挠性航天器伸展动力学分析

本文导出了带挠性伸展附件航天器姿态动力学方程，研究了附件伸展和振动对姿态动力学的影响。对于附件按指数规律伸展情况，以及附件长度的次方随时间线性变化情况，给出了姿态角速率的渐近公式。     

A new technique for direction of arrival estimation for ionospheric multipath channels

A novel array signal processing technique is proposed to estimate HF channel parameters including number of paths, their respective direction of arrivals (DOA), delays, Doppler shifts and amplitudes. The proposed technique utilizes the Cross Ambiguity Function (CAF), hence, called as the CAF-DF technique. The CAF-DF technique iteratively processes the array output data and provides reliable estimates for DOA, delay, Doppler shift and amplitude corresponding to each impinging HF propagated wave onto an antenna array. Obtained results for both real and simulated data at different signal to noise ratio (SNR) values indicate the superior performance of the proposed technique over the well known MUltiple SIgnal Classification (MUSIC) technique.     

非线性自适应控制在无尾飞控系统中的应用

无尾飞机是新型飞机的研究方向,由于其没有尾翼甚至机身,导致横侧向模态自身以及横侧向模态与纵向模态之间存有强耦合非线性特性。将非线性自适应控制应用到无尾飞控系统中,结合MATLAB的仿真工具,对无尾飞机模型进行实时仿真,得到了相应的仿真曲线。通过对仿真曲线的分析,验证了该控制方法在无尾飞控系统应用中的可行性。     

非线性热传导逆问题的表面热流辨识方法

当材料的热物性参数随温度变化时,其内部的热传导方程是一非线性偏微分方程,对应的热传导逆问题称为非线性热传导逆问题。本文建立了非线性热传导逆问题的两种表面热流辨识方法:顺序函数法和共轭梯度法,介绍了这两种辨识方法的基本思想和具体算法推导,并针对典型算例进行了仿真辨识,结果表明:两种辨识方法虽然在算法构造、计算效率方面存在一定的差异,但都能给出较好的辨识结果,并且算法受测量噪声的影响较小,具有较好的鲁棒性。     

基于原模图扩展的QC-LDPC构造方法

基于原模图构造的低密度奇偶校验码(LDPC)性能很大程度上取决于扩展算法。为此,提出了一种构造准循环低密度奇偶校验码(QC-LDPC)的新方法。所述算法经过两步扩展得到QC-LDPC:第一步是原模图去重边,在边置换条件的约束下,使扩展所得矩阵局部围长最大化;第二步进行准循环扩展,通过计算机搜索得到规定长度内的所有闭环路径,比较环长和近似环路外信息度得到置换矩阵的最优偏移量,目的是剔除连通性差的短环对码性能的负面影响。对于不存在重边的原模图,则直接进行准循环扩展。仿真结果表明,利用该方法构造的QC-LDPC在译码门限和误码平层两方面都具有优异的性能。     

基于FBM分形向量特征的图象匹配

由于自然景物图象的灰度与边缘特征不稳定，基于灰度与边缘的匹配算法对于这一类图象难以生效。本文通过分析ＦｒａｃｔａｌＢｒｏｗｎｉａｎＭｏｔｉｏｎ（ＦＢＭ）的Ｗｅｉｅｒｓｔｒａｓｓ－Ｍａｎｄｅｌｂｒｏｔ随机分形逼近函数的频谱，给出了分形向量特征的定义和快速判别图象的ＦＢＭ区域的方法。在ＦＢＭ区域内采用该特征进行匹配能克服复杂自然景物图象中灰度与边缘特征的不稳定性。实验表明采用ＦＢＭ分形向量特征的匹配方法能够获得比较传统匹配方法，例如平均绝对差算法以及特征匹配法更高的匹配定位精度和匹配概率     

A memetic algorithm for path planning of curvature-constrained UAVs performing surveillance of multiple ground targets

The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles （UAVs） performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs＇ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood （DTSPN）. Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants （multi-UAV scenario and multiple groups of targets scenario）. The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.     

基于微波辐射测量的电波折射修正技术

针对电波折射修正精度直接影响无线电系统的探测和定位精度这一问题,提出了利用微波辐射计反演大气折射率剖面进行电波折射修正的解决方法,并引入RBF（Radial Basis Function,径向基）神经网络算法反演大气折射率.在青岛市气象局架设MP-3000A型多通道微波辐射计,开展了长达1个月的与探空数据的联合观测比对实验,对输出的大气折射率剖面进行了详细的分析.实验结果表明：RBF神经网络算法与MP-3000A自带的神经网络算法相比,反演大气折射率剖面的精度提高了30％以上,同时,电波折射修正的精度也得以提高.因此,利用微波辐射计反演大气折射率剖面进行电波折射修正方法可行.     

共因失效条件下多状态系统选择性维修优化

共因失效（CCF）广泛存在于多状态系统（MSS）中,研究共因失效条件下多状态系统的维修优化问题,对于提高系统任务成功概率、降低故障损失具有重要意义。考虑多状态系统、任务剖面和随机共因失效的模糊特性,采用模糊马尔可夫模型（FMM）和模糊通用生成函数（FUGF）法,建立了模糊随机共因失效条件下模糊多状态系统（FMSS）任务成功概率评估解析模型（AM）,采用Monte Carlo仿真（MCS）方法对模型进行了验证;考虑维修费用约束,建立了模糊随机共因失效条件下模糊多状态系统选择性维修优化模型,为生成最优维修方案提供支持,结合实际案例,分析了随机共因失效对选择性维修优化和系统各状态的模糊概率的影响,验证了模型的有效性。研究结果表明,模糊随机共因失效和各模糊参数的α水平截集可能会影响选择性维修优化的结果,且忽略模糊随机共因失效会高估系统任务成功概率。     

An intelligent approach for flight risk prediction under icing conditions

Flight risk prediction is significant in improving the flight crew’s situational awareness because it allows them to adopt appropriate operation strategies to prevent risk expansion caused by abnormal conditions, especially aircraft icing conditions. The flight risk space representing the nonlinear mapping relations between risk degree and the three-dimensional commanded vector(commanded airspeed, commanded bank angle, and commanded vertical velocity) is developed to provide the crew with practi...