technology makes electric-powered drones an excellent choice for flexible logistics services at the last mile delivery stage. To reach a balance between green transportation and competitive edge, the collaborative routing of drones in the air and trucks on the ground is increasingly invested in the next generation of delivery, where it is particularly reasonable to consider customer time windows and time-dependent travel times as two typical time-related factors in daily services. In this paper, we propose the Vehicle Routing Problem with Drones under Time constraints (VRPD-T) and focus on the time constraints involved in realistic scenarios during the delivery. A mixed-integer linear programming model has been developed to minimize the total delivery completion time. Furthermore, to overcome the limitations of standard solvers in handling large-scale complex issues, a space-time hybrid heuristic-based algorithm has been developed to effectively identify a high-quality solution. The numerical results produced from randomly generated instances demonstrate the effectiveness of the proposed algorithm.     

Target localization based on cross-view matching between UAV and satellite

Matching remote sensing images taken by an unmanned aerial vehicle (UAV) with satellite remote sensing images with geolocation information. Thus, the specific geographic location of the target object captured by the UAV is determined. Its main challenge is the considerable differences in the visual content of remote sensing images acquired by satellites and UAVs, such as dramatic changes in viewpoint, unknown orientations, etc. Much of the previous work has focused on image matching of homologous data. To overcome the difficulties caused by the difference between these two data modes and maintain robustness in visual positioning, a quality-aware template matching method based on scale-adaptive deep convolutional features is proposed by deeply mining their common features. The template size feature map and the reference image feature map are first obtained. The two feature maps obtained are used to measure the similarity. Finally, a heat map representing the probability of matching is generated to determine the best match in the reference image. The method is applied to the latest UAV-based geolocation dataset (University-1652 dataset) and the real-scene campus data we collected with UAVs. The experimental results demonstrate the effectiveness and superiority of the method.