Unbalanced AltBOC: a Compass B1 candidate with generalized MPOCET technique

With the proposed new GNSS signals, enhanced navigation performance is expected in both civil and military applications. However, these new signals introduce the difficulty of combining multiple signal components into a constant-envelope signal. For the Compass B1 band, the problem is to multiplex a QPSK(2) signal and a new multiplexed binary offset carrier (MBOC) signal with a center frequency difference of 14.322 MHz. One approach for multiplexing spreading codes is the phase-optimized constant-envelope transmission (POCET) method proposed for the GPS L1 band. However, only binary spreading codes are considered in POCET. We first generalize the POCET method as a multilevel POCET (MPOCET) algorithm for multilevel coded signals. A new implementation of the alternative binary offset carrier (AltBOC) generator is derived from MPOCET. Secondly, the multiplexing problem for Compass is modeled by MPOCET. Multilevel subcarriers of AltBOC are adopted in the model. As a result, an 8-PSK unbalanced AltBOC (UAltBOC) modulation, which has a QPSK(2) signal at the lower sideband and a TMBOC signal at the upper sideband, is obtained. Simulations for signal model validation and power spectrum analysis are conducted. Numerical results indicate that UAltBOC successfully combines the QPSK and TMBOC signals with only 0.16-dB additional combining loss compared to AltBOC. The proposed MPOCET technique is demonstrated as a unified multiplexing method for navigation signals.     

圆型限制性三体问题下Halo-绕月轨道的星间测距定轨

在传统星座自主定轨中,SST(satellite to satellite tracking)可以同时提供轨道的大小、形状和星座相对方位信息,但不能确定星座的绝对定向。针对这一亏秩问题,联合圆型限制性三体模型CRTBP(circle restricted three bodyproblem)下的一种平动点周期轨道-Halo轨道飞行器,与二体问题轨道卫星组成扩展星座。利用两种力模型的特性差异,可以去除星座系统上的相关性,避免星座的整体旋转,从而确定星座的全部轨道状态参量。分析Halo轨道的力模型及性态特点,从系数矩阵的相关性角度讨论引进Halo轨道对定轨法矩阵正定性的改善作用,利用地月系L1平动点附近的Halo轨道与月球低轨卫星(LMO)的星间链路,在理想CRTBP框架下进行自主定轨仿真。初步验证了LMO-Halo星座定轨可行性,为开展附加平动点轨道的星座SST定轨提供了参考依据。     

Virtual geographic environment-based integrated rockfall risk simulation method for canyon bridges

Bridges located in mountainous areas are vulnerable to rockfall accidents, posing a threat to bridge engineering construction and operation safety in these regions. Under the coupling effect of complex environments and engineering disturbances, integrated rockfall risk simulation has become increasingly important for canyon bridge structural protection in long-term construction and operation phases. One of the main scientific challenges in rockfall risk simulation is studying the interaction between rockfalls and the topography and engineering environments during consecutive contacts. To systematically simulate the integrated bridge rockfall risk, an integrated construction of multivariable elements coupled with rockfall risk environments and scenarios is required. In this article, we proposed a VGE-based integrated rockfall scenario simulation method that uses the “associated representation—integrated modelling—interactional simulation” core strategy. Our method constructs a virtual rockfall risk environment by fusing multisource data to represent rockfall factors that induce rockfall disasters, hazard-forming environments, and elements at risk. We design rockfall scenarios under different bridge engineering construction conditions and extreme environmental conditions to analyze the interactional rockfall risks. The results demonstrate that our method enables a systematic analysis of the potential integrated rockfall risk, providing realistic reference value for the timely and effective disposal of emergencies, and reducing the harm and losses caused by such emergencies.     

EVKG: An interlinked and interoperable electric vehicle knowledge graph for smart transportation system

Over the past decade, the electric vehicle (EV) industry has experienced unprecedented growth and diversification, resulting in a complex ecosystem. To effectively manage this multifaceted field, we present an EV-centric knowledge graph (EVKG) as a comprehensive, cross-domain, extensible, and open geospatial knowledge management system. The EVKG encapsulates essential EV-related knowledge, including EV adoption, EV supply equipment, and electricity transmission network, to support decision-making related to EV technology development, infrastructure planning, and policy-making by providing timely and accurate information and analysis. To enrich and contextualize the EVKG, we integrate the developed EV-relevant ontology modules from existing well-known knowledge graphs and ontologies. This integration enables interoperability with other knowledge graphs in the Linked Data Open Cloud, enhancing the EVKG's value as a knowledge hub for EV decision-making. Using six competency questions, we demonstrate how the EVKG can be used to answer various types of EV-related questions, providing critical insights into the EV ecosystem. Our EVKG provides an efficient and effective approach for managing the complex and diverse EV industry. By consolidating critical EV-related knowledge into a single, easily accessible resource, the EVKG supports decision-makers in making informed choices about EV technology development, infrastructure planning, and policy-making. As a flexible and extensible platform, the EVKG is capable of accommodating a wide range of data sources, enabling it to evolve alongside the rapidly changing EV landscape.     

Scale-oriented temporal analysis of movement data: A series-based approach

The ubiquity of movement data has led to new research interest in aspects of temporal scale. Few of the approaches analyzing movement data have been developed specifically for scale-oriented temporal analysis. To overcome this limitation, this article proposes a series-based approach to perform scale-oriented temporal analysis of movement data. Key to the proposed approach is the construction of four types of series (one type of identical-scale series and three types of cross-scale series) based on the continuous triangular model (CTM). Two distinct research goals are derived from this: to investigate the changes in motion attributes of moving individuals across different temporal scales, and to detect the time intervals during which active events might have occurred. The results based on real football movement data show that finer changes in motion attributes can be found and more accurate time intervals can be detected through the proposed approach.     

顾及用户体验的三维城市模型自适应组织方法

传统基于“图层付象”的组织方法,没有考虑三维城市模型的不同内容以及不同细节层次的粒度差异,导致在网络环境下的传输效率低,难以满足多用户并发访问的流畅可视化。深入分析了大范围漫游与小范围聚焦的用户体验特点,通过元数据统筹管理和对象离散化,即时响应用户请求,减少无效数据传输,保证了多用户并发环境下的高效调度和浏览。针对模型LoI)和分解的对象,设计了结构统一的对象ID,隐式存储关联关系并支持分布式模型存储管理。以分布式数据库MongoDB为平台进行实验,验证了本文方法的可行性和有效性。     

基于SMVF的高频雷达自适应多目标检测

针对高频雷达强海杂波和干扰环境下的多目标检测问题,结合S-method时频分布和Vitcrbi算法提出了一种多分量线性调频信号瞬时频率估计方法—SMVF法(S-method viterbi fitting),然后根据所提取的瞬时频率的直线拟合性能,提出了一种自适应多目标检测算法。实测数据的处理结果,表明了该算法在低信噪比时,与WDM法(wigncr distribution maxima) , WDV法( wigncr distribution vitcrbi)相比,估计精度提高约2000,验证了该算法的可行性和有效性。     

利用NOAA-AVHRR数据分析1982-2001年间中国植被的动态变化

The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period, China’s vegetation cover h...     

半参数模型统计诊断与粗差检验

This paper systematically studies the statistical diagnosis and hypothesis testing for the semiparametric linear regression model according to the theories and methods of the statistical diagnosis and hypothesis testing for parametric regression model.Several diagnostic measures and the methods for gross error testing are derived.Especially,the global and local influence analysis of the gross error on the parameter X and the nonparameter s are discussed in detail;at the same time,the paper proves that the d...     

Climate applications of a global, 2-hourly atmospheric precipitable water dataset derived from IGS tropospheric products

A global, 2-hourly atmospheric precipitable water (PW) dataset is produced from ground-based GPS measurements of zenith tropospheric delay (ZTD) using the International Global Navigation Satellite Systems (GNSS) Service (IGS) tropospheric products (~80–370 stations, 1997–2006) and US SuomiNet product (169 stations, 2003–2006). The climate applications of the GPS PW dataset are highlighted in this study. Firstly, the GPS PW dataset is used as a reference to validate radiosonde and atmospheric reanalysis data. Three types of systematic errors in global radiosonde PW data are quantified based on comparisons with the GPS PW data, including measurement biases for each of the fourteen radiosonde types along with their characteristics, long-term temporal inhomogeneity and diurnal sampling errors of once and twice daily radiosonde data. The comparisons between the GPS PW data and three reanalysis products, namely the NCEP-NCAR (NNR), ECMWF 40-year (ERA-40) and Japanese reanalyses (JRA), show that the elevation difference between the reanalysis grid box and the GPS station is the primary cause of the PW difference. Secondly, the PW diurnal variations are documented using the 2-hourly GPS PW dataset. The PW diurnal cycle has an annual-mean, peak-to-peak amplitude of 0.66, 0.53 and 1.11 mm for the globe, Northern Hemisphere, and Southern Hemisphere, respectively, with the time of the peak ranging from noon to late evening depending on the season and region. Preliminary analyses suggest that the PW diurnal cycle in Europe is poorly represented in the NNR and JRA products. Several recommendations are made for future improvements of IGS products for climate applications.