探测点序列的最优化与简化计算方法

在搜索状态建模和求解一阶搜索状态方程的特征迹线解的基础上,建立了对随机运动进行离散时间探测的发现概率最优控制模型,结合动态规划原理给出一种最优探测点序列的逼近算法,并给出了短时计算的算法简化形式。在满足一阶搜索状态方程的随机恒速目标条件以及有限指数探测函数条件下,将给出的算法及其简化形式应用到算例。算例表明,当随机恒速运动目标初始位置和速度均服从圆正态分布时,该算法及其简化形式均能够由任意给定的初始探测点序列优化收敛到满足精度要求的最优探测点序列。     

天基星空背景观测覆盖范围计算方法研究

针对日趋复杂的空间环境，天基观测由于其分布灵活和全天候观测的特性受到越来越多的关注，该类问题为典型的星空背景观测（above-the-horizon，ATH）问题。基于分段积分思想，提出了一种ATH观测三维空间覆盖范围的计算方法，涵盖了该问题所有可能的10种积分形式，适用于因观测约束参数不同取值而形成的任意几何构型场景。不仅在二维平面覆盖问题上与现有方法进行了比较并验证，还首次解决了ATH在三维空间中覆盖体积的定量解析计算难题。仿真结果表明，平面和空间覆盖最大化所对应的最优观测轨道高度存在明显差异，空间覆盖计算模型能更为准确有效地表示卫星覆盖性能，同时能为星座优化设计提供参考。     

Robust optimal sliding mode control for the deployment of Coulomb spacecraft formation flying

Inter-spacecraft electrostatic force (Coulomb force) is desirable for close formation flying control because of its propellant-less and free contaminate characteristics attributed to the propellant exhaust emission. This paper presents robust optimal sliding mode control to deal with the problem of thruster saturation in tracking the formation trajectory for Coulomb spacecraft formation flying. The robust controller design is based on optimal control theory as a linear quadratic system, and it is augmented with an integral sliding mode control technique. The stability of the closed-loop system is guaranteed using the second Lyapunov method. The developed controller outperforms the existing ones, because it has a higher degree of fine-tuning to cope with the uncertainty. Numerical simulations are employed to confirm the efficiency of the developed controller.     

力矩输出能力最优化混合执行机构操纵律设计

当航天器执行高动态敏捷机动或者姿态动态跟踪控制等任务时，常使用控制力矩陀螺（control moment gyroscope，简称CMG）和飞轮（reaction wheel，简称RW）构成的混合执行机构来提供大力矩。提出了基于力矩输出能力最优化的混合执行机构操纵律，从几何角度出发，给出了力矩输出能力最优的CMG框架角速度和RW角加速度，通过引入参数，并讨论参数的设置的最优，使得框架转速误差和输出力矩误差的混合二次型达到最小，保证了混合执行机构在输出力矩误差最小的情况下，力矩输出能力最优。以金字塔构型的CMG集群和正交的RW集群构成的混合执行机构为例，对基于力矩输出能力最优化的混合执行机构操纵律进行合理化分析，证明了引入参数的作用，并且证明了混合执行机构不存在CMG奇异情况。仿真结果表明，基于力矩输出能力最优化的混合执行机构操纵律解决了CMG奇异的问题并使得RW不陷入饱和，输出力矩误差较小，输出力矩能力强，能够应用于航天器大角度机动任务。     

柔性基座冗余机械臂的最优反作用控制

针对柔性基座冗余机械臂的末端轨迹跟踪问题，提出一种反作用最优控制方法，该算法将轨迹跟踪视为高优先级任务，而反作用优化控制在高优先级任务零空间内进行。由于冗余机械臂的自运动能在不影响末端运动的前提下改变关节运动，利用冗余机械臂的自运动消除振动系统中的低阶模态力，使机械臂在完成轨迹跟踪的同时激起的弹性振动大幅减小，从而提高了系统的稳定性。以平面3自由度柔性基座机械臂和空间7自由度柔性基座机械臂为例进行数值仿真，证实了方法的有效性。     

Frequency steering of spaceborne clocks based on XPNAV-1 observations

Due to high stable rotations, timing of pulsars provides a natural tool to correct the frequency deviation of spaceborne atomic clocks. Based on processing the observational data about a year of Crab pulsar given by XPNAV-1 satellite, we study the possibility of correcting the frequency deviation of spaceborne atomic clocks using pulsar timing. According to the observational data in X-ray band and the timing model parameters from radio observations, the pre-fit timing residuals with a level of 6...     

Robust extension of the simple sea-surface irradiance model to handle cloudy conditions for the global ocean using satellite remote sensing data

Sea-surface solar radiation (abbreviated as photosynthetically available radiation, PAR) in the visible wavelength (400–700 nm) is an essential parameter to estimate marine primary productivity and understanding phytoplankton dynamics, upper ocean physics and biogeochemical processes. Although many remote-sensing models were developed to estimate daily PAR (DPAR) from ocean colour data, these models often produce biases in the DPAR products under cloudy-sky and complex atmospheric conditions due to the lack of parameterization to deal with the cloud cover conditions and insufficient in-situ DPAR data. This study presents an Extended Sea-surface Solar Irradiance Model (ESSIM) for estimating DPAR over the global ocean. The ESSIM uses the direct and diffuse components from the Simple sea-surface Solar Irradiance Model (SSIM) along with a new parameter to handle cloudy conditions. The ESSIM produced DPAR products with greater accuracy under both clear and cloudy conditions. Its performance was tested on the time-series MODIS-Aqua images and compared with the concurrent in-situ data and the results from two global models. Results showed that the DPAR values produced by ESSIM agree with in-situ data better than the global models for all-sky conditions (with a mean relative error of 11.267 %; a root mean square error of 5.563 Em^?2day^?1; and a mean net bias of 2.917 Em^?2day^?1). The ESSIM performed slightly better than the SSIM for clear conditions and the Frouin's Operational Algorithm (FOA) for all-sky conditions. As the new parameterization accounts for cloudy conditions, the ESSIM produced more accurate results for cloud cover conditions across latitudes (up to 60°). The time-series Level-3 binned MODIS-Aqua data (global gridded) also demonstrated that the ESSIM improved the accuracy of DPAR products and produced spatially and temporally consistent DPAR products over the global ocean regardless of the seasons and sky conditions.