三轴稳定卫星无陀螺姿态确定算法研究

针对三轴稳定卫星进行了正常飞行模式下无陀螺姿态确定算法研究，采用磁强计、地球敏感器和太阳敏感器组合获得姿态数据，利用四元数法和高斯－马尔可夫过程建立了姿态确定估计器算法模型。通过数学仿真证明，此姿态确定算法能够对星体姿态进行较精确的估计或校正，满足卫星控制精度要求。     

基于数字滤波的B-样条插值法在图像旋转中的应用

提出一种基于无限脉冲响应和有限脉冲响应数字滤波技术的快速 B-样条插值法 ,并将其应用于实时图像旋转处理中。为了优化旋转后的图像质量 ,本文采用 3次 B-样条对图像旋转后的像素点灰度值进行插值运算。另外 ,通过对传统图像旋转矩阵的分解 ,将图像在二维空间中的旋转运算分解成为三步在一维空间内平移运算 ,使插值运算在一维空间中完成 ,从而简化了图像旋转数据处理中的插值运算。最后 ,还提出了一种以硬件方法完成高阶图像插值运算实现图像旋转的新方法 ,并针对 2 5 6灰度级 ,2 5 6× 2 5 6像素的图像 ,设计出一个以 FPGA为核心的实时、高质量的硬件图像旋转系统。     

基于联邦滤波器的新型故障检测结构及算法

提出了一种基于联邦卡尔曼滤波器的故障检测结构,该结构利用各局部滤波器和参考滤波器共有状态之间的残差进行故障检测.并提出了2种故障检测算法:χ2检验法和Elman神经网络检验法.以组合导航系统为例进行了仿真研究,和其它算法相比该算法计算简单、可靠,不但可以快速检测出外部传感器及参考系统故障,且具有很好的容错性能,能快速检测出故障并进行隔离,使融合后系统依然保持较高精度.     

SINS／GPS组合系统的蒙特卡洛仿真

以考虑位置误差相关项的伪距率观测模型，对遥感中使用的SINS/GPS为距、伪距率组合系统进行了蒙特卡洛仿真。结果表明，组合系统的长期位置精度能达到5m以内；GPS数据更新率低于SINS，在GPS测量时间间隔内，组合系统的性能仅由SINS决定，虽然SINS的误差随时间积累，但在GPS测量时间间隔为秒数量级的情况下，即使采用中等精度的惯性的误差随时间积累，但在GPS测量时间间隔为秒数量级的情况下，即使采用中等精度的惯性仪表，其相对位置精度可达到厘米级（这里相对位置精度指组合系统在GPS测量时间间隔内位置误差的变化范围）。     

应用加权中值滤波法检测薄壁梁式挠性器件下摆量

应用加权中值滤波法对薄壁梁式挠性器件下摆量进行高准确度CCD检测。薄壁梁式挠性器件在测量过程中测量图像存在高频抖动现象,因此测量准确度不高,运用加权中值滤波后使用最小二乘法细分技术,可以在实现提高测量准确度的同时,消除高频抖动带来的误差,从而可以有效提高CCD测量薄壁梁式挠性器件下摆量的准确度。实验表明,该方法比传统测量方法准确度提高20倍以上。     

平台摇摆对卡尔曼滤波跟踪精度的影响

通过建立目标相对运动坐标系和目标相对运动观测模型,研究了在平台摇摆影响下,跟踪系统观测到的目标运动状态的变化。在分析捷联垂直基准补偿原理的基础上建立了捷联垂直基准平台摇摆角补偿模型,建立的模型结合捷联垂直基准系统的测量能力对其补偿算法进行了理论推导,使模型适用于实际捷联垂直基准系统。通过建立模型以及仿真研究了平台摇摆作用下卡尔曼滤波跟踪精度的变化,指出了摆造成卡尔曼滤波跟踪精度降低甚至离散的主要原因在于模型误差增大。设计仿真实验验证了结论的正确性,为进一步改进跟踪手段提供了理论参考。     

A cost driven predictive maintenance policy for structural airframe maintenance

Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance stop.With progress in sensor technology and data processing techniques,structural health monitoring (SHM) systems are increasingly being considered in the aviation industry.SHM systems track the aircraft health state continuously,lead ing to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule.This paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter (EKF) with a first order perturbation (FOP) method.By using the information given by this prognostics method,a novel cost driven predictive maintenance (CDPM) policy is proposed,which ensures the aircraft safety while minimizing the maintenance cost.The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is imple mented.Under the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies:scheduled maintenance and threshold based SHM maintenance.The comparison results show CDPM could lead to significant cost savings.     

Real-time object tracking via least squares transformation in spatial and Fourier domains for unmanned aerial vehicles

This paper addresses the problem of real-time object tracking for unmanned aerial vehicles. We consider the task of object tracking as a classification problem. Training a good classifier always needs a huge number of samples, which is always time-consuming and not suitable for realtime applications. In this paper, we transform the large-scale least-squares problem in the spatial domain to a series of small-scale least-squares problems with constraints in the Fourier domain using the correlation filter technique. Then, this problem is efficiently solved by two stages. In the first stage, a fast method based on recursive least squares is used to solve the correlation filter problem without constraints in the Fourier domain. In the second stage, a weight matrix is constructed to prune the solution attained in the first stage to approach the constraints in the spatial domain. Then, the pruned classifier is used for tracking. To evaluate proposed tracker's performance, comprehensive experiments are conducted on challenging aerial sequences in the UAV123 dataset. Experimental results demonstrate that proposed approach achieves a state-ofthe-art tracking performance in aerial sequences and operates at a mean speed of beyond 40 frames/s. For further analysis of proposed tracker's robustness, extensive experiments are also performed on recent benchmarks OTB50, OTB100, and VOT2016.     

基于Kalman滤波的变体飞行器T-S模糊控制

针对变体飞行器的跟踪控制问题,提出了一种基于Kalman滤波的T-S模糊控制方法。考虑飞行器系统状态不可测,引入惯导数据作为辅助信息,利用Kalman滤波算法融合飞控信息与惯导信息实现状态估计。由于变体飞行器在不同变形结构下气动特性变化较大,为便于控制器设计,采用小扰动线性化方法得到飞行器在不同平衡点处的局部线性模型,并通过状态反馈方法设计局部控制器,局部线性模型和局部控制器通过模糊集和模糊规则聚合成一个连续光滑的全局T-S模糊模型和T-S模糊控制器。通过综合Kalman滤波器与T-S模糊控制器得到一个基于Kalman滤波的T-S模糊控制器。仿真结果表明,该控制器在变形过程中能够实现状态估计,保证飞机的跟踪性能。