基于Hankel矩阵填充的稀疏孔径ISAR成像

在稀疏孔径(SA)逆合成孔径雷达(ISAR)成像中,传统压缩感知(CS)方法使用稀疏信号处理来处理数据缺失下的成像问题。这类方法存在模型不匹配这一固有问题,在一定程度上会限制成像质量。提出了一种利用Hankel矩阵填充(HMC)的基于结构化稀疏ISAR成像方法。该方法是一种典型的无网格方法,可以有效地提高稀疏孔径ISAR成像性能。首先,建立ISAR稀疏孔径成像信号模型,根据每个距离单元的回波构造Hankel矩阵;其次,通过证明所构造Hankel矩阵的低秩性质,作为方位稀疏成像的先验信息约束;最后,通过逐步迭代求解基于增广拉格朗日乘子(ALM)的矩阵填充(MC)来实现重构方位维成像。提出的基于低秩约束的方法,可以避免过完备基的假设,有效地克服了CS方法的离网格效应。基于实测数据的实验分析,进一步验证了所提算法的有效性。     

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.     

Multi-parameter optimization of machining impeller surface based on the on-machine measuring technique

Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel. Existing experimental methods require lots of machining experiments and off-line tests, which may lead to high machining cost and low efficiency. This paper proposes a novel method of machining parameters optimization for an impeller based on the on-machine measuring technique. The absolute average error and standard deviation of the measured points are used to define the grey relational grade for reconstructing the objective function, and the complex problem of multi-objective optimization is simplified into a problem of single-objective optimization. Then, by comparing the values of the defined grey relational grade in a designed orthogonal experiment, the optimal combination of the machining parameters is obtained. The experiment-solving process of the objective function corresponds to the minimization of the used errors, which is advantageous to reducing the machining error. The proposed method is efficient and low-cost, since it does not require re-clamping the workpiece for off-line tests. Its effectiveness is verified by an on-machine inspection experiment of the impeller blade.     

基于近邻保持嵌入的卫星姿态控制系统微小故障检测

摘要： 以卫星姿态控制系统(ACS)为研究对象，以微小故障检测为研究目标，提出一种改进的近邻保持嵌入算法(EWMA DNPE).针对近邻保持嵌入(NPE)算法中邻域参数无法自动设定的缺陷，通过引入动态邻域，使得动态近邻保持嵌入算法（DNPE）可根据流形的样本密度动态地选取近邻点计算权值重构矩阵.将指数加权移动平均(EWMA)引入DNPE，通过EWMA对历史故障数据的累加作用，建立SPE统计量实现微小故障的检测，并仿真验证了EWMA DNPE算法对卫星ACS微小故障检测的有效性和可行性.     

A star identification algorithm based on radial and dynamic cyclic features of star pattern

A full-sky star identification algorithm based on radial and dynamic cyclic patterns is presented with the aim of solving the “lost-in-space” problem. The dynamic cyclic pattern match is applied with a maximum cumulate comparison method to identify sensor-catalog pairings in initial match, which substantially eliminates the effects of the star position noise, magnitude noise, and false stars. After initial match pairings of stars are obtained, a chain part extension technique is employed to quickly search for the longest match chain as the final result. Experimental results indicate that the proposed algorithm is highly robust to star position noise, magnitude noise and false stars. In a series of simulations, the identification rate of the algorithm is 97.50% with 2.0 pixels star position noise, 96.90% with 0.4 Mv star magnitude noise and 95.30% with four false stars respectively. Moreover, the algorithm achieves an identification rate of 58.08% when only six stars are in the field of view.     

基于神经网络和遗传算法的公差优化设计

针对产品制造中公差与成本之间高度非线性关系的特点,提出了一种综合神经网络与遗传算法进行公差优化的方法,该方法利用遗传算法在大范围解空间内采用概率搜索策略得到全局最优解且有较强鲁棒性的特点,以及神经网络解决高度非线性问题的优越性,首先利用神经网络对公差成本进行仿真,得到具有黑箱特点的公差成本函数关系;然后在公差分配中采用遗传算法,以总成本最小为目标函数,以满足装配公差要求和符合标准公差等级为约束条件进行优化;同时基于VC和Matlab开发了公差优化系统,以飞机舱门锁钩机构为对象进行了验证,并针对不同的公差成本及分配方法进行了对比.结果表明:采用神经网络与遗传算法综合分配的结果与传统方法相比具有较大的优越性.     

五自由度气浮仿真试验台的动力学建模

五自由度气浮仿真试验台是在地面模拟微小卫星空间运动的一种重要仿真设备。通过分 析试验台的系统结构,定义世界系、轨道系及本体系三个坐标系,建立了其所模拟微小卫星 空间运动的一般情况下轨道动力学和姿态动力学模型,最后根据试验台目前执行机构为冷气 推进装置的实际工作情况导出了试验台状态方程,为下一步试验台模拟微小卫星的自治飞行 提供了理论基础。
     

复合噪声调频干扰的极化滤波方法

基于瞬态极化理论研究了复合噪声调频干扰的极化滤波方法。在对多个噪声调频干扰源合成信号的极化起伏特性进行分析的基础上,提出了复合噪声调频干扰的瞬态极化估计方法和基于MLP的极化滤波抑制方法。最后,利用计算机仿真实验验证了文中所提方法的有效性和可行性。     

多路导航信号恒包络处理技术

现代化的导航系统需要在一个频段发射多路导航信号以提高频谱利用率。直接组合的复合信号不是恒包络,在通过饱和状态功率放大器时会产生AM/PM失真,从而影响整个导航系统的定位精度。为了解决这个问题,需要增加互调分量,把信号处理成恒包络复合信号。文章在分析GPS和GALILEO系统导航信号恒包络处理方法的基础上,给出了我国导航卫星系统恒包络处理方法的建议。