基于数据关联性分析的飞轮异常检测

针对航天器早期故障在闭环系统下难以被检测、数学模型难以精确建立的问题,提出了一种基于数据关联性分析的归纳式系统异常监测(IMS)方法。该方法采用无监督学习的聚类算法,利用具有关联性的参数构建数据向量,通过聚类分析自动建立健康数据向量的族类阈值区间。关联关系的破坏将引起部分参数超出族类阈值区间,使系统的异常程度存在模糊性与随机性。引入云模型评价指标,将闭环系统异常程度的不确定性通过熵与超熵定量表示,从而更加准确地判断闭环系统的异常程度。仿真结果表明:该方法能够建立卫星飞轮闭环系统的族类知识库,并可以根据云模型提供的定性知识有效判断系统的异常程度。     

应用数据挖掘关联技术研究温湿度对冲击谱试验的影响

冲击谱试验随机性强,难度较大,必须了解环境温度、湿度对试验的影响。通过对数据预处理并建立冲击谱试验评价模型,应用数据挖掘中关联分析方法提取数据背后隐藏的有用知识,获得了温度、湿度对冲击谱试验各个调试因素的影响,并分析了其间存在的某种规律性,找出了适用于冲击谱试验的环境温度、湿度范围。研究结果可为今后的产品冲击环境试验提供有力的技术支持,进一步提高冲击谱试验的试验质量和试验中的产品安全性。     

Multi-EAP:Extended EAP for multi-estimate extraction for SMC-PHD filter

The ability to extract state-estimates for each target of a multi-target posterior, referred to as multi-estimate extraction (MEE), is an essential requirement for a multi-target filter, whose key performance assessments are based on accuracy, computational efficiency and reliability. The probability hypothesis density (PHD) filter, implemented by the sequential Monte Carlo approach, affords a computationally efficient solution to general multi-target filtering for a time-varying num-ber of targets, but leaves no clue for optimal MEE. In this paper, new data association techniques are proposed to distinguish real measurements of targets from clutter, as well as to associate par-ticles with measurements. The MEE problem is then formulated as a family of parallel single-estimate extraction problems, facilitating the use of the classic expected a posteriori (EAP) estima-tor, namely the multi-EAP (MEAP) estimator. The resulting MEAP estimator is free of iterative clustering computation, computes quickly and yields accurate and reliable estimates. Typical sim-ulation scenarios are employed to demonstrate the superiority of the MEAP estimator over existing methods in terms of faster processing speed and better estimation accuracy.     

Loopy belief propagation based data association for extended target tracking

The data association problem of multiple extended target tracking is very challenging because each target may generate multiple measurements. Recently, the belief propagation based multiple target tracking algorithms with high efficiency have been a research focus. Different from the belief propagation based Extended Target tracking based on Belief Propagation (ET-BP) algorithm proposed in our previous work, a new graphical model formulation of data association for multiple extended target tracking is proposed in this paper. The proposed formulation can be solved by the Loopy Belief Propagation (LBP) algorithm. Furthermore, the simplified measurement set in the ET-BP algorithm is modified to improve tracking accuracy. Finally, experiment results show that the proposed algorithm has better performance than the ET-BP and joint probabilistic data association based on the simplified measurement set algorithms in terms of accuracy and efficiency. Additionally, the convergence of the proposed algorithm is verified in the simulations.     

基于正弦拟合的空间目标短弧关联算法

星敏感器是一种高精度姿态传感器，具有断续拍摄空间目标的能力，可作为空间目标监视平台。将星敏感器断续观测的短弧准确关联是实现空间目标精确定轨的前提。通过对空间目标的大量观测数据统计发现，空间目标的赤纬随赤经的变化始终满足一条周期为360°的正弦曲线且峰值与轨道倾角有关。对新旧航迹的赤经赤纬变化规律进行研究，提出一种基于正弦拟合的空间目标短弧关联算法，避免了空间目标初定轨的步骤，节约了算法运行时间。仿真中观测时长最短为50s，通过对目标密集的GEO带增加额外约束，可区分倾角相差0.01°的轨道。当航迹段间隔3h时，3组噪声水平目标关联的准确率均达90%以上。     

观测数据关联的泰勒展开径向速率方法

针对近地空间目标编目探测中,双屏电子篱笆的观测数据关联判断的问题,提出一种基于泰勒展开的径向速率数据关联方法。该方法对关联判断中径向速率这一判别量的计算采用泰勒展开的方式;与传统方法相比,该方法不需要进行地心地固坐标系与地心惯性系坐标转换,也不需要迭代计算初轨根数,具有简单、快速、符合精度需求的特点。在双屏电子篱笆探测LEO(Low Earth Orbit,低地球轨道)cm级空间目标的应用仿真中,该方法与使用初轨确定结果的径向速率方法相比,判断正确率基本相同,但所需计算时间比后者低一个数量级。因此,所述方法的判断效率较高,可为编目探测系统的数据处理流程提供参考。     

空基多雷达航迹抗差关联算法

基于高斯随机矢量统计特性,推导出一种适用于探测距离较远、系统误差时变、雷达上报目标不一致等复杂环境的空基多雷达航迹抗差关联算法。分解航迹距离矢量,对消系统误差矢量得出适用于3个及3个以上雷达的航迹抗差关联条件和流程。分别设置了目标密集程度、随机误差和系统误差适应性实验验证算法性能。仿真结果表明所提算法的关联准确性和复杂环境适应性相比现有的基于参照拓扑特征的航迹关联算法（RET算法）和基于距离检测的可信关联算法（confidential算法）有较大幅度的提升。     

利用有限仿射酉空间中的点构作多个结合类的结合方案

设A∪G(n,Fq2)是Fq2上的n维仿射酉空间。利用A∪G(n,Fq2)中的点作处理构作了一个类数为q的结合方案,并且计算了其全部参数。     

利用有限仿射辛空间中超平面构作结合方案

设Fq是一个q元域，用Fq上仿射辛空间中的全部超平面构作了类数为3的结合方案，并计算了参数。     

基于云模型的关联规则的提取算法

关联规则的提取是数据库应用领域研究的一个重要课题。如何发现普通数据库中各属性之间的关联, 也称为数量相关问题,具有更为普遍的意义。