飞机顶层需求捕获经验介绍

飞机顶层需求是飞机研制过程的关键环节。长期以来,对飞机研制中的需求捕获和分析工作一直用自然语言定性或定量地描述,主观因素较多。采用系统工程过程思维,对需求捕获经验进行了描述,通过过程控制来保证最终获得的飞机顶层需求文件的完整性、全面性、正确性和可实施性。     

环境激励下基于chirplet变换的线性时变系统参数识别

提出了针对时变系统响应的短时频率线性时变假设,通过将时变响应拟合成多分量线调频信号,根据线调频信号互相关理论推导了随机白噪声激励下时变系统的物理参数识别方法。该识别方法只需基于结构的加速度响应,便能识别结构的时变质量和刚度。由于引入了调频斜率刻画响应信号的短时频率线变特征,该方法相比传统识别方法能更好地追踪快变甚至突变参数,对实际工程中的时变问题具有重要的应用价值。仿真算例中构造了1个3自由度时变结构模型,针对线性时变、周期时变和突变等情况进行了物理参数的识别,误差分析显示识别误差均在5%以内,仿真结果验证了方法的正确性和适用性。     

民用飞机系统需求确认研究

本文从系统工程的角度和民机设计的要求出发,主要讨论了民用飞机系统开发过程中需求的确认工作.需求相关工作是系统设计的一个起点,对于后续的工作将会产生巨大的影响.为了降低风险和研发成本,在设计之初首先需要做好系统的需求确认工作,保证需求的正确性和完备性,这样才能保证设计实现的正确性,最终实现项目的成功.本文从适航性的角度出发,着重描述了系统需求确认工作的流程和相关的确认方法.希望通过这篇文章能够为高度综合、复杂的飞机系统设计研制提供必要的支持     

Space Flight Validation of Design and Engineering of the ZDPS-1A Pico-satellite

The ZDPS-1A pico-satellites are the first satellites in China within the 1-10 kg mass range that are successfully operated on orbit. Unlike common pico-satellites, they are designed to be "larger but stronger" with more powerful platforms and unique payloads so as to bear a better promise for real applications. Through their space flight mission, the functionality and performance of the two flight models are tested on orbit and validated to be mostly normal and in consistency with design and ground tests with only several inconforming occasions. Moreover, they have worked properly on orbit for one year so far, well exceeding their life expectancy of three months. Therefore, the space flight mission has reached all its goals, and verified that the design concept and the engineering process of the picosatellites are sufficient in allowing them the desired functionality and performance in, and the adaption to the launch procedure and the low-Earth orbit space environment. In the foreseeable future, the platform together with the design concept and the engineering process of the pico-satellites are expected to be applied to more complicated real space applications.     

A novel data association scheme for LEO space debris surveillance based on a double fence radar system

The increasing amount of space debris threatens to seriously deteriorate and damage space-based instruments in Low Earth Orbit (LEO) environments. Therefore, LEO space debris surveillance systems must be developed to provide situational awareness in space and issue warnings of collisions with LEO space debris. In this paper, a double fence radar system is proposed as an emerging paradigm for LEO space debris surveillance. This system exhibits several unique and promising characteristics compared with existing surveillance systems. In this paper, we also investigate the data association scheme for LEO space debris surveillance based on a double fence radar system. We also perform a theoretical analysis of the performance of our proposed scheme. The superiority and the effectiveness of our novel data association scheme is demonstrated by experimental results. The data used in our experiments is the LEO space debris catalog produced by the North American Air Defense Command (NORAD) up to 2009, especially for scenarios with high densities of LEO space debris, which were primarily produced by the collisions between Iridium 33 and Cosmos 2251. We hope that our work will stimulate and benefit future work on LEO space debris surveillance approaches and enable construction of the double fence radar system.     

基于URTS平滑建议分布函数的PF算法设计及应用

为改善基于Unscented Kalman滤波建议分布函数的粒子滤波状态估计的性能,将Unscented Kalman滤波与RTS（Rauch-Tung-Striebel）固定区间平滑算法融合,产生了一种新的建议分布函数--Unscented RTS平滑建议分布函数。该函数首先实施Unscented Kalman滤波,之后对此滤波结果进行RTS固定区间平滑,以此产生预测样本。以此新建议分布函数得到的预测粒子的精度较通常的以Unscented Kalman滤波方法作为建议分布函数时得到的预测粒子的精度将大为提高,进而提高相应的粒子滤波算法--PF URTS的状态估计精度。新算法的可行性和有效性在GPS/DR组合导航数据处理中得到了应用验证。     

资源受限嵌入式机电控制系统功耗感知调度

针对嵌入式机电控制系统的能耗受限问题,提出了一种基于功耗感知和反馈调度的能耗管理方法.研究了嵌入式机电控制系统的静态功耗调度模型,提出了一种基于控制代价和系统能耗的联合优化指标,并给出了其优化解.针对在动态调度模型下运算开销大,难以在线实现的问题,采用智能计算方法逼近优化结果.对比了4种智能计算方法的逼近精度和调度开销,采用小波神经网络逼近优化结果.仿真的结果表明:该方法在保证了控制性能的同时,降低了调度开销和系统能耗.      

High-precision single-input control of relative motion in spacecraft formation

A Newton-type method is proposed to improve the accuracy of control for relative motion of two satellites in close formation. We assume that the deputy satellite is equipped with a passive attitude control system that provides one-axis stabilization, and one or two orbit control thrusters are installed along the stabilized axis. Previous studies show that it is possible to construct periodic relative trajectories both in case of passive magnetic and spin stabilization. However, the accuracy of the numerically obtained control is quite low due to modeling errors caused by linearization of the equations of relative motion. Therefore, a correction procedure is required to compensate for nonlinear effects. To this end we suggest a recently developed algorithm based on the Newton method for solving nonlinear systems with geometric constraints. Being implemented, this algorithm allows decreasing the modeling error by up to ten times. The previously found control and trajectory of the linearized system are used as initial approximations.     

基于GPU的高光谱遥感主成分分析并行优化

主成分分析（principal component analysis, PCA）是高光谱遥感图像特征提取的重要方法。为了在保证精度的同时,提高高光谱遥感PCA算法的计算效率,文章提出一种基于图形处理器（graphic processing unit,GPU）＋中央处理器（central processing unit,CPU）异构系统的PCA并行优化方法。该方法利用GPU的并行计算能力实现PCA中复杂的协方差矩阵计算与维数缩减过程,优化了像元去均值的计算流程;解决了GPU内核计算像元累加和非合并访问问题;利用共享内存机制,提高了访存效率。此外,该方法采用改进的Jacobi快速迭代法在CPU中进行特征分解,保证了算法的精度。实验结果表明,该方法在保证精度的同时能够有效提高计算效率,在Quadro600平台上的加速比达到141倍,满足了高光谱遥感图像实时应用的需求。     

Modeling and parameter identification of linear time-varying systems based on adaptive chirplet transform under random excitation

In this paper, a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying (LTV) systems under random excitation is presented. It is assumed that the solution of responses of LTV structures is expressed as the sum of multicomponent Linear Frequency Modulated (LFM) signals in a short-time. Then the measured acceleration response is used to perform the adaptive chirplet transform, in which an integral algorithm is employed to reconstruct the velocity and displacement responses. The vibration differential equation with time-varying coefficients is transformed into a simple linear equation. Furthermore, for systems under random excitation, the input–output relation based on correlation function is also derived to estimate the parameters including physicals parameters and instantaneous modal parameters. The full procedure of the method is presented and validated by using simulated responses. The results show that the presented method is accurate and robust for various LTV systems under random excitation.