一种改进的变步长BLMS算法

在BLMS(Block Least Mean Square) 算法的基础上提出了一种变步长算法,它除具有BLMS算法的特点,还提高收敛速度,降低了权失调噪声,具有较好抑噪能力。适用于实时噪声抵消,计算机仿真效果较好。     

电力谐波对卫星天线驱动电机的影响

大型数据信息处理中心需配UPS(Uninterruptible Power System)系统供电,但这样的系统设计中UPS在输入端产生的谐波电流可能会影响配电系统的其他设备。以北京气象卫星地面站供电系统为实例,分析了在应急备用电源供电情况下,当卫星接收天线跟踪卫星时,天线的驱动电机出现明显的抖动现象系UPS工作时产生的谐波电流所致,阐述了UPS电源产生的谐波电流产生的原理以及对配电系统电能质量的影响,给出采用设计有源滤波器消除电力谐波影响以解决天线驱动电机抖动问题的实践方法,总结新技术整流电源产生谐波的扩展趋势,并建议重视大型数据中心配电系统在新形势下电能质量及电磁问题的研究。     

同化MODIS温度产品估算地表水热通量

基于集合卡尔曼滤波和通用陆面模型(CLM 1.0)发展了一个地表温度的同化系统。这个系统同化了MODIS温度产品, 并将MODIS的叶面积指数引入CLM模型中, 主要用于改进地表水热通量的估算精度。将CLM输出的地表温度与MODIS地表温度建立关系, 并作为同化系统的观测算子。将MODIS地表温度与实测地表温度进行了比较, 将其均方差(Root Mean Square Error, RMSE)作为观测误差。选取3个美国通量网站点(Blackhill、Bondville、Brookings)作为实验数据, 结果表明: 同化结果中地表温度、显热通量的估算精度均有提高。其中Blackhill站的估算精度改进最大, 均方差由81.5W·m-2减小到58.4W·m-2, Bondville站均方差由47.0W·m-2减小到31.8W·m-2, Brookings站均方差由46.5W·m-2减小到45.1W·m-2。潜热通量估算精度在Bondville站均方差由88.6W·m-2减小到57.7W·m-2, Blackhill站均方差由53.4W·m-2减小到47.2W·m-2。总之, 结合陆面过程模型同化MODIS温度产品估算地表水热通量是可行的。     

Carrier phase-based integrity monitoring for high-accuracy positioning

Pseudorange-based integrity monitoring, for example receiver autonomous integrity monitoring (RAIM), has been investigated for many years and is used in various applications such as non-precision approach phase of flight. However, for high-accuracy applications, carrier phase-based RAIM (CRAIM), an extension of pseudorange-based RAIM (PRAIM) must be used. Existing CRAIM algorithms are a direct extension of PRAIM in which the carrier phase ambiguities are estimated together with the estimation of the position solution. The main issues with the existing algorithms are reliability and robustness, which are dominated by the correctness of the ambiguity resolution, ambiguity validation and error sources such as multipath, cycle slips and noise correlation. This paper proposes a new carrier phase-based integrity monitoring algorithm for high-accuracy positioning, using a Kalman filter. The ambiguities are estimated together with other states in the Kalman filter. The double differenced pseudorange, widelane and carrier phase observations are used as measurements in the Kalman filter. This configuration makes the positioning solution both robust and reliable. The integrity monitoring is based on a number of test statistics and error propagation for the determination of the protection levels. The measurement noise and covariance matrices in the Kalman filter are used to account for the correlation due to differencing of measurements and in the construction of the test statistics. The coefficient used to project the test statistic to the position domain is derived and the synthesis of correlated noise errors is used to determine the protection level. Results from four cases based on limited real data injected with simulated cycle slips show that residual cycle slips have a negative impact on positioning accuracy and that the integrity monitoring algorithm proposed can be effective in detecting and isolating such occurrences if their effects violate the integrity requirements. The CRAIM algorithm proposed is suitable for use within Kalman filter-based integrated navigation systems.

Modeling spatial autocorrelation in spatial interaction data: empirical evidence from 2002 Germany journey-to-work flows

Since before the inception of work by Okabe, the intermingling of spatial autocorrelation (i.e., local distance and configuration) and distance decay (i.e., global distance) effects has been suspected in spatial interaction data. This convolution was first treated conceptually because technology and methodology did not exist at the time to easily or fully address spatial autocorrelation effects within spatial interaction model specifications. Today, however, sufficient computer power coupled with eigenfunction-based spatial filtering offers a means for accommodating spatial autocorrelation effects within a spatial interaction model for modest-sized problems. In keeping with Okabe’s more recent efforts to dissemination spatial analysis tools, this paper summarizes how to implement the methodology utilized to analyze a particular empirical flows dataset.

基于小波滤波的神经网络变形预测

运用小波滤波的的优越性,消除数据噪声,使数据更加的接近真实的数据和更具规律性,有利于我们对数据发展趋势的预测。对消噪后的数据,利用BP神经网络强大的学习能力建立预测网络。在建立网络时,输入样本为监测k时段序列k和第k-1时段变形量与再k-2时段变形量之差组成的二维向量,目标样本为小波滤波后的变形量。并与GM（1,1）。模型和回归模型进行了对比。     

基于最小均方误差算法消除GPS接收机噪声

从解决GPS接收机受干扰的实际需求出发,阐述了基于LMS算法的自适应滤波器基本原理和不同的噪声产生方式,并对GPS接收机仿真信号与噪声进行叠加。最后用基于LMS算法的自适应滤波器对仿真信号进行消噪处理,得到良好的消噪效果,证明了基于LMS算法的自适应滤波器能够应用于GPS接收机滤波系统。     

Short-term (≤2 yrs) estuarine mudflat and saltmarsh sedimentation: High-resolution data from ultrasonic altimetery, rod surface-elevation table, and filter traps

Rates of short-term (up to 2 years) bed elevation change and sedimentation from mudflats to salt marshes were measured in a rapidly infilling macrotidal estuary using an original combination of three high-resolution techniques: an ultrasonic altimeter, the Rod Surface-Elevation Table (RSET) method, and filter traps. The Authie estuary is located on a straight, sand-rich coast and is undergoing rapid infill under the influence of flood-dominant tides reinforced by wave action. The estuarine sediment suite consists of both mud and sand derived from the sea, of sand derived from storm wave erosion of dunes lining the north bank of the estuary, and, to a much smaller extent, of mud from the river catchment. Bed elevation change and sedimentation rates show an expected increase with the duration of tidal flooding (hydroperiod) in both space and time. The estuarine bed sediment suite changes from sandy at the mouth to muddy within the low-energy inner estuary, where mudflats are rapidly accreting, paving the way for the formation of increasingly denser and mature salt marshes from the high-sedimentation pioneer zone to the upper marsh where annual sedimentation is very low. Recorded variability in rates of bed elevation change and sedimentation reflect the influence of estuarine macro-scale and local sediment transport and depositional processes in a macrotidal context dominated by high inputs of allochthonous sediments.     

一种低信噪比下PN码的快速捕获技术

直扩系统中,为了硬件实现的简便,PN码的捕获一般都采用串行搜索的方法.但当PN码很长时,由于搜索相位点很多,串行搜索法将使捕获时间过长.并且当信噪比较低时,会有较高的虚警概率.这些都会使系统的捕获性能降低.提出一种基于匹配滤波器的快速捕获算法,改善了在极低信噪比下的性能.降低了平均捕获时间.     

广义超弹性杆方程的初边值问题

主要研究广义超弹性杆方程的初边值问题,讨论方程在区间[0,1],及边界条件u(0,t)=ux(1,t)=uxx(0,t)=0,-u(1,t)uxx(1,t)=ψ(u(1,t))下,整体解的存在性,H1-整体指数稳定性估计及H2-整体渐进稳定性估计.