多核处理器的机载激光雷达点云并行三角网渐进加密滤波方法

滤波是机载LiDAR点云数据处理的关键步骤之一,点云数据的海量化特性使得一般的串行化滤波处理方法无法满足快速成图的应用需求。提出一种基于多核计算技术的并行三角网渐进加密滤波方法,将串行方法中最耗时的三角网构建与脚点判别过程进行了并行化改造。三角网构建算法的并行化基于分治法实现,脚点判别算法的并行化采用一种随机分配策略将三角网划分为多个离散分布的三角形子集合来实现负载均衡。并行滤波方法在8核环境下多次渐进加密的实际加速比达到3.1左右。试验证明,该方法可以充分发挥多核计算优势,并且对不同分布形态点云数据具有良好的适应性。     

R-T-S平滑算法在POS数据后处理中的应用

高精度的定位定姿系统（POS,Position and Orientation System）在测绘领域发挥着重要的作用,为了提高数据的精度,将平滑技术应用于POS数据的后处理中.文中介绍POS数据后处理算法的流程,对平滑技术尤其是应用最为广泛的R-T-S平滑进行详细分析,并对该算法进行数值仿真.结果表明,与传统的卡尔曼滤波相比,R-T-S平滑不仅可以提高位置姿态精度,而且在卫星信号失锁的情况下精度也能得到大幅改善,是一种有效的数据处理算法.     

自适应卡尔曼滤波在沉降预测中的应用

随着我国经济高速发展,对煤炭资源的需求与日俱增,矿山大量开采造成矿区地表大面积沉陷.对于地下采煤,地表点的移动经历一个由开始移动到剧烈移动,最后到停止移动的全过程.为了更好地掌握矿山开采地袁沉降移动规律,本文采用自适应卡尔曼滤波与标准卡尔曼滤波对其进行预测与分析.     

基于GPS软件接收机的SINS／GPS紧组合系统仿真

为了系统验证SINS／GPS紧组合系统的性能,基于GPS软件接收机,进行了仿真系统构建。仿真系统由轨迹发生器、GPS中频信号模拟器、IMU信号模拟器、GPS软件接收机、SINS导航解算模块、组合滤波算法和导航性能分析模块等部分构成,其中详细设计了GPS软件接收机中的捕获和跟踪算法、SINS解算以及基于伪距和伪距率的组合滤波算法。仿真结果表明：紧组合导航系统收敛性较好,能够一定程度上抑制惯导系统误差的积累,有较好的导航性能。设计的该系统满足紧组合导航系统性能验证的需要,也为后续的超紧组合研究奠定了良好的基础。     

结合卡尔曼滤波的城市路段速度估计

本文以城市出租车为浮动车数据采集源,介绍了基于GPS数据的实时路段速度估计的基本方法。针对目标路段GPS数据样本量不足的情况,考虑邻近区域的路段速度、上周同日速度、前一时刻速度等与目标路段当前时刻速度等密切相关的变量,建立多元线性回归方程,利用卡尔曼滤波融合预测值和测量值,从而提高路段行驶速度的估计精度。选择广州市东风路作为测试实例,融合值比测量值误差降低9%,绝对相对误差变动系数减少4%,表明结合卡尔曼滤波技术的城市路段速度估计精度和稳定性均得到提高。     

Generation of differential GPS corrections along with performance of quality control

The DGPS technique can provide considerably better relative positioning accuracy than the stand-alone GPS positioning, but the improvement depends on the distance between the user and the reference station (spatial correlation), the latency of differential corrections (temporal correlation), and the quality of differential corrections. Therefore, how to correctly generate differential corrections as well as their pricision is very important to the DGPS positioning technique. This paper presents a new algorithm for generating differential GPS corrections. This algorithm directly uses code and carrier observations in the measurement model of a Kalman filter, so that it is possible to use a simple stochastic model and to use the standard algorithm of the Kalman filter. The algorithm accounts for biases like multipath errors and instrumental delays in code observations and it shows how differential corrections are differently affected by code biases when dual or single frequency data is used. In addition, the algorithm can be integrated with a real time quality control procedure. As a result, the quality of differential corrections can be guaranteed with a certain probability.     

Dual states estimation of a subsurface flow-transport coupled model using ensemble Kalman filtering

Modeling the spread of subsurface contaminants requires coupling a groundwater flow model with a contaminant transport model. Such coupling may provide accurate estimates of future subsurface hydrologic states if essential flow and contaminant data are assimilated in the model. Assuming perfect flow, an ensemble Kalman filter (EnKF) can be used for direct data assimilation into the transport model. This is, however, a crude assumption as flow models can be subject to many sources of uncertainty. If the flow is not accurately simulated, contaminant predictions will likely be inaccurate even after successive Kalman updates of the contaminant model with the data. The problem is better handled when both flow and contaminant states are concurrently estimated using the traditional joint state augmentation approach. In this paper, we introduce a dual estimation strategy for data assimilation into a one-way coupled system by treating the flow and the contaminant models separately while intertwining a pair of distinct EnKFs, one for each model. The presented strategy only deals with the estimation of state variables but it can also be used for state and parameter estimation problems. This EnKF-based dual state-state estimation procedure presents a number of novel features: (i) it allows for simultaneous estimation of both flow and contaminant states in parallel; (ii) it provides a time consistent sequential updating scheme between the two models (first flow, then transport); (iii) it simplifies the implementation of the filtering system; and (iv) it yields more stable and accurate solutions than does the standard joint approach. We conducted synthetic numerical experiments based on various time stepping and observation strategies to evaluate the dual EnKF approach and compare its performance with the joint state augmentation approach. Experimental results show that on average, the dual strategy could reduce the estimation error of the coupled states by 15% compared with the joint approach. Furthermore, the dual estimation is proven to be very effective computationally, recovering accurate estimates at a reasonable cost.     

基于数学模型的陕西黑河水源区植被过滤带效果评估

为探讨运用数学模型进行植被过滤带效果评估的方法,以陕西黑河水源区为例,通过植被过滤带水文及泥沙输移模型,分析了植被过滤带的带宽及坡度对入流泥沙净化效果的影响,确定适宜的植被过滤带设置方法,并采用污染负荷~泥沙关系法对植被过滤带的流域非点源污染负荷削减效果进行估算。结果表明:草地植被过滤带带宽以3~5 m为宜,且应设置于坡度小于60°的河岸岸坡;在黑河水源区内的可设带区域全部设置植被过滤带后,将削减泥沙负荷的21.7%,TP负荷的12.4%和TN负荷的14.3%,植被过滤带能够在黑河水源区的水质保护中起到重要作用。     

基于Matlab的最小相位滤波在处理影区地震中的初步研究

研究基于Matlab的最小相位滤波器在处理影区地震中的应用。使用共轭倒序法设计滤波器对合肥地震台记录的中国台湾影区地震进行滤波处理,有效抑制地动噪声干扰,突出地震信号特征,为地震分析提供较好的帮助。     

高庙子膨润土与砂混合物的土-水特征曲线

用滤纸法和压力板法对高庙子膨润土与福建砂的混合物进行试验研究,在不同孔隙比和不同膨润土与砂配合比情况下量测脱湿过程的土-水特征曲线,研究土-水特征曲线与孔隙比和配合比之间的关系。试验结果表明：在同一配合比下用饱和度与吸力表示土-水特征曲线时,其曲线随着孔隙比的减小向右上方移动,即当土样的吸力一定时,土样的饱和度随着孔隙比的减小而增大,当吸力小于10 MPa时,这种现象较为显著;在同一孔隙比下膨润土与砂混合物的土-水特征曲线随着膨润土的比例增加而向右上方移动,即混合物的进气值随着膨润土的比例增加而增大;另外,配合比以及孔隙比相同时,膨润土与福建砂的混合物的土-水特征曲线与日本产Kunigel膨润土与丰浦砂的混合物的土-水特征曲线非常接近。