基于EMD及PNN的航天器振动环境分析

针对航天器非平稳随机振动信号模态频率密集的特点,提出了基于经验模式分解EMD (Empirical Mode Decomposition)的多分量过程神经网络PNN(Process Neural Network)自回归模型.通过EMD对原始时间序列进行分解, 使之成为一组不同尺度的局部正交本征模函数IMF(Intrinsic Mode Functions),利用PNN对每个IMF分别进行时变参数分析并以此确定其时变自功率谱密度,对所有分量的时变自功率谱密度通过叠加进行重构, 以此得到原始信号的时变自功率谱密度.仿真结果和实例分析表明:和传统的时频分析法相比,该方法直接使用信号数据,避免了相关估计计算,减小了计算工作量;无交叉干扰项,提高了信号的时频分布特性,具有较高的时频分辨率;对各工况下航天器的振动信号能有效的进行分析,具有较强的信号特征提取能力.      

基于小波分析的航空发动机旋转失速检测方法

对试车检测到的压气机旋转失速压力数据,进行了小波降噪处理,并对处理后的数据进行多分辨分析,利用dN层小波系数重构相关频带内的压力信号分量,当重构信号某处的幅值超过给定阀值时,认为检测到了失速。研究结果表明,小波分解能有效地区分信号中的突变部分和噪声,达到降噪的目的;对不同采样频率的压力数据进行分析,给出了相应的阀值,对dN层重构信号进行监测,能有效检测到旋转失速的发生。      

改进的极化SAR图像三分量分解方法

针对原始三分量分解方法中,偶次散射和表面散射类地物的体散射分量可能会过估计的问题,提出了一种基于H/α珔参数和一般散射机理模型的改进的三分量分解方法。首先在进行极化分解之前利用H/α珔参数判定目标的主导散射类型。对于主导散射类型明确的像素点,利用一般散射机理模型优先计算主导散射成分的相关扩展系数,然后再从剩余成分中提取非主导散射分量。对于主导散射类型不明确的像素点,采用传统的去取向三分量分解方法进行分解。对实测极化SAR图像进行实验表明,新方法不仅继承了传统三分量分解方法的优点,而且能在分解结果中更加有效地突出雷达目标的主导散射特征。     

Estimation and analysis of GPS receiver differential code biases using KGN in Korean Peninsula

The total electron content (TEC) estimation by the Global Positioning System (GPS) can be seriously affected by the differential code biases (DCB), referred to as inter-frequency biases (IFB), of the satellite and receiver so that an accuracy of GPS–TEC value is dependent on the error of DCBs estimation. In this paper, we proposed the singular value decomposition (SVD) method to estimate the DCB of GPS satellites and receivers using the Korean GPS network (KGN) in South Korea. The receiver DCBs of about 49 GPS reference stations in KGN were determined for the accurate estimation of the regional ionospheric TEC. They obtained from the daily solution have large biases ranging from +5 to +27 ns for geomagnetic quiet days. The receiver DCB of SUWN reference station was compared with the estimates of IGS and JPL global ionosphere map (GIM). The results have shown comparatively good agreement at the level within 0.2 ns. After correction of receiver DCBs and knowing the satellite DCBs, the comparison between the behavior of the estimated TEC and that of GIMs was performed for consecutive three days. We showed that there is a good agreement between KASI model and GIMs.     

铅盐、铜盐及其碳黑复合物对叠氮/硝胺推进剂燃烧性能的影响

研究了LA铅盐、GT铜盐及其碳黑复合物对硝胺/叠氮推进剂燃烧性能的影响。结果表明：GT铜盐可提高叠氮/硝胺推进剂的燃速,质量分数1%的GT铜盐能提高推进剂燃速1.5～2.4 mm/s;LA铅盐、GT铜盐及其碳黑复合物可降低叠氮/硝胺推进剂压强9～19 MPa下的压强指数,推进剂中加入质量分数3%的该复合催化剂,压强9～...     

基于IPTA数据的毫秒脉冲星综合稳定度评估

利用脉冲星极其稳定的自转频率可以形成一种天文时间基准，部分毫秒级脉冲星的稳定度甚至超越了原子钟，但其观测稳定度易受多种噪声源的影响。一般来说，不同的脉冲星的噪声大部分是相互独立的，因此可以通过加权综合和滤波算法构建综合脉冲星时，有效去除计时残差中的噪声。针对此问题，采用10颗毫秒级脉冲星的国际脉冲星计时阵列（international pulsar timing array, IPTA）数据进行了稳定度评估分析，其中7颗脉冲星的观测数据长度在10年以上。综合考虑单颗脉冲星稳定度评估的结果和观测数据的长度后，筛选出了4颗脉冲星用于构建综合脉冲星时。同时对比了经典加权算法、小波分解算法和维纳滤波算法的综合脉冲星时稳定度结果。结果表明：脉冲星的长期稳定度优于短期稳定度，2颗脉冲星在1年处稳定度达10-15量级，8颗在1 000天处也达到了10-15量级，其中PSR J1600-3053在5年处稳定度达到了最佳，为7.023×10-16 。此外，三种算法中，维纳滤波建立的综合脉冲星时稳定度最佳，在5年处达到了1.502×10-15，优于参与构建的其他所有脉冲星的5年稳定度。     

火星探测器气动外形/弹道一体化多目标优化

针对火星探测器概念设计阶段的需求,提出了融合气动外形、弹道和开伞条件的一体化多目标优化设计方法。首先建立了火星探测器进入段三自由度弹道运动方程,基于修正牛顿理论推导了适用于具有较大半锥角球锥外形的气动参数估算模型,采用Sutton-Graves公式计算了驻点热流密度。以开伞高度、总吸热量和容积率为目标函数建立了火星探测器气动外形/弹道一体化多目标优化模型,采用基于分解的多目标进化算法(MOEA/D)进行求解计算并与参考设计进行了对比。数值结果表明:多目标优化方法提供多个三目标均优于参考设计的Pareto最优解,为火星探测器的概念设计提供了一定的参考依据。     

多变量气动设计问题分层协同优化

 通过验证实例分析,气动设计中精细化优化模型对设计结果收敛精度的提高有很大帮助,但同时也带来优化算法搜索困难的问题,并且由于不同类型设计变量之间的相互耦合干扰使优化难以收敛到全局最优解。于是提出基于响应均值灵敏度的概念对大规模的设计变量进行重要性分组的策略,依据设计变量分组情况应用系统分解思想对多变量设计问题进行分层协同优化来降低系统的复杂度,这既保证了精细化设计的要求,又缓解了优化算法对大规模问题搜索困难的问题。与传统气动优化方法相比,基于系统分解的分层协同优化算例有较大寻优效率和性能提升,证明了该方法的可行性。     

Novel passive localization algorithm based on double side matrix-restricted total least squares

In order to solve the bearings-only passive localization problem in the presence of erroneous observer position, a novel algorithm based on double side matrix-restricted total least squares (DSMRTLS) is proposed. First, the aforementioned passive localization problem is transferred to the DSMRTLS problem by deriving a multiplicative structure for both the observation matrix and the observation vector. Second, the corresponding optimization problem of the DSMRTLS problem without constraint is derived, which can be approximated as the generalized Rayleigh quotient minimization problem. Then, the localization solution which is globally optimal and asymptotically unbiased can be got by generalized eigenvalue decomposition. Simulation results verify the rationality of the approximation and the good performance of the proposed algorithm compared with several typical algorithms.     

Monitoring of rice cropping intensity in the upper Mekong Delta,Vietnam using time-series MODIS data

Information on rice growing areas is important for policymakers to devise agricultural plans. This research explores the monitoring of rice cropping intensity in the upper Mekong Delta, Vietnam (from 2001 to 2007) using time-series MODIS NDVI 250-m data. Data processing includes three steps: (1) noise is filtered from the time-series NDVI data using empirical mode decomposition (EMD); (2) endmembers are extracted from the filtered time-series data and trained in a linear mixture model (LMM) for classification of rice cropping systems; and (3) classification results are verified by comparing them with the ground-truth and statistical data. The results indicate that EMD is a good filter for noise removal from the time-series data. The classification results confirm the validity of LMM, giving an overall accuracy of 90.1% and a Kappa coefficient of 0.7. The lowest producer and user accuracies were associated with single crop rain-fed rice class due to the mixed pixel problems. A strong yearly correlation at the district level was revealed in the MODIS-derived areas (R² ? 0.9). Investigation of interannual changes in rice cropping intensity from 2001 to 2007 showed a remarkable conversion from double to triple crop irrigated rice from 2001 to 2003, especially in the Thoai Son and Phu Tan districts. A big conversion from triple crop rice back to double crop rice cultivation was also observed in Phu Tan from 2005 to 2006. These changes were verified by visual interpretation of Landsat images and examination of NDVI profiles.