Energy-efficient data collection for UAV-assisted IoT: Joint trajectory and resource optimization

Internet of Things (IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. As energy-efficient operations are critical to prolong the lifetime of the energy-constrained IoT devices, the Unmanned Aerial Vehicle (UAV) can be dispatched to geographically approach the IoT clusters towards energy-efficient IoT transmissions. This paper intends to maximize the system energy efficiency by considering both the IoT transmission energy and UAV propulsion energy, where the UAV trajectory and IoT communication resources are jointly optimized. By applying large-system analysis and Dinkelbach method, the original fractional optimization is approximated and reformulated in the form of subtraction, and further a block coordinate descent framework is employed to update the UAV trajectory and IoT communication resources iteratively. Extensive simulation results are provided to corroborate the effectiveness of the proposed method.     

Advanced analytical model for orbital aerodynamic prediction in LEO

The growing interest in low earth orbit (LEO) applications demands for accurate modeling of orbital aerodynamics. But classical analytical models of aerodynamic coefficients in free molecule flow, such as the Sentman’s model, Schamberg’s model and Schaaf-Chambre model, were built upon over simplistic gas-surface interaction models, which degrade the fidelity of aerodynamic prediction. This work presents a new analytical model of orbital aerodynamic coefficients based on the state-of-the-art Cercignani–Lampis–Lord (CLL) gas-surface interaction model, where lobular quasi-specular scattering pattern and separate accommodation degree for different velocity components can be well captured. A key component of the new model is a rigorous function approximation solution of the reflected normal momentum flux based on the CLL model which is derived for the first time and is validated within 1% for any hypothermal flow and surface accommodation conditions. Closed-form analytical solutions of aerodynamic coefficients for simple convex geometries are obtained and exhibit high accuracy (within 0.1%) in typical LEO scenarios. The new analytical model surpasses the classical models in some important aspects, such as overcoming the diffuse scattering hypothesis constraint, considering the variation of normal momentum exchange with the surface incidence angle and being applicable in any hypothermal flow situation. In virtue of the advanced CLL model and feasibility of coupling with the panel method technique, the new analytical model is promising to provide more accurate predictions on the orbital aerodynamic coefficients for LEO applications.     

FY-3(05)星主动对月定标控制技术研究

月球是低轨气象卫星载荷进行外定标的一个理想目标,不同载荷通过观测月球可以建立统一的参考基准,提高相互之间的数据匹配性。对于低轨卫星,月球一般每月一次进入载荷的视场,但停留时间只有几秒钟。为进一步提高对月定标的观测时长,积累更多的观测数据,本文针对低轨偏置动量卫星提出了一种主动对月定标控制方案,通过卫星平台的姿态控制,使月球在载荷视场中停留30 min以上。仿真结果表明:对月定标过程中卫星姿态控制精度满足指标要求,具备工程应用条件。     

基于低轨通信星座的导航增强技术发展概述

在我国北斗三号卫星导航系统全面完成组网建设的背景下,世界卫星导航步入新时代。各卫星导航大国均瞄准更高服务精度、更加多样功能、更加可靠服务,正在着手开展新一代系统建设和技术迭代。随着各国对于大型低轨通信星座的积极开发与广泛部署,应用低轨卫星技术实现导航增强与PNT系统备份能力,因其易与GNSS协同,具有提高全球自主导航精度、拓展全球卫星导航应用市场的巨大潜力而成为研究热点。面向低轨导航增强技术,首先总结了低轨卫星的最新态势,梳理了卫星导航增强服务模式,并详细分析了低轨通信星座导航精度增强及导航信号增强两方面的技术动向。在此基础上,重点针对导航增强频率的兼容互操作、通信/导航信号一体化设计、高动态导航增强信号捕获与跟踪等方面,对低轨卫星导航增强体系未来的发展机遇以及面临的技术挑战进行了展望。此外,还基于美国铱星系统实收采集信号开展了定位服务性能试验分析,结果表明600个历元内收敛定位精度优于100m,相关分析成果可为我国低轨导航增强建设提供参考和借鉴。     

未知纬度条件下基于空间圆拟合的SINS初始对准方法

传统的捷联惯导系统(SINS)晃动基座初始对准算法,如积分双矢量方法和多矢量Wahba方法等均需要精确的纬度信息,粗对准偏航角误差较大.针对此特点,提出了一种未知纬度条件下基于空间圆拟合的SINS初始对准方法.根据重力矢量在惯性系中绕地轴旋转包含北向信息的特征,以初始时刻凝固载体坐标系作为惯性系,首先对重力矢量在凝固载体系内进行投影并滤波,对其矢量端点进行空间圆拟合,然后通过三角几何关系得到导航坐标系,从而完成对准过程.通过仿真验证,证实了该对准方法不需要已知对准点的精确位置信息,相比于积分双矢量方法与多矢量Wahba方法,偏航角对准精度分别提高了12.37'与5.10'.