基于成败试验的导弹贮存可靠性Bayes分析模型

针对传统导弹贮存可靠性分析方法的缺点, 提出了一种Bayes分析模型.这种模型以狄氏分布为先验分布, 综合利用了历史信息和专家信息, 结合导弹检测时间段的成败试验数据, 给出了各检测时间段可靠性的联合后验分布, 然后利用Gibbs抽样算法进行后验推断, 得到了各阶段可靠性的Bayes估计和区间估计.此外, 基于当前试验数据, 利用这种模型以预测未来导弹贮存可靠性.算例表明这种Bayes模型参数含义清楚, 利于工程应用.      

一种基于二次组阵的DOA估计方法

提出一种基于二次组阵的信号到达方向估计方法,在阵列中通过划分相互重叠的子阵对指定的空间区域进行空域滤波波束设计实现对空间信号的干扰抑制,提高期望信号的信干噪比。根据子阵间的位置关系对阵列进行二次组阵,用空间谱估计方法实现对各子阵输出期望信号的到达方向（DOA）估计。仿真结果表明：与常规谱估计方法相比,基于二次组阵的DO...     

Efficient and accurate online estimation algorithm for zero-effort-miss and time-to-go based on data driven method

This paper introduces a novel and efficient algorithm for online estimation of zero-effortmiss and time-to-go based on data driven method.Only missile-target separations are utilized to construct the estimation models, and a practical Fisher fusion algorithm is derived to acquire the estimates with high accuracy and computational efficiency.Further, the two parameters can be online estimated at a particular time.Meanwhile, the kinematics equations of the missile-target engagement are independent, and assumptions of the missile guidance system dynamics and behaviors of the missile and target are completely out of consideration.Moreover, the effectiveness and applicability are explicitly verified through various simulation scenarios.     

A multi-rate sensor fusion approach using information filters for estimating aero-engine performance degradation

Gas-path performance estimation plays an important role in aero-engine health management, and Kalman Filter(KF) is a well-known technique to estimate performance degradation. In previous studies, it is assumed that different kinds of sensors are with the same sampling rate, and they are used for state estimation by the KF simultaneously. However, it is hard to achieve state estimation using various kinds of sensor measurements at the same sampling rate due to a complex network and physical characteristic differences between sensors, especially in an advanced multisensor architecture. For this purpose, a multi-rate sensor fusion using the information filtering approach is proposed based on the square-root cubature rule, which is called Multi-rate Squareroot Cubature Information Filter(MSCIF) to track engine performance degradation. Soft measurement synchronization of the MSCIF is designed to provide a sensor fusion condition for multiple sampling rates of measurement, and a fault sensor is isolated by maximum likelihood validation before state estimation. The contribution of this paper is to supply a novel multi-rate informationfilter approach for sensor fault tolerant health estimation of an aero-engine in a multi-sensor system. Tests are conducted for aero-engine performance degradation estimation with multiple sampling rates of sensor measurement on both digital simulation and semi-physical experiment.Experimental results illustrate the superiority of the proposed algorithm in terms of degradation estimation accuracy and robustness to sensor failure in a multi-sensor system.     

GNSS卫星钟差估计与结果分析

探讨了GNSS卫星钟差估计的基本原理、处理方法及数据处理中的一些关键技术,利用全球56个IGS跟踪站的观测数据进行钟差估计,比较分析了钟差产品的精度与定位性能。以GPS系统解算结果为例,其钟差产品与IGS最终精密卫星钟差符合较好,精度优于0.04ns(约0.012m),多系统钟差解算结果互差优于亚纳秒级。基于钟差产品进行精密单点定位解算试验,试验结果表明,在定位收敛之后,静态PPP在东、北、天3个方向上精度为0.0582m、0.0466m、0.1188m;动态PPP在东、北、天3个方向上精度为0.0671m、0.0640m、0.3200m。定位结果与IGS最终精密钟差解算结果符合较好,表明两者之间差异较小,进一步验证了解算得到的卫星钟差产品的定位性能。     

基于UKF的大失准角船舶行进间对准技术研究

由于标准卡尔曼滤波只适用于线性系统,通常在SINS/GPS组合导航初始对准过程中,先通过基于惯性系的粗对准方法,将失准角转化为小量,然后再进行卡尔曼滤波精对准。由于杆臂效应,使用的基准信息存在一定误差,导致初始对准精度降低。因此,首先设计UKF的大失准角初始对准算法;其次将基准信息杆臂在UKF方程中建模,对杆臂误差进行补偿;最后通过仿真验证算法的可行性,并利用海试实验数据对UKF算法与传统动基座算法进行对比,实验结果表明该方法具有明显优势。     

一种基于星表特征直线匹配的着陆器位姿估计算法

针对深空探测星际着陆过程中的自主导航问题,提出一种基于星表特征直线的着陆器位姿估计算法。该算法首先采用EDLine算法对着陆过程中所拍摄的图像进行特征直线提取;其次根据直线局部特征对特征直线进行匹配;之后利用至少3对已匹配的特征直线,建立关于着陆器位姿的几何约束方程;然后根据奇异值分解法得到着陆器位姿的候选解;最终通过最小二乘法从候选解中选取着陆器位置、姿态的唯一解。仿真结果表明:该算法可以快速估计着陆器位姿,且在高度为2 000 m时位置误差小于2 m、姿态误差小于0.10°。     

基于目标逃逸机动预估的空空导弹可发射区

为适应无人自主空战条件下对空空导弹火控解算的特殊需求,提出了基于目标机动预估的空空导弹可发射区问题。首先,基于导弹-目标追逃对抗策略,设计了目标机动预估模型,根据导弹与目标的相对方位信息,实现对目标逃逸机动方式的预估;然后,基于多种实际约束,构建了导弹运动动力学模型;最后,设计了基于黄金分割搜索算法的可发射区边界求解策略,实现对可发射区边界值的快速精确搜索。仿真结果表明,空空导弹对初始位置位于所提出的基于目标机动预估的可发射区内的目标,具有更大的命中概率;该可发射区更加适应近距空战中目标逃逸机动的剧烈态势变化,有利于导弹战术使用性能的充分发挥。      

Autonomous space target tracking through state estimation techniques via ground-based passive optical telescope

The presence of operational satellites or small-body space debris is a challenge for autonomous ground-based space object observation. Although most space objects exceeding 10?cm in diameter have been cataloged, the position of each space object (based on six orbital parameters) remains important and should be updated periodically, as the Earth’s orbital perturbations cause disturbances. Modern ground-based passive optical telescopes equipped with complementary metal-oxide semiconductors have become widely used in astrometry engineering, being combined with image processing techniques for target signal enhancement. However, the detection and tracking performance of this equipment when employed with image processing techniques primarily depends on the size and brightness of the space target, which appears on the monitor screen under variable background interference conditions. A small and dim target has a highly sensitive tracking error compared to a bright target. Moreover, most image processing techniques for target signal enhancement require large computational power and memory; therefore, automatic tracking of a space target is difficult. The present work investigates autonomous space target detection and tracking to achieve high-sensitivity detection and improved tracking ability for non-Gaussian and dynamic backgrounds with a simple system mechanism and computational efficiency. We develop an improved particle filter (PF) using the ensemble Kalman filter (KF) for track-before-detect (TBD) frameworks, by modifying and optimizing the computational formula for our non-linear measurement function. We call this extended version the “ensemble Kalman PF-TBD (EnKPF-TBD).” Three sequential astronomical image datasets taken by the Asia-Pacific Ground-Based Optical Space Objects Observation System (APOSOS) telescope under different conditions are used to evaluate three proposed TBD baseline frameworks. Given an optimal random sample size, the EnKPF-TBD exhibits superior performance to PF-TBD and threshold-based unscented KF with two-dimensional peak search (2dPS). The EnKPF-TBD scheme achieves satisfactory performance for all variable background interference conditions, especially for a small and dim space target, in terms of tracking accuracy and computational efficiency.     

非高斯杂波背景中距离扩展目标的盲积累检测器

在采用球不变随机向量(SIRV)建模的非高斯杂波背景下,研究了导向矢量失配或未知时距离扩展目标的检测问题。先假设导向矢量已知,采用广义似然比检验(GLRT)得到每个距离单元的归一化匹配滤波器(NMF)统计量,再将多个距离单元的统计量进行非相干积累得到扩展目标的NMF积累检测器(NMFI),然后通过最大化检测统计量的方法,结合特征值分解技术,对导向矢量进行估计,提出了距离扩展目标的盲NMFI(B-NMFI)。仿真分析表明:当导向矢量失配时,NMFI的检测性能优于GLRT;当导向矢量未知时,B-NMFI能有效地检测目标,并且对不同方位的目标具有很好的鲁棒性。