An improved approach to model ionospheric delays for single-frequency Precise Point Positioning

PPP with low-cost, single-frequency receivers has been receiving increasing interest in recent years because of its large amount of possible users. One crucial issue in single-frequency PPP is the mitigation of ionospheric delays which cannot be removed by combining observations on different frequencies. For this purpose, several approaches have been developed, such as, the approach using ionospheric model corrections with proper weight, the GRAPHIC (Group and Phase Ionosphere Calibration) approach, and the method to model ionospheric delays over a station with a low polynomial or stochastic process. From our investigation on the stochastic characteristics of the ionospheric delay over a station, it cannot be precisely represented by either a deterministic model in the form of a low-order polynomial or a stochastic process for each satellite, because of its strong irregular spatial and temporal variations. Therefore, a novel approach is developed accordingly in which the deterministic representation is further refined by a stochastic process for each satellite with an empirical model for its power density. Furthermore, ionospheric delay corrections from a constructed model using GNSS data are also included as pseudo-observations for a better solution. A large data set collected from about 200 IGS stations over one month in 2010 is processed with the new approach and several commonly adopted approaches for validation. The results show its significant improvements in terms of positioning accuracy and convergence time with a negligible extra processing time, which is also demonstrated by data collected with a low-cost, handheld, single-frequency receiver.     

Individual Differences in Representational Precision Predict Spatial Working Memory Span

Perhaps the signature feature of working memory is that it is limited. In the same subjects, we used two different retrieval tasks to independently measure two different limits of spatial memory. Precision was measured by asking participants to localize a missing target item among a field of other targets and distracters. Capacity was measured with a similar task where participants identified, rather than localized, a set of remembered targets from within a larger set of identical items. Across participants, the precision of localization was positively correlated with the number of successfully retrieved items. These data suggest that an individual's representational capacity may ultimately be constrained by their ability to form precise representations of space.     

空-空导弹打靶专家仿真系统

 本文介绍一个为检验空空导弹性能而研制的空空导弹打靶专家仿真系统。该系统采用专家经验选择导弹初始攻击条件和目标的逃逸策略,因而可以大大减少检验导弹性能所必需的仿真次数。该系统采用通用型数学模型,并把与具体导弹及目标有关的知识与一般性知识分开,因而具有较强的通用性。     

基于故障树模型的航天器故障诊断研究

本文建立了基于故障树模型的航天器故障诊断框架，提出了航天器故障诊断的知识组织和表示方法及相应的推理控制策略，并通过对某卫星能源系统故障实验台的故障诊断验证了方法的正确性。     

微型高速图像压缩系统

提出了一种基于多分辨率分解的静止图像压缩算法,在8倍压缩的条件下能够保证较高的图像质量。该算法与现有的静止图像压缩算法相比,在较大程度上降低了对数据传输误码率的敏感性,并且能够在现有器件工艺水平下采用硬件电路来实现。详细介绍了利用FPGA实现的该算法的演示系统。     

稀疏RAM式联想存储器

在RAM式联想存储器(RAM-AM)基础上,借助Kanerva的稀疏分布存储思想,提出了稀疏RAM联想存储器模型(SRAM-AM),分析了该模型的信噪比特性,通过适当地选取其中的一些关键参数,可使SRAM-AM的性能大大高于RAM-AM.最后在汉字识别应用中验证了模型的可行性,同时大大降低了硬件实现的开销.     

N元自适应模式识别系统开发工具

N元模式识别方法是一种易于硬件并行实现的自适应模式识别方法。单层自适应模式识别系统(WISARD)、加权WISARD、双层自适应模式识别系统模型都是以这一方法为基础的。本文论述的N元自适应模式识别系统开发工具——NIRSS就是为这些模型体系结构的仿真及应用研究而开发的。它可以仿真现有的4种模型,共有7种工作方式,23个功能模型,97条人机交互命令。有关上述模式识别系统结构的研究以及多印刷体汉字、手写体汉字的识别、自适应图像处理的应用研究都是在该软件包上进行的。实际应用表明,这是一种使用方便、功能丰富的有效开发工具。     

故障诊断神经网络系统的专家知识表达方法

通过介绍其它故障诊断技术存在的问题，研究了故障诊断神经网络系统，提出了两种故障诊断神经网络的专家知识表达方法，并将其应用于飞行器液压动力系统的故障诊断，仿真结果表明：提出的方法是正确可行的，并且专家知识表达方法对诊断结果有很大影响，该方法可推广应用于其它动力系统的故障诊断     

SketchMapia: Qualitative Representations for the Alignment of Sketch and Metric Maps

More and more private citizens collect and publish environmental data via web-based geographic information systems. These systems face two challenges: The user interface must be intuitive and the processing of geographic information must account for cognitive impact. We propose to use sketch maps as the medium for interaction, because they reflect a person's spatial knowledge. Information from sketch maps is distorted, schematized, incomplete, and generalized and metric maps are not. This article employs qualitative representations for the alignment of sketch and metric maps. We suggest a set of cognitively oriented aspects in sketch maps stably computed by people and evaluate qualitative representations to formalize these aspects. This allows us to align and integrate geographic information from sketch maps.     

Wavelet modelling in support of IRI

The slant total electron content (STEC) of the ionosphere is defined as the integral of the electron density along the ray-path of the signal between the transmitter and the receiver. So-called geometry free GPS measurements provide information on the electron density, which is basically a four-dimensional function depending on spatial position and time. Since ground-based measurements are not very sensitive to the vertical structure within the atmosphere, the ionosphere is often represented by a spherical layer, where all electrons are concentrated. Then the STEC is transformed into the vertical total electron content (VTEC), which is a three-dimensional function depending on longitude, latitude and time.In our approach, we decompose an ionospheric function, i.e. the electron density or the VTEC, into a reference part computed from a given model like the International Reference Ionosphere (IRI) and an unknown correction term expanded in a multi-dimensional series in terms of localizing base functions. The corresponding series coefficients are calculable from GPS measurements applying parameter estimation procedures. Since the GPS receivers are located rather unbalanced, finer structures are modelable just in regions with a sufficient number of observation sites. Due to the localizing feature of B-spline functions we apply a tensor product spline expansion to model the correction term regionally. Furthermore, the multi-resolution representation derived from wavelet analysis allows monitoring the ionosphere at different resolutions levels. We demonstrate the advantages of this procedure by representing a simulated VTEC data set over South America.