Time-varying sliding mode control for a class of uncertain MIMO nonlinear system subject to control input constraint

To solve the regulator problem of a class of uncertain MIMO nonlinear systems subject to control input constraint, three types of time-varying sliding mode control laws are proposed. The sliding surfaces pass the initial value of the system at the initial time, and are shifted/rotated towards the predetermined ones. The controller parameters are optimized by genetic algorithm (GA). Lyapunov method is adopted to prove the stability and robustness to the parameter uncertainties and external disturbance. By me...     

Multi-sensor calibration through iterative registration and fusion

In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively registering the discrete 3D sensor data against an evolving reconstructed B-spline surface, which results from the Kalman filter-based multi-sensor data fusion. Upon each registration, the sensor data gets closer to the surface. Upon fusing the newly registered sensor data with the surface, the updated surface represents the sensor data more accurately. We prove that such an iterative registration and fusion process is guaranteed to converge. We further demonstrate in experiments that the IRF can result in more accurate and more stable calibration than many classical point cloud registration methods.     

The CM-SAF operational scheme for the satellite based retrieval of solar surface irradiance — A LUT based eigenvector hybrid approach

The radiation budget at the earth surface is an essential climate variable for climate monitoring and analysis as well as for verification of climate model output and reanalysis data. Accurate solar surface irradiance data is a prerequisite for an accurate estimation of the radiation budget and for an efficient planning and operation of solar energy systems.This paper describes a new approach for the retrieval of the solar surface irradiance from satellite data. The method is based on radiative transfer modelling and enables the use of extended information about the atmospheric state. Accurate analysis of the interaction between the atmosphere, surface albedo, transmission and the top of atmosphere albedo has been the basis for the new method, characterised by a combination of parameterisations and “eigenvector” look-up tables. The method is characterised by a high computing performance combined with a high accuracy. The performed validation shows that the mean absolute deviation is of the same magnitude as the confidence level of the BSRN (Baseline Surface Radiation Measurement) ground based measurements and significant lower as the CM-SAF (Climate Monitoring Satellite Application Facility) target accuracy of 10 W/m². The mean absolute difference between monthly means of ground measurements and satellite based solar surface irradiance is 5 W/m² with a mean bias deviation of − 1 W/m² and a RMSD (Root Mean Square Deviation) of 5.4 W/m² for the investigated European sites. The results for the investigated African sites obtained by comparing instantaneous values are also encouraging. The mean absolute difference is with 2.8% even lower as for the European sites being 3.9%, but the mean bias deviation is with − 1.1% slightly higher as for the European sites, being 0.8%. Validation results over the ocean in the Mediterranean Sea using shipboard data complete the validation. The mean bias is − 3.6 W/m² and 2.3% respectively. The slightly higher mean bias deviation over ocean is at least partly resulting from inherent differences due to the movement of the ship (shadowing, allocation of satellite pixel). The validation results demonstrate that the high accuracy of the surface solar irradiance is given in different climate regions. The discussed method has also the potential to improve the treatment of radiation processes in climate and Numerical Weather Prediction (NWP) models, because of the high accuracy combined with a high computing speed.     

Large-area assessment of impervious surface based on integrated analysis of single-date Landsat-7 images and geospatial vector data

Driven by a constantly accelerating increase of urban population in recent decades urban sprawl has become one of the most dynamic processes in the context of global land use transformations. The expansion of urban agglomerations is closely associated with a substantial increase of impervious surface. In Europe, methods for an accurate, fast and cost-effective mapping and assessment of impervious surface on a state-wide or national scale have not been established so far. This study presents an approach for estimating the impervious surface based on a combined analysis of single-date Landsat images and road network and railway vector data using Support Vector Machines and functionalities of geographic information processing. The modeling aims at the provision of data on the impervious surface for the total of residential, industrial and transportation-related areas. The derived information is provided for the administrative units of communities. The output of the procedure is a vector data file providing the ‘percent impervious surface of built-up areas’ (PIS_B) and the ‘percent impervious surface of the total of built-up and transportation-related areas’ (PIS_BT) for the administrative units of communities. The developed method is tested for a study area covering almost one third of the German territory. The results prove the suitability of the approach for a widely automated and area-wide mapping of impervious surfaces. Using reference data sets of three cities (Leipzig, Ludwigshafen, Passau) we realized a mean absolute error of 19.8% and an average error of 6.4% for the percent impervious surface modeled on the basis of the Landsat images. The final product resulting from a combination of the imperviousness raster derived from the satellite images with the transportation-related vector information showed a mean difference of 1% to 4% compared to corresponding reference data and results of previous studies. For the year 2000 our research shows that 45.3% of the area occupied by settlements and transport infrastructure in the German federal state of Bavaria, 44.6% in the state of Baden-Württemberg and 42.6% in the state of Saxony was covered by impervious surface.     

Variational implicit surface meshing

In this paper, we propose a new algorithm to mesh implicit surfaces which produces meshes both with a good triangle aspect ratio as well as a good approximation quality. The number of vertices of the output mesh is defined by the end-user. For this goal, we perform a two-stage processing: an initialization step followed by an iterative optimization step. The initialization step consists in capturing the surface topology and allocating the vertex budget. The optimization algorithm is based on a variational vertices relaxation and triangulation update. In addition a gradation parameter can be defined to adapt the mesh sampling to the curvature of the implicit surface. We demonstrate the efficiency of the approach on synthetic models as well as real-world acquired data, and provide comparisons with previous approaches.     

Discrete Critical Values: a General Framework for Silhouettes Computation

Many shapes resulting from important geometric operations in industrial applications such as Minkowski sums or volume swept by a moving object can be seen as the projection of higher dimensional objects. When such a higher dimensional object is a smooth manifold, the boundary of the projected shape can be computed from the critical points of the projection. In this paper, using the notion of polyhedral chains introduced by Whitney, we introduce a new general framework to define an analogous of the set of critical points of piecewise linear maps defined over discrete objects that can be easily computed. We illustrate our results by showing how they can be used to compute Minkowski sums of polyhedra and volumes swept by moving polyhedra.     

WorldView卫星16波段影像光谱特征分类

传统的高分辨率遥感卫星光谱分辨率较低,WorldView卫星在8个可见光G近红外多光谱波段的基础上,新增加的８个短波红外(short wave infrared,SWIR)影像,有助于提高影像提取地物信息能力。分析了WorldView卫星的16波段影像上各种地物的光谱特征和分类性能,提出了新的植被指数、水体指数和建成区指数。实验表明,相比于8波段影像,使用16波段影像分类能够显著提高各类地物特别是裸地、建筑物和道路的分类精度,总体精度提高约5.5％。基于16波段设计的新地物特征指数能更好地避免干扰地物,通过简单阈值提取地物,取得较高的提取精度。     

基于网格的散乱点曲面重构技术

提出一种利用网格技术实现散乱点曲面重构的方法,设计适合网格并行的松耦合分层重构算法,在此基础上研究基于Agent技术的智能任务分解机制和基于Condor-G技术的任务分配与调度策略,并搭建网格实验平台进行测试。对重构结果的分析表明,该技术可提高基于散乱点的曲面重构速度,降低应用成本。     

三维图像中边界曲面的抽取与半透明可视化

已有算法在重构及可视化梯度值从高到低变化且包含弱边界的边界曲面时无法分辨弱边界与噪声碎片。针对上述问题,提出边界曲面半透明显示方法。采用半透明显示技术显示边界曲面及附着在其上的小碎片,利用人的智能及知识在观察可视化结果时对小碎片及弱边界进行有效的区分。结果证明,该方法有助于正确理解及完整显示三维图像中梯度值从高到低变化的边界曲面,为进一步的交互式操作去除小碎片提供依据。