The use of Gaussian equations of motions of a satellite for local gravity anomaly recovery

The orbital elements of a low Earth orbiting satellite and their velocities can be used for local determination of gravity anomaly. The important issue is to find direct relations among the anomalies and these parameters. Here, a primary theoretical study is presented for this purpose. The Gaussian equations of motion of a satellite are used to develop integral formulas for recovering the gravity anomalies. The behaviour of kernels of the integrals are investigated for a two-month simulated orbit similar to that of the Gravity field and steady-state ocean circulation explorer (GOCE) mission over Fennoscandia. Numerical investigations show that the integral formulas have neither isotropic nor well-behaved kernels. In such a case, gravity anomaly recovery is not successful due to large spatial truncation error of the integral formulas. Reformulation of the problem by combining the orbital elements and their velocities leads to an integral with a well-behaved kernel which is suitable for our purpose. Also based on these combinations some general relations among the orbital elements and their velocities are obtained which can be used for validation of orbital parameters and their velocities.     

A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering

Multi-sensor image matching based on salient edges has broad prospect in applications, but it is difficult to extract salient edges of real multi-sensor images with noises fast and accurately by using common algorithms. According to the analysis of the features of salient edges, a novel salient edges detection algorithm and its rapid calculation are proposed based on possibility fuzzy C-means （PFCM） kernel clustering using two-dimensional vectors composed of the values of gray and texture. PFCM clustering can overcome the shortcomings that fuzzy C-means （FCM） cluster- ing is sensitive to noises and possibility C-means （PCM） clustering tends to find identical clusters. On this basis, a method is proposed to improve real-time performance by compressing data sets based on the idea of data reduction in the field of mathematical analysis. In addition, the idea that kernel-space is linearly separable is used to enhance robustness further. Experimental results show that this method extracts salient edges for real multi-sensor images with noises more accurately than the algorithm based on force fields and the FCM algorithm; and the proposed method is on average about 56 times faster than the PFCM algorithm in real time and has better robustness.     

基于小波变换和核独立分量分析的遥感图像变化检测

为了进一步提高基于独立分量分析(IndependentComponentAnalysis,ICA)的遥感图像变化检测精确度,并解决ICA分离的图像分量排序不确定问题,提出了基于小波变换和核独立分量分析(KernelIndependentComponentAnalysis,KICA)的遥感图像变化检测方法。首先通过小波变换对遥感图像进行分解,得到由图像的高频分量和低频分量组成的分块向量,然后利用核函数将分块向量映射到高维特征空间中,再在该空间中用ICA方法分离出互相独立的向量,最后根据分离出的向量中高频分量的差异自动分辨出变化分量。文章给出了遥感图像变化检测方法及近年提出的基于主分量分析(PrincipalComponentAnalysis,PCA)、基于ICA、基于KICA三种变化检测方法的试验结果,并进行了分析和定量比较。试验结果表明,文中方法能更好地分离出遥感图像的变化信息,具有更高的精确度,并实现了变化检测的智能化。     

基于逐步回归的模型误差估计及在天基测控系统中的应用研究

以双星定位系统的天基测控技术为应用背景,提出了一种能够自适应估计模 型误差的轨道确定方法。详细推导了观测模型中的系统误差形态,建立了能表征实际特征的 部分线性轨道改进模型,并利用二阶段法和核函数估计法对混合误差进行补偿,在此基础上 对补偿模型进行逐步回归分析,从中提取动力学模型误差,从而抑制了动力学模型误差的影 响,提高了轨道改进的精度。在本文的仿真环境下,部分线性轨道改进法能够有效抑制混合 误差对定轨精度的影响,提高天基测控的轨道确定精度。     

Convex optimisation approach to constrained fuel optimal control of spacecraft in close relative motion

This paper describes an interesting and powerful approach to the constrained fuel-optimal control of spacecraft in close relative motion. The proposed approach is well suited for problems under linear dynamic equations, therefore perfectly fitting to the case of spacecraft flying in close relative motion. If the solution of the optimisation is approximated as a polynomial with respect to the time variable, then the problem can be approached with a technique developed in the control engineering community, known as “Sum Of Squares” (SOS), and the constraints can be reduced to bounds on the polynomials. Such a technique allows rewriting polynomial bounding problems in the form of convex optimisation problems, at the cost of a certain amount of conservatism. The principles of the techniques are explained and some application related to spacecraft flying in close relative motion are shown.     

End-to-end trajectory design for a solar-sail-only pole-sitter at Venus,Earth, and Mars

The concept of a pole-sitter has been under investigation for many years, showing the capability of a low-thrust propulsion system to maintain a spacecraft at a static position along a planet’s polar axis. From such a position, the spacecraft has a view of the planet’s polar regions equivalent to that of the low- and mid-latitudes from geostationary orbit. Previous work has hinted at the existence of pole-sitters that would only require a solar sail to provide the necessary propulsive thrust if a slight deviation from a position exactly along the polar axis is allowed, without compromising on the continuous view of the planet’s polar region (a so-called quasi-pole-sitter). This paper conducts a further in-depth analysis of these high-potential solar-sail-only quasi-pole-sitters and presents a full end-to-end trajectory design: from launch and transfer to orbit design and orbit control. The results are the next steppingstone towards strengthening the feasibility and utility of these orbits for continuous planetary polar observation.     

一种基于核回归的改进型图像去噪方法

为了消除图像处理中的噪声,同时尽可能地保留图像细节,提出了一种基于核回归的图像去噪算法。该方法的基本思想是在经典方法以像素位置决定权值的基础上,引入像素灰度值。即核函数在计算权值时考虑两个因素:空间距离和灰度距离。通过计算控制核来做到自适应,最后引入一个迭代过程。实验结果表明该算法能够在滤除图像中的高频噪声的同时尽可能保留了图像的细节特征,获得了较为理想的去噪效果。     

不确定飞行环境下的滑翔制导炮弹方案弹道优化

滑翔制导炮弹因体积和成本所限存在控制能力有限的问题,有必要对其方案弹道加以合理的设计,为此提出一种不确定飞行环境下的弹道优化方法以降低方案弹道对各类随机干扰的敏感度。建立了模型偏差、滑翔启控点参数偏差、气动参数偏差及气象偏差等不确定性因素的数学模型,推导出计及随机干扰的滑翔弹动力学系统雅可比矩阵的解析表达式,利用线性协方差分析法,得到了系统误差传播方程,进而建立了不确定飞行环境下的弹道优化模型。利用Chebyshev伪谱法将弹道优化问题转换为非线性规划问题,在此基础上采用内点算法(Ipopt)获得了方案弹道的最优解。仿真结果表明,与不考虑不确定因素的设计方法相比,采用本文方法设计出的方案弹道,纵向和侧向位移散布方差明显减小,显示出对随机干扰更好的抑制效果。     

Multi-view space object recognition and pose estimation based on kernel regression

The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we proposed a kernel regression-based method for joint multi-view space object recognition and pose estimation. We built a new simulated satellite image dataset named BUAA-SID 1.5 to test our method using different image representations. We evaluated our method for recognition-only tasks, pose estimation-only tasks, and joint recognition and pose estimation tasks. Experimental results show that our method outperforms the state-of-the-arts in space object recognition, and can recognize space objects and estimate their poses effectively and robustly against noise and lighting conditions.     

基于改进ADC法的雷达阵地现场优化效能评估

针对雷达阵地现场优化的特点,分析了对抗条件下战场环境对雷达阵地现场优化效能的影响,建立了雷达阵地现场优化效能的指标体系,提出了一种改进型ADC模型,并通过实例分析验证了该方法的正确性和有效性,为雷达装备阵地现场优化提供了一定的参考依据。