基于城市CORS的快速单点定位增强服务与应用

智慧城市建设中CORS位置服务的海量、隐私及高可靠性成为重要发展趋势。本文介绍了基于PPP-RTK技术体系的城市CORS增强定位服务,推导了城市CORS增强精密单点定位的公式,给出了城市CORS增强定位参数的可估形式及其在用户端的适用方法。结合广州CORS实时数据,验证了PPP-RTK服务的有效性。试验表明PPP-RTK用户端平面首历元即可收敛到厘米级,高程7个历元左右可收敛到厘米级,并且PPP-RTK增强定位参数SSR2OSR与短基线RTK性能大体相当,可支撑海量用户的监测需求。车载试验全程保持优于0.5 m车道级的三维精度,表明PPP-RTK定位能够满足多元化高可靠性定位。

河南地矿CORS省域地面沉降监测与机理分析

为了进一步研究省域尺度范围地面沉降,分析河南地矿CORS省域地面沉降的监测方法与其形成机理:针对河南省地面沉降分布特征,采用河南省地质信息连续采集运行系统(HNGICS)的62个基准站数据,时间序列为2012—2019年,获得国际地球参考框架下无净旋转条件的河南省三维速度场;然后分解三维速度场获得河南垂直速度场,发现河南省地面沉降呈现“西稳东沉”的现象,开封附近出现沉降漏斗;最后将河南省地质图、河南省耕地面积占比、河南省年均降雨量与沉降等值线对比分析。结果表明:不同地质条件下,河南省地面沉降分布于豫东地区的第四系冲积层,而相同地质条件下,耕地占比和区域年均降雨量是地表差异性沉降的主要原因,如豫东地区耕地约占总面积的70%,地下水用于农业灌溉是豫东平原出现沉降漏斗的主要原因。

北斗三号带状CORS系统基准站布设距离研究

针对传统的CORS系统在高速公路等带状区域场景下存在的定位性能不足问题,尝试通过构建单站RTK和多站VRS结合的带状CORS系统从而提升定位性能,并实地采集多组不同基线长度的北斗三频观测数据,测试在满足平面2 cm、高程3 cm的最大定位误差前提下,该种CORS服务模式下基站的合理布设距离。实验结果表明,在开阔、轻微遮挡和中度遮挡环境下,满足该定位精度的基线长度分别可以达到30 km、19.7 km、15 km,而对于更长的基线,其定位精度及模糊度固定成功率均明显下降,不能保证定位的可靠性。

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

基于北斗CORS的铁路快速静态测量方法研究

复杂环境下由于卫星信号质量差等原因,常规地区的测量技术标准不具有适用性。为研究复杂环境下快速静态测量的技术方案,利用某铁路带状稀疏卫星导航定位基准站(Continuously Operating Reference Stations,CORS)综合服务系统,开展一系列快速静态测量实验,通过箱形图等方式,分析不同星座、不同观测时长下的测量精度。与铁路控制网的成果比较后发现,观测时长为5~25min且解算成功的前提下,基于CORS的GPS+BDS、单GPS与单BDS的快速静态测量成果计算的外符合精度差异较小,平面和高程中误差整体优于16 mm和45 mm,均可满足像控点测量精度要求;存在解算失败的情况,解算失败的像控点与其距CORS站的距离无显著联系,随着观测时长的增加,解算失败的时段数明显减少。此外,在相同观测时长下,基于CORS的GPS+BDS与单BDS模式测量精度较高,单GPS相对较差。对于复杂环境,北斗CORS系统在铁路快速静态测量方面替代GPS是可行的,建议快速静态测量时长在25 min以上为宜。

铁路带状CORS的VRS内插模型研究

针对铁路带状CORS系统存在的网外收敛速度慢、定位精度低的问题,本文对3种VRS的大气延迟内插模型,即最小二乘配置模型、距离相关内插模型和线性内插模型进行了误差仿真分析。真结果显示,在带状网型中,LSC模型的抗差性能最佳,其次为DIM模型,LIM模型则表现最差。然后基于某高速铁路CORS网络的GNSS观测数据,3种模型进行了实证测试,结果与仿真相吻合。具体为,LSC/DIM/LIM模型的定位精度在水平方向约为3.0、5.3、14.1 cm,高程为3.5、6.8、43.1 cm。LSC模型最适用于带状网络VRS定位。此外,本研究可为铁路CORS系统的精化提供参考。

厦门市台风事件CORS站网数据水汽反演及分析

针对厦门市3次台风事件,利用厦门市连续运行参考站(CORS)的GNSS观测数据,使用PANDA软件进行解算,反演出大气可降水量(PWV),将获取的ERA5再分析数据与反演出的PWV数据进行对比分析,在此基础上分析厦门市受台风影响期间GNSS-PWV变化特征与实际降雨量的关系.结果表明:PWV与ERA5数据具有较好的一致性;GNSS反演PWV具有较高的精度;GNSS-PWV能够较好地反映台风期间水汽的时空动态变化过程,其与降水量之间呈现出明显的相关性.

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.

Large-scale model testing of high-pressure grouting reinforcement for bedding slope with rapid-setting polyurethane

Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining walls,stabilizing piles,and anchors,are time-consuming and labor-and energy-intensive.This study proposes an innovative polymer grout method to improve the bearing capacity and reduce the displacement of bedding slopes.A series of large-scale model tests were carried out to verify the effectiveness of polymer grout in protecting bedding slopes.Specifically,load-displacement relationships and failure patterns were analyzed for different testing slopes with various dosages of polymer.Results show the great potential of polymer grout in improving bearing capacity,reducing settlement,and protecting slopes from being crushed under shearing.The polymer-treated slopes remained structurally intact,while the untreated slope exhibited considerable damage when subjected to loads surpassing the bearing capacity.It is also found that polymer-cemented soils concentrate around the injection pipe,forming a fan-shaped sheet-like structure.This study proves the improvement of polymer grouting for bedding slope treatment and will contribute to the development of a fast method to protect bedding slopes from landslides.

基于网络CORS的架空电力线路弧垂远程检测设计与应用

架空电力线路作为主要的输电线路,数据检测多受到野外环境、气象条件等因素的干扰。基于此,研究借助弧垂检测算法和倾角传感器计算档间弧垂,并以CORS系统实现对问题电力线路的定位检测。该系统能使电压补偿的偏移误差最小值达到-0.1,灵敏度系数补偿最大值趋近于0.1,整体性能较为稳定。且其数据定位精度变化值最大超过了80%,与实际理论值的距离相对误差也在0.06%以下。基于CORS系统的架空电力线路设计能对问题线路和弧垂数据进行定位和动态监测,极大提高了电力监测的精度,降低了人工成本并减少了数据失真,能保证输电线路的安全作业。

城市CORS网基站稳定性分析

连续运行卫星定位导航服务系统(continuous operational reference system,CORS)基准站网作为一座城市地理空间框架的基础硬件设施,为城市规划、市政建设提供实时准确的坐标定位服务与精确的授时服务,这其中保证CORS网系统自身的稳定性是正常运行的基础。以作者所在地城市CORS基准站网为例,通过收集CORS网基站数据、周边IGS站数据,计算与分析CORS网中各基站的稳定性,为后续建设城市CGCS2000坐标系提供基准。

Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics

This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

地形测量中GPS-RTK测量CORS模式结合电台模式的运用研究

分析了CORS模式与电台模式的优缺点,并结合两者联合运用的测绘实例,评价两者联合运用的价值。研究结果表明,CORS模式与电台模式结合使用能够提升地形车辆的效率与准确率,针对复杂地形展开有效的地形测量。

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Large-Scale Carbon Dioxide Storage in Salt Caverns:Evaluation of Operation,Safety,and Potential in China

Underground salt cavern CO_(2) storage(SCCS)offers the dual benefits of enabling extensive CO_(2) storage and facilitating the utilization of CO_(2) resources while contributing the regulation of the carbon market.Its economic and operational advantages over traditional carbon capture,utilization,and storage(CCUS)projects make SCCS a more cost-effective and flexible option.Despite the widespread use of salt caverns for storing various substances,differences exist between SCCS and traditional salt cavern energy storage in terms of gas-tightness,carbon injection,brine extraction control,long-term carbon storage stability,and site selection criteria.These distinctions stem from the unique phase change characteristics of CO_(2) and the application scenarios of SCCS.Therefore,targeted and forward-looking scientific research on SCCS is imperative.This paper introduces the implementation principles and application scenarios of SCCS,emphasizing its connections with carbon emissions,carbon utilization,and renewable energy peak shaving.It delves into the operational characteristics and economic advantages of SCCS compared with other CCUS methods,and addresses associated scientific challenges.In this paper,we establish a pressure equation for carbon injection and brine extraction,that considers the phase change characteristics of CO_(2),and we analyze the pressure during carbon injection.By comparing the viscosities of CO_(2) and other gases,SCCS’s excellent sealing performance is demonstrated.Building on this,we develop a long-term stability evaluation model and associated indices,which analyze the impact of the injection speed and minimum operating pressure on stability.Field countermeasures to ensure stability are proposed.Site selection criteria for SCCS are established,preliminary salt mine sites suitable for SCCS are identified in China,and an initial estimate of achievable carbon storage scale in China is made at over 51.8-77.7 million tons,utilizing only 20%-30%volume of abandoned salt caverns.This paper addresses key scientific and engineering challenges facing SCCS and determines crucial technical parameters,such as the operating pressure,burial depth,and storage scale,and it offers essential guidance for implementing SCCS projects in China.

海南岛CORS站坐标时间序列特征分析

通过GAMIT/GLOBK解算出海南岛CORS站坐标时间序列,分析海南岛CORS站坐标时间序列的噪声特性。根据最优噪声模型,N分量的最优噪声模型呈现多样性特征,E、U分量表现出一致性。分析有色噪声对于噪声量级的影响,仅考虑白噪声会高估其估值精度,须同时考虑白噪声与有色噪声。海南岛CORS站在水平方向都有向SEE向运动的趋势,与华南板块的运动方向一致。沿海测站的坐标时间序列所含的白噪声与闪烁噪声量级比岛内测站大,我国上空电离层的变化对闪烁噪声的影响较大,闪烁噪声量级明显大于白噪声,海南岛CORS站的闪烁噪声量级大于大陆沿海测站。

Factorized Smith Method for A Class of High-Ranked Large-Scale T-Stein Equations

We introduce a factorized Smith method(FSM)for solving large-scale highranked T-Stein equations within the banded-plus-low-rank structure framework.To effectively reduce both computational complexity and storage requirements,we develop techniques including deflation and shift,partial truncation and compression,as well as redesign the residual computation and termination condition.Numerical examples demonstrate that the FSM outperforms the Smith method implemented with a hierarchical HODLR structured toolkit in terms of CPU time.