Image Smearing Modeling and Verification for Strapdown Star Sensor

To further extend study on celestial attitude determination with strapdown star sensor from static into dynamic field, one prerequisite is to generate precise dynamic simulating star maps. First a neat analytical solution of the smearing trajectory caused by spacecraft attitude maneuver is deduced successfully, whose parameters cover the geometric size of optics, three-axis angular velocities and CCD integral time. Then for the first time the mathematical law and method are discovered about how to synthesize the two formulae of smearing trajectory and the static Gaussian distribution function (GDF) model, the key of which is a line integral with regard to the static GDF attenuated by a factor 1/ L s (L s is the arc length of the smearing trajectory) along the smearing trajectory. The dynamic smearing model is then obtained, also in an analytical form. After that, three sets of typical simulating maps and data are simulated from this dynamic model manifesting the expected smearing effects, also compatible with the linear model as its special case of no boresight rotation. Finally, model validity tests on a rate turntable are carried out, which results in a mean correlation coefficient 0.920 0 between the camera images and the corresponding model simulated ones with the same parameters. The sufficient similarity verifies the validity of the dynamic smearing model. This model, after parameter calibration, can serve as a front-end loop of the ground semi-physical simulation system for celestial attitude determination with strapdown star sensor.     

Asymptotic Performance of Sparse Signal Detection Using Convex Programming Method

The detection of sparse signals against background noise is considered. Detecting signals of such kind is difficult since only a small portion of the signal carries information. Prior knowledge is usually assumed to ease detection. In this paper, we consider the general unknown and arbitrary sparse signal detection problem when no prior knowledge is available. Under a Neyman-Pearson hypothesis-testing framework, a new detection scheme is proposed by combining a generalized likelihood ratio test (GLRT)-like test statistic and convex programming methods which directly exploit sparsity in an underdetermined system of linear equations. We characterize large sample behavior of the proposed method by analyzing its asymptotic performance. Specifically, we give the condition for the Chernoff-consistent detection which shows that the proposed method is very sensitive to the 2 norm energy of the sparse signals. Both the false alarm rate and the miss rate tend to zero at vanishing signal-to-noise ratio (SNR), as long as the signal energy grows at least logarithmically with the problem dimension. Next we give a large deviation analysis to characterize the error exponent for the Neyman-Pearson detection. We derive the oracle error exponent assuming signal knowledge. Then we explicitly derive the error exponent of the proposed scheme and compare it with the oracle exponent. We complement our study with numerical experiments, showing that the proposed method performs in the vicinity of the likelihood ratio test (LRT) method in the finite sample scenario and the error probability degrades exponentially with the number of observations.     

B93铝合金热加工特性模拟研究

在Gleeble1500热模拟机上采用轴对称等温压缩实验,研究了B93铝合金在热加工中变形温度和应变速率对合金组织的影响,基于动态模型计算出B93铝合金加工图,分析合金热加工的流变失稳区并确定了合金热加工的最佳工艺参数。结果表明:变形速率和变形温度对B93铝合金的微观组织有影响;合金的峰值应力随变形温度的升高而降低,随变形速率的提高而增大;B93铝合金最佳的热加工制度为:变形温度420℃左右,应变速率0.001 s-1。     

一种基于三正交主轴平面的快速星图模拟方法

为在地面上进行星图模拟以测试星图识别算法和星敏感器性能, 提出了一种新的快速星图模拟方法. 该方法利用截面圆和固定区域的性质, 将单位天球按照三个正交主轴平面进行等分, 根据赤纬值求解恒星矢量与主轴平面夹角来确定选星条件, 进而根据坐标变换原理进行星图模拟. 为验证所提方法与现有方法相比的优势, 进行了大量的仿真实验. 实验结果表明, 与现有星图模拟方法相比, 本文方法在保证星图模拟精度的条件下, 选星速度提高了3倍以上.      

地磁图制备方法及其有效性评估

高精度地磁图制备是地磁匹配导航关键技术之一.在简单介绍4种网格插值方法原理的基础上(反距离加权插值法、克里金插值法、改进的谢别德插值法以及径向基函数法),应用实测地磁数据,选取测点分布较均匀区域,根据上述插值方法分别制备地磁图,并通过交叉验证统计准则对地磁图制备方法的有效性进行评估.结果表明,径向基函数插值法制备的地磁图"鸭蛋"形分布较少,地磁图等值线较圆滑,其标准偏差远小于其它方法的标准偏差,且其标准误差以及平均偏差也最小,具有较高的插值精度,能更好地反映该区域地磁场分布情况.     

基于稀疏贝叶斯学习的字典失配杂波空时谱估计方法

杂波谱稀疏恢复空时自适应处理（STAP）是一种有效减少杂波样本数需求的机载雷达杂波抑制方法。然而,空时平面被离散地划分为若干个网格点来构建空时导向矢量字典,当字典在失配时,杂波脊不能准确落在预先离散化的网格点上,稀疏恢复STAP性能严重下降。提出了一种基于稀疏贝叶斯学习的字典失配杂波空时谱估计方法,首先利用二维泰勒级数建立空时动态字典模型,然后将字典失配误差作为待估超参数构建贝叶斯稀疏恢复模型,并利用失配误差估计值对空时导向矢量字典进行修正,最后利用修正后的空时导向矢量字典重构杂波协方差矩阵,进而计算杂波空时谱。实验证明,该方法能够有效提高字典失配情况下的杂波谱稀疏恢复精度,杂波抑制性能优于已有字典预先离散化的稀疏贝叶斯学习STAP方法。     

基于数据挖掘的飞行器气动布局设计知识提取

为了更深入地理解飞行器气动布局设计优化中多目标/多设计变量间的影响关系,提高优化模型的科学性及优化效率,对基于数据挖掘技术的飞行器气动布局隐含设计知识提取问题开展了探索研究。以高升阻比滑翔飞行器布局设计优化问题为例,基于当前比较有代表性的方差分析、等度量映射、决策树、自组织映射4类机器学习算法对气动布局优化设计中产生的中间数据进行了挖掘分析。对不同方法得到的升阻比、横/侧向稳定性及容积率4种目标性能间的权衡关系,目标性能与设计变量间的敏感性关系及产生较优布局外形的设计变量取值规则进行了综合对比分析,凝练形成了适用于该类飞行器的设计知识,同时对4种方法的特点及适用性进行了总结分析,给出了相关结论。     

应用灰度特征的行星陨石坑自主检测方法与着陆导航研究

针对陨石坑阴影不明显的行星着陆导航图像,提出了基于图像灰度值特征的陨石坑自主检测方法,通过兴趣区快速确定陨石坑边缘分布,解决了一般陨石坑检测方法对图像太阳高度角的依赖问题。利用检测出的陨石坑视线信息,采用非线性预测滤波方法估计着陆器着陆阶段的位置和姿态;鉴于视觉着陆导航对照了场景状况的高度依赖性,提出了一种利用分形理论和相邻点分级方法的天体随机地景建模方法。最后验证了所提方法的有效性。     

Chaos and its avoidance in spinup dynamics of an axial dual-spin spacecraft

Attitude dynamics of a dual-spin spacecraft (DSSC) and a torque-free angular motion of a coaxial bodies system are considered. Some regimes of the heteroclinic chaos are described. The local chaotization of the DSSC is investigated at the presence of polyharmonic perturbations and small nutation restoring/overturning torques on the base of the Melnikov method and Poincaré Maps. Reasons of the chaotic regimes initiation at the spinup maneuver realization are studied. An approach for the local heteroclinic chaos escape/avoidance at the modification of the classical spinup maneuver is suggested.     

非圆信号的贝叶斯稀疏重构阵列测向方法

对信号非圆特性的有效利用能显著改善子空间类阵列测向方法的性能,但难以弥补此类方法在低信噪比（SNR）、小样本等信号环境适应能力方面的局限。本文引入贝叶斯稀疏学习（SBL）技术以解决非圆信号的波达方向（DOA）估计问题,在结合信号非圆特性的同时对入射信号的空域稀疏性加以利用,通过将非圆信号阵列输出协方差矩阵和共轭协方差矩阵在预先定义的空域字典集上进行稀疏重构,得到入射信号的空间谱重构结果,并依据其谱峰位置估计各信号的方向。该方法对独立和相关信号都具有较好的适应能力,仿真结果验证了该方法在信号环境适应能力和相关信号测向精度等方面的优势。