基于神经网络的无人机影像多目标检测方法

针对现有方法检测无人机目标时精度与泛化能力不足,提出一种基于回归的多目标检测方法.使用密集连接增强层间信息传递,添加批量再规范化(Batch Renormalization,BRN)层加速模型训练,降低样本分布不均而导致的精度偏低,使用密集连接结构聚合上采样层不同层信息.以开源数据集Vision Drone为基础建立优化数据集训练模型.结果表明,提出模型检测精度达89.57％平均精度均值,相比(You Only Look Once v3,YOLOv3)模型和(Region Full Convolutional Network,R-FCN)分别提高6.53％和3.11％,检测速度达27每秒传输帧数,在不同场景表现稳定.     

附有道路信息约束的自适应卡尔曼滤波在车载导航中的应用

基于车辆"当前"统计模型,利用白适应卡尔曼滤波对车载GPS动态数据进行了处理.将制约车辆运动的道路信息引入模型中,作为约束条件引入卡尔曼滤波方程.其思路是在原有滤波的基础上,利用道路信息约束条件对滤波方程中的一步预测值进行修正,以提高滤波结果的精度.实验结果表明,该算法具有实用意义.     

基于SPOT-5图像的城市水体自动提取模型研究

以南京市主城区为对象,研究基于SPOT-5图像的城市地区水体信息的提取方法.分析表明,对SPOT-5的SWIR波段进行简单的阈值处理,可以清晰地将水体与阴影提取出来.在分析水体和阴影光谱特征和空间特征（形状指数等）的基础上,建立了基于SPOT-5图像的城市地区水体的自动提取决策树模型.精度验证表明,该模型的水体提取精度较监督分类的提取精度提高2.5%,尤其在具有许多建筑物阴影的局部区域,本模型的水体提取精度提高11.6%.此外,本模型还具有很好的移植性,只是在阈值大小的确定上会有部分差异.     

倾斜摄影技术的单体塔式建筑物三维重建方法

针对塔式单体建筑物形状不规则导致三维模型构建失败,提出倾斜摄影技术的塔式单体建筑物三维重建方法. 选用消费型多旋翼无人机搭载单镜头的相机,通过环线拍摄的方式获取多视影像数据,通过ContextCapture软件对获取的多视影像数据进行处理,构建塔式建筑物的实景三维模型,利用外业控制点、纹理细节信息对生成的三维模型精度评定. 试验表明:环线航拍获取多视影像数据构建三维模型,精度较高、模型纹理信息缺失少、完整度高.      

GPS导航解算中几种非线性Kalman滤波的理论分析与比较

GPS导航解算中常采用离散线性Kalman滤波模型.由于线性化忽略高次项,加之线性化受初始值精度的影响,导致线性化模型精度很难满足高动态用户需求.为此,分别讨论了扩展Kalman滤波和Bancroft算法以及利用观测信息迭代精化观测方程三种算法,并结合算例进行了比较与分析.     

干涉合成孔径雷达(INSAR)复图像配准方法

合成孔径雷达干涉测量技术是使用图像中的相位信息来提取高精度的数字地面高程模型.精确的图像配准是合成孔径雷达干涉技术提取数字高程模型的关键步骤之一,配准质量将直接影响提取的地面高程的精度.配准按照其精度分为粗配准和精配准.文中采用基于幅度互相关函数法完成图像的粗配准,在粗配准的基础上,使用最小二乘配准算法进一步提高配准的精度.实际数据处理表明,配准精度能够满足INSAR数据处理的要求.     

基于LiDAR点云的复杂钢结构模型重建

传统的基于全站仪等单点测量技术难以获取钢结构整体信息,且测量速度慢、模型重建精度低。针对此问题,本文将三维激光扫描技术应用于钢结构模型重建领域,提出了基于LiDAR点云的复杂钢结构模型重建方法。首先,基于标靶球和钢结构面信息实现多测站点云的高精度配准,并通过半径滤波算法去除噪点,以得到完整的激光点云数据;然后,对复杂钢结构单体模型进行分割,以实现各个部件的模型重建;最后,根据现场实测数据对重建的三维模型进行精度评估。试验结果表明,基于该方法得到的模型精度较高,与实际尺寸差值均小于1 cm,为复杂钢结构的三维模型重建提供了有效解决方案。     

基于 SPOT-5影像的吴哥地区水体提取方法研究

对于一个较小研究区提取地物信息,需要更高的空间分辨率和适合的光谱信息。以柬埔寨吴哥窟西北部为研究对象,开展基于SPOT-5影像的水体信息提取方法研究。通过分析研究区内的地物光谱特征信息,发现各地物在绿色波段和短波红外波段虽然都有下降趋势,但是水体的变化程度最大。利用这个信息建立决策树的一种水体提取模型:Band3/Band41.73并且Band1Band4。通过与NDWI法、决策树模型提取精度进行对比,证明该模型提取精度有较大提高,可有效地消除水田对提取精度的影响。     

倾斜摄影测量在建筑附属设施施工中的应用

以某图书馆的雨棚为例,首先利用消费级无人机采集雨棚的数据信息,再通过Smart-3D软件构建雨棚三维模型,然后分别量测三维模型和实际雨棚框架的检查点来分析精度,最后利用EPS软件勾画龙骨框架,利用AutoCAD软件生成并导出最终模型.结果表明,通过无人机倾斜摄影测量的方法可有效获取建筑附属设施的尺寸信息,其结果既符合G...     

基于速度场模型的区域CGCS2000坐标实时转换

从WGS84到CGCS2000的坐标转换,涉及坐标框架转换和历元转换两个问题.如何提高大区域坐标转换精度,是一直以来的研究热点,针对大区域坐标转换精度较低的问题,考虑历元转换,提出融合速度场改正信息的坐标转换方法.该方法对建立速度场改正模型进行了研究,分析比较了各模型的精度和可靠性,在此基础上选择一种模型用于实现CGC...     

平面相似变换之模型可靠性研究

介绍了平面相似变换建模联测点粗差探测因子的确定方法，提出了利用信息扩散估计探测建模联测点粗差的操作方法，研究了利用近似t-检验构建模型可靠性判据的理论和方法，并进行了实例计算与分析。     

激光雷达点云树木建模研究进展与展望

三维树木几何模型是数字城市与数字林业工程的重要组成部分.针对点云树木建模,深入分析了基于广义(泛在)激光雷达点云的树木模型重建方法,提出了聚类思想建模、图论方法建模、先验假设建模、拉普拉斯算子建模与轻量化表达建模5类建模体系,归纳总结了不同建模体系在树冠枝干的细节表达、建模算法性能、树木模型的多层次细节表达、建模体系综...     

Effect of heteroscedasticity and heterogeneousness on outlier detection for geodetic networks

The robustness of an outlier detection method strongly depends on the weights of observations, i.e., the type of the stochastic model applied (homoscedasticity, heteroscedasticity and heterogeneousness). In this paper, we have investigated how the reliability of the robust methods and tests for outliers changes depending on the weights of the observations in geodetic networks. Furthermore, the contribution of the directions and distances to horizontal control network with regard to reliability are investigated separately. The concept of a breakdown point is used as a global measure of robustness against outliers. The mean success rate (MSR) is found to be a practical tool for confirming the breakdown point. Many different “good” data samples are generated for each network and then deliberately contaminated using a Monte-Carlo simulation. Six robust methods and Baarda’s test are applied to the corrupted samples and the degree of corruption is varied. The performance of each method is measured using both local and global MSRs. Our research shows: (1) The MSRs of Baarda’s test change depending on the strength of the heteroscedasticity, but do not change for trilateration and leveling networks, (2) the global MSRs of robust methods do not differ considerably from the local ones     

Measuring the robustness potential of the least-squares estimation: geodetic illustration

For a linear least-squares parametric model analysis is carried out of the structure of the projection operator transforming the vector of standardised observations into the vector of standardised residuals. On this basis the properties of the model responses to observational disturbances (i.e. gross errors or blunders) are derived. A final outcome of the research can be summarised as: (1) proposing the robustness characteristics of a model and linking them with the local measures of internal reliability, being the diagonal elements in the projection operator; (2) determining the internal reliability levels satisfying specified robustness requirements, i.e. the possibility of detecting at least one of the k observational disturbances (k=1,2,…) having most disadvantageous locations in the system. The theory and a numerical example show that for the systems which have been designed to a proper level of internal reliability, the least-squares estimation can demonstrate an accordingly high level of robustness. Received: 11 June 1996 / Accepted: 28 April 1997     

Enhancing the Reliability of 3D Subsurface Models through Differential Weighting and Mathematical Recombination of Variable Quality Data

One of the first stages of the three‐dimensional (3D) subsurface modeling process involves collation and analysis of available borehole and/or outcrop data to identify individual subsurface units, usually distinguished by the grain size of the sediment, and the elevation of their bounding contacts. Input data can come from a variety of sources and may be categorized according to their reliability and/or quality. The output from the 3D model is a prediction of subsurface conditions based on these data and the reliability of the output model is highly dependent on both the quality of input data and the types of interpolation methods used. This article presents a new quality weighting methodology that allows the user to assign a differential weighting factor to data points of variable quality in the modeling process. Input data are categorized into high and low quality datasets which are then recombined using a grid math process in which a differential “weighting” factor is applied. This allows the 3D modeling program to maximize the use and effectiveness of data from all available sources while giving high quality data greater influence on the final model output, and will result in the generation of more accurate and reliable 3D subsurface models.     

Application of spectral decomposition algorithm for mapping water quality in a turbid lake (Lake Kasumigaura,Japan) from Landsat TM data

The remote sensing of Case 2 water has been far less successful than that of Case 1 water, due mainly to the complex interactions among optically active substances (e.g., phytoplankton, suspended sediments, colored dissolved organic matter, and water) in the former. To address this problem, we developed a spectral decomposition algorithm (SDA), based on a spectral linear mixture modeling approach. Through a tank experiment, we found that the SDA-based models were superior to conventional empirical models (e.g. using single band, band ratio, or arithmetic calculation of band) for accurate estimates of water quality parameters. In this paper, we develop a method for applying the SDA to Landsat-5 TM data on Lake Kasumigaura, a eutrophic lake in Japan characterized by high concentrations of suspended sediment, for mapping chlorophyll-a (Chl-a) and non-phytoplankton suspended sediment (NPSS) distributions. The results show that the SDA-based estimation model can be obtained by a tank experiment. Moreover, by combining this estimation model with satellite-SRSs (standard reflectance spectra: i.e., spectral end-members) derived from bio-optical modeling, we can directly apply the model to a satellite image. The same SDA-based estimation model for Chl-a concentration was applied to two Landsat-5 TM images, one acquired in April 1994 and the other in February 2006. The average Chl-a estimation error between the two was 9.9%, a result that indicates the potential robustness of the SDA-based estimation model. The average estimation error of NPSS concentration from the 2006 Landsat-5 TM image was 15.9%. The key point for successfully applying the SDA-based estimation model to satellite data is the method used to obtain a suitable satellite-SRS for each end-member.     

基于椭球面三角格网的数字高程建模

针对传统的DEM在模拟表达大面积地形时具有存在裂缝、地理分析不精确、数据冗余等问题，在椭球面四元三角格网QTM层次剖分的基础上，提出了一种基于椭球面三角格网层次剖分的数字高程建模方法，该方法避免了上述缺陷。应用全球GTOP030数据对该方法进行了验证。     

基于三维激光扫描技术在崖墓保护中的应用

以满城汉墓中山靖王墓室为例,利用三维激光扫描技术对古代崖墓进行扫描建模研究,获得了墓室真实尺寸的三维彩色模型,研究所制定的流程方案为今后开展类似研究提供了参考依据.     

基于三维激光扫描的校园建筑物三维建模研究

"数字校园"建设是科技发展的必然趋势,为加快这一进程,本次研究将地面三维激光扫描技术应用到大学校园。本文以Z+F IM AGER 5010c地面三维激光扫描仪采集到的吉林建筑大学基础实验楼数据为基础,运用3ds max、Auto CAD、Point Cloud等建模软件建立三维模型。同时将依据点云数据建立的实体模型与实际测量数据进行对比和精度分析,验证了地面三维激光扫描仪在建筑物三维模型建立中的精度和可靠性。