超构材料红外探测芯片的研究进展

在梳理超构材料的概念与发展历程的基础上,着重分析了超构材料对波长、偏振态、相位等电磁波参量的调控作用。结合红外探测芯片及成像系统的发展趋势,介绍了超构材料与红外探测芯片的结合,及其在双色/多色成像、偏振成像、高光谱成像等先进成像模式中的应用,以及国内外相关研究进展。     

Adaptive Square-Root Cubature–Quadrature Kalman Particle Filter for satellite attitude determination using vector observations

A novel algorithm is presented in this study for estimation of spacecraft?s attitudes and angular rates from vector observations. In this regard, a new cubature–quadrature particle filter (CQPF) is initially developed that uses the Square-Root Cubature–Quadrature Kalman Filter (SR-CQKF) to generate the importance proposal distribution. The developed CQPF scheme avoids the basic limitation of particle filter (PF) with regards to counting the new measurements. Subsequently, CQPF is enhanced to adjust the sample size at every time step utilizing the idea of confidence intervals, thus improving the efficiency and accuracy of the newly proposed adaptive CQPF (ACQPF). In addition, application of the q-method for filter initialization has intensified the computation burden as well. The current study also applies ACQPF to the problem of attitude estimation of a low Earth orbit (LEO) satellite. For this purpose, the undertaken satellite is equipped with a three-axis magnetometer (TAM) as well as a sun sensor pack that provide noisy geomagnetic field data and Sun direction measurements, respectively. The results and performance of the proposed filter are investigated and compared with those of the extended Kalman filter (EKF) and the standard particle filter (PF) utilizing a Monte Carlo simulation. The comparison demonstrates the viability and the accuracy of the proposed nonlinear estimator.     

Hybrid methods for determining time-optimal,constrained spacecraft reorientation maneuvers

Time-optimal spacecraft slewing maneuvers with path constraints are difficult to compute even with direct methods. This paper examines the use of a hybrid, two-stage approach, in which a heuristic method provides a rough estimate of the solution, which then serves as the input to a pseudospectral optimizer. Three heuristic methods are examined for the first stage: particle swarm optimization (PSO), differential evolution (DE), and bacteria foraging optimization (BFO). In this two-stage method, the PSO-pseudospectral combination is approximately three times faster than the pseudospectral method alone, and the BFO-pseudospectral combination is approximately four times faster; however, the DE does not produce an initial estimate that reduces total computation time.     

HW/SW Co-design of the Instrument Control Unit for the Energetic Particle Detector on-board Solar Orbiter

ESA’s medium-class Solar Orbiter mission is conceived to perform a close-up study of our Sun and its inner heliosphere to better understand the behaviour of our star. The mission will provide the clues to discover how the Sun creates and controls the solar wind and thereby affects the environments of all the planets. The spacecraft is equipped with a comprehensive suite of instruments. The Energetic Particle Detector (EPD) is one of the in-situ instruments on-board Solar Orbiter. EPD is composed of five different sensors, all of them sharing the Instrument Control Unit or ICU that is the sole interface with the spacecraft. This paper emphasises on how the hardware/software co-design approach can lead to a decrease in software complexity and highlights the versatility of the toolset that supports the development process. Following a model-driven engineering approach, these tools are capable of generating the high-level code of the software application, as well as of facilitating its configuration control and its deployment on the hardware platforms used in the different stages of the development process. Moreover, the use of the Leon2ViP virtual platform, with fault injection capabilities, allows an early software-before-hardware verification and validation and also a hardware–software co-simulation. The adopted solutions reduce development time without compromising the whole process reliability that is essential to the EPD success.     

Comprehensive optimization design of aerodynamic and electromagnetic scattering characteristics of serpentine nozzle

Comprehensive optimization design of serpentine nozzle with trapezoidal outlet was studied to improve its aerodynamic and electromagnetic scattering performance. Serpentine nozzles with different center offsets and different ratios of the bases of the trapezoidal outlet were generated based on curvature control regulation. Computational Fluid Dynamics (CFD) simulations have been conducted to obtain the flow field in the nozzle, and Forward-Backward Iterative Physical Optics (FBIPO) method was applied to study the electromagnetic scattering characteristics of the nozzle. Guarantee Convergence Particle Swarm Optimization (GCPSO) algorithm based on Radial Basis Function (RBF) neural network was used to optimize the geometry of the nozzle in consideration of its aerodynamic and electromagnetic scattering characteristics. The results show that the GCPSO method based on RBF can be used to optimize the aerodynamic characteristics of the internal flow and the scattering characteristics of the cavity of the serpentine nozzle with irregular outlet. The optimized model has a higher center offset and a lower ratio of the bases of the trapezoidal outlet after optimization compared to the original model. The optimized model leads to a slight change in aerodynamic performance, with a total pressure recovery coefficient increase of 0.31% and a discharge coefficient increase of 0.41%. In addition, the Radar Cross Section (RCS) decreases also by around 83.33% and the overall performance is significantly improved, with a decrease of the optimized objective function by around 38.74%.     

关于卫星姿态确定非线性滤波算法的研究

本文探讨了利用方位矢量和陀螺速率观测信息确定卫星姿态的问题。该问题实际上是一个非线性/非高斯状态滤波问题,因此,经典的基于EKF和UKF算法的姿态滤波器有可能失败,尤其是当初始状态的先验估计不可能精确得知的情况下。近来,粒子滤波理论已经开始应用于姿态确定问题,但是,这类算法往往需要大量的“粒子”,这对有限计算能力来说是一个沉重的负担。为此,本文尝试利用双重滤波方法,在每个序贯估计过程中,将有陀螺姿态确定问题暂时分解为1个四元数估计问题和1个陀螺常漂参数估计问题。本文提出了2个双重滤波器,包括1个姿态确定双重粒子滤波器和1个姿态确定的混合型滤波器。这两者都采用一个相同的四元数粒子滤波器,但在粒子重采样和平滑处理方面,不同于近来提出的类似滤波器。至于陀螺常漂估计,双重粒子滤波器发展了一个辅助粒子滤波器,而混合滤波器中则发展了一个参数UKF滤波器。通过与经典的姿态确定滤波器的仿真比较,证实了本文新提的2个算法的有效性和优越性。
     

航天器质量特性参数的在轨辨识方法

针对高精度姿态和轨道控制要求准确已知航天器质量特性的问题,提出了基于参数解耦的最小二乘法和基于PSO的非线性优化两种方法,以辨识航天器的质量、惯量和质心位置。第一种方法将惯量与质量和质心位置解耦后分别辨识;第二种方法则将参数辨识问题转换为非线性系统的全局优化问题,同时辨识出所有参数。所提出的方法均不需要假设航天器运动足够慢,克服了以往方法将待辨识参数的耦合关系强行分离的缺点,采用辨识后的参数明显提高了航天器姿态及轨道控制性能。仿真结果验证了方法的有效性。     

基于精英群引导下量子粒子群算法的快速零陷形成技术

引入罚函数项,建立了一种新的发射波束方向图综合控零的多目标优化模型。用适应度值排序建立由种群非支配解组成的精英群,以精英群中的粒子作为全局最优解引导粒子飞行;用爬坡策略更新全局最优解,给出了基于精英群引导的量子粒子群算法。对阵列权值采用加权优化,可在发射波束指定方向的多零陷、宽凹口。仿真结果表明：算法对多目标的优化较文献算法更优,能优化阵列权值在指定方向快速形成零陷。     

基于粒子群算法的切削参数优化及其约束处理

切削参数优化问题通常是多约束、非线性的,通过对其目标函数进行分析,发现这类问题的最优解通常位于可行域边界上.针对该问题的求解,在约束处理方法上引入了非固定多段映射罚函数法和半可行域概念,并考虑到绝对半可行域宽度导致的不同约束条件难以同步得到满足问题,提出了相对半可行域设置方法,即将半可行域宽度与各约束许用值的相对误差相对应,应用于粒子群算法实现了切削参数优化,并通过实例计算对所提出的方法进行了验证.     

考虑观测的双冲量最优交会研究

针对跟踪星主动交会目标星的轨道转移问题,给出了考虑观测的双冲量最优交会迭代算法。首先对考虑观测的轨道交会问题进行了分析,给出了椭圆转移轨道的存在性判定方法。在此基础上,给出了基于粒子群的优化求解方案。经过对两异面椭圆轨道转移问题的仿真解算,求得了最优交会轨道,验证了算法的正确性。该研究成果可作为工程应用的有益参考,并为其他带约束的轨道交会优化问题提供可行的求解方案。