Assessment of code bias variations of BDS triple-frequency signals and their impacts on ambiguity resolution for long baselines

GPS Solutions - Carrier phase ambiguity resolution over long baselines is challenging in BDS data processing. This is partially due to the variations of the hardware biases in BDS code signals and...     

Design of an adaptive GPS vector tracking loop with the detection and isolation of contaminated channels

GPS Solutions - In vector tracking loop (VTL), the relativity among received signals is exploited to deeply integrate the entire information within signal processing channels. However, the tracking...     

AAC算法的大气校正复合改进算法

利用模拟数据,评价Autonomous Atmospheric Compensation(AAC)算法的抗噪性,认为AAC算法的抗噪性较弱。基于TASI实测数据,利用AAC算法开展反演计算时,计算结果呈现出多样性问题。结合In-scene Atmospheric Compensation(ISAC)算法中黑体像元的标定方法,提出了一种复合改进算法。首先,利用ISAC算法反演的大气透过率和路径辐射,重新计算AAC算法中大气透过率之比(Tr)和相邻两强弱吸收通道的路径辐射之差(Pd),再次,运用经验公式获得稳定的大气反演结果(大气透过率和路径辐射),有效解决了计算结果多样性的问题。利用复合改进算法,开展的温度与发射率分离实验,证明反演得到的发射率波谱更接近野外实测波谱。     

开放式地理实体关系抽取的Bootstrapping方法

从网络文本中抽取地理实体间空间关系和语义关系要求高时效性和强鲁棒性。本文提出一种开放式地理实体关系的自动抽取方法,通过bootstrapping技术统计词语的词性、位置和距离特征来计算语境中词语权值,据此确定描述地理实体关系的关键词,最终组织成结构化实例,并使用百度百科和Stanford CoreNLP开展了试验。研究结果表明,本文方法能自动挖掘自然语言的部分词法特征,无须领域专家知识和大规模标注语料,适用于未知关系类型的信息抽取任务;较之经典的Frequency、TFIDF和PPMI频率统计方法,精度和召回率分别提升约5%和23%。     

井上下一体化三维信息管理与应急系统构建

基于构建的地质体和特殊构造的混合真实网格模型、巷道纹理自动添加及不同巷道交叉拼接技术,实现了集工业广场与井巷、地质体及采掘工作面于一体的井上下三维表达;利用多判据融合技术,研发了基于井下定位传感网的人员逃生避险线路规划与决策支持系统,实现了井下人员避灾疏散、逃生自救等功能。示范应用表明,该系统显著提高了煤矿安全生产管理与应急决策的信息化和科学化水平。     

Grid pattern recognition in road networks using the C4.5 algorithm

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.     

Curve matching approaches to waveform classification: a case study using ICESat data

Light Detection and Ranging (LiDAR) waveforms are being increasingly used in many forest and urban applications, especially for ground feature classification. However, most studies relied on either discretizing waveforms to multiple returns or extracting shape metrics from waveforms. The direct use of the full waveform, which contains the most comprehensive and accurate information has been scarcely explored. We proposed to utilize the complete waveform to test its ability to differentiate between objects having distinct vertical structures using curve matching approaches. Two groups of curve matching approaches were developed by extending methods originally designed for pixel-based hyperspectral image classification and object-based high spatial image classification. The first group is based on measuring the curve similarity between an unknown waveform and a reference waveform, including curve root sum squared differential area (CRSSDA), curve angle mapper (CAM), and Kullback–Leibler (KL) divergence. The second group assesses the curve similarity between an unknown and reference cumulative distribution functions (CDFs) of their waveforms, including cumulative curve root sum squared differential area (CCRSSDA), cumulative curve angle mapper (CCAM), and Kolmogorov–Smirnov (KS) distance. When employed to classify open space, trees, and buildings using ICESat waveform data, KL provided the highest average classification accuracy (87%), closely followed by CCRSSDA and CCAM, and they all significantly outperformed KS, CRSSDA, and CAM based on 15 randomized sample sets.     

智能手机音频信号与MEMS传感器的紧耦合室内定位方法

基于智能手机内置的传感器,开展了音频信号和MEMS传感器的紧组合室内定位研究.首先,将时频分析技术用于音频信号TOA估计,提出了一种基于短时傅里叶变换和优化互相关方法的两步估计方法.之后,研究了一种基于音频T DOA和行人航迹推算的紧组合定位算法,静态测试的平均定位精度为0.238 m,相比最小二乘方法提高了38.66...     

倾斜立体影像匹配若干问题研究

倾斜摄影技术是近年发展起来的一项高新技术.航空倾斜摄影系统颠覆了以往只能从垂直角度拍摄的局限,通过在同一飞行平台上搭载多台传感器,同时从垂直和倾斜角度采集影像,将用户引入了符合人眼视觉的真实直观世界,已成为当前获取空间信息的有效方式之一,在三维城市建设等领域有着独特的优势.由于在获取影像过程中传感器视角发生显著变化,导致影像间存在较大的几何和辐射畸变、同名区域遮挡等问题,加大了计算机自动确定同名特征的难度,直接导致了倾斜影像空三解算及地物空间信息提取相对传统航测影像更为困难.因此,研究倾斜立体影像的可靠自动匹配算法对推动倾斜航空摄影测量快速发展具有重要的理论和实用价值.     

地面激光扫描技术在建筑变形测量中的应用探讨

已有不少文献针对激光扫描在建筑变形测量中的应用进行了研究,但是国家和行业尚无三维激光扫描技术规程出台。本文通过应用调研、扫描仪的标称精度统计分析,以及具有针对性的试验,明确了激光扫描测量建筑变形的作业方法,确立了选用仪器精度、扫描测量的测回数、标靶入射角度等技术指标,为激光扫描技术在建筑变形测量中的工程应用提供了参考依据。