Application of Multi-Scale Tracking Radar Echoes Scheme in Quantitative Precipitation Nowcasting

A new radar echo tracking algorithm known as multi-scale tracking radar echoes by cross-correlation （MTREC） was developed in this study to analyze movements of radar echoes at different spatial scales. Movement of radar echoes, particularly associated with convective storms, exhibits different characteristics at various spatial scales as a result of complex interactions among meteorological systems leading to the formation of convective storms. For the null echo region, the usual correlation technique produces zero or a very small magnitude of motion vectors. To mitigate these constraints, MTREC uses the tracking radar echoes by correlation （TREC） technique with a large ＂box＂ to determine the systematic movement driven by steering wind, and MTREC applies the TREC technique with a small ＂box＂ to estimate small-scale internal motion vectors. Eventually, the MTREC vectors are obtained by synthesizing the systematic motion and the small-scale internal motion. Performance of the MTREC technique was compared with TREC technique using case studies： the Khanun typhoon on 11 September 2005 observed by Wenzhou radar and a squall-line system on 23 June 2011 detected by Beijing radar. The results demonstrate that more spatially smoothed and continuous vector fields can be generated by the MTREC technique, which leads to improvements in tracking the entire radar reflectivity pattern. The new multi-scMe tracking scheme was applied to study its impact on the performance of quantitative precipitation nowcasting. The location and intensity of heavy precipitation at a 1-h lead time was more consistent with quantitative precipitation estimates using radar and rain gauges.

Synchronization of Radar Observations with Multi-Scale Storm Tracking

The 3-D radar reflectivity data has become increasingly important for use in data assimilation towards convective scale numerical weather prediction as well as next generation precipitation estimation. Typically, reflectivity data from multiple radars are objectively analyzed and mosaiced onto a regional 3-D Cartesian grid prior to being assimilated into the models. One multi-radar observations is the synchronization of all of the scientific issues associated with the mosaic of the observations. Since radar data is usually rapidly updated （-every 5-10 min）, it is common in current multi-radar mosaic techniques to combine multiple radar＇ observations within a time window by assunfing that the storms are steady within the window. The assumption holds well for slow evolving precipitation systems, but for fast evolving convective storms, this assumption may be violated and the mosaic of radar observations at different times may result in inaccurate storm structure depictions. This study investigates the impact of synchronization on storm structures in multiple radar data analyses using a multi-scale storm tracking algorithm.

Optimal Tracking Controller Design for a Small Scale Helicopter

A model helicopter is more difficult to control than its full scale counterpart. This is due to its greater sensitivity to control inputs and disturbances as well as higher bandwidth of dynamics. This work is focused on designing practical tracking controller for a small scale helicopter following predefined trajectories. A tracking controller based on optimal control theory is synthesized as a part of the development of an autonomous helicopter. Some issues with regards to control constraints are addressed. The weighting between state tracking performance and control power expenditure is analyzed. Overall performance of the control design is evaluated based on its time domain histories of trajectories as well as control inputs.

Multi-Scale Human Pose Tracking in 2D Monocular Images

In this paper we address the problem of tracking human poses in multiple perspective scales in 2D monocular images/videos. In most state-of-the-art 2D tracking approaches, the issue of scale variation is rarely discussed. However in reality, videos often contain human motion with dynamically changed scales. In this paper we propose a tracking framework that can deal with this problem. A scale checking and adjusting algorithm is proposed to automatically adjust the perspective scales during the tracking process. Two metrics are proposed for detecting and adjusting the scale change. One metric is from the height value of the tracked target, which is suitable for some sequences where the tracked target is upright and with no limbs stretching. The other metric employed in this algorithm is more generic, which is invariant to motion types. It is the ratio between the pixel counts of the target silhouette and the detected bounding boxes of the target body. The proposed algorithm is tested on the publicly available datasets (HumanEva). The experimental results show that our method demonstrated higher accuracy and efficiency compared to state-of-the-art approaches.

Optimal tracking control for nonlinear large-scale systems with persistent disturbances

This paper studies the optimal control with zero steady-state error problem for nonlinear large-scale systems affected by external persistent disturbances.The nonlinear large-scale system is transformed into N nonlinear subsystems with interconnect terms.Based on the internal model principle,a disturbance compensator is constructed such that the ith subsystem with external persistent disturbances is transformed into an augmented subsystem without disturbances.According to the sensitivity approach,the optimal tracking control law for the ith nonlinear subsystem can be obtained.The optimal tracking control law for the nonlinear large-scale systems can be obtained.A numerical simulation shows that the method is effective.

Optimal tracking control for linear time-delay large-scale systems with persistent disturbances

An optimal tracking control （OTC） problem for linear time-delay large-scale systems affected by external persistent disturbances is investigated. Based on the internal model principle, a disturbance compensator is constructed. The system with persistent disturbances is transformed into an augmented system without persistent disturbances. The original OTC problem of linear time-delay system is transformed into a sequence of linear two- point boundary value （TPBV） problems by introducing a sensitivity parameter and expanding Maclaurin series around it. By solving an OTC law of the augmented system, the OTC law of the original system is obtained. A numerical simulation is provided to illustrate the effectiveness of the proposed method.

基于神经认知科学的卫衣情感分析与建模

在消费升级与情感体验日益重视的时代背景下,服装的情感化设计成为制约消费者是否购买产品的关键。为了探索服装设计元素与消费者情感反应的关系,本文以卫衣作为研究载体,借助PAD情绪模型、眼动追踪和脑电波(EEG)技术,系统分析消费者对服装元素(款式、色彩、图案)的情感反应。结果表明,色彩搭配中单色和双色组合更易激发积极情绪,而三色较易引起消极情绪;图案大小和位置设计更易产生积极情绪;款式元素引起的情绪变化无明显规律;同时,以客观生理指标为输入,以主观情感指标为输出,构建服装情感识别模型;最后通过损失曲线、混淆矩阵、ROC曲线及误差的分析对情感识别模型进行了评估。研究表明,本文构建的服装情感识别模型准确率为98%,能高效准确识别服装情感类别,可以为更契合消费者情感需求的卫衣情感化定制提供参考。

Adaptive Object Tracking Discriminate Model for Multi-Camera Panorama Surveillance in Airport Apron

Autonomous intelligence plays a significant role in aviation security.Since most aviation accidents occur in the take-off and landing stage,accurate tracking of moving object in airport apron will be a vital approach to ensure the operation of the aircraft safely.In this study,an adaptive object tracking method based on a discriminant is proposed in multi-camera panorama surveillance of large-scale airport apron.Firstly,based on channels of color histogram,the pre-estimated object probability map is employed to reduce searching computation,and the optimization of the disturbance suppression options can make good resistance to similar areas around the object.Then the object score of probability map is obtained by the sliding window,and the candidate window with the highest probability map score is selected as the new object center.Thirdly,according to the new object location,the probability map is updated,the scale estimation function is adjusted to the size of real object.From qualitative and quantitative analysis,the comparison experiments are verified in representative video sequences,and our approach outperforms typical methods,such as distraction-aware online tracking,mean shift,variance ratio,and adaptive colour attributes.

Mean Flow–Storm Track Relationship and Rossby Wave Breaking in Two Types of El-Nino

The features of large-scale circulation, storm tracks and the dynamical relationship between them were examined by investigating Rossby wave breaking （RWB） processes associated with Eastern Pacific （EP） and Central Pacific （CP） E1-Nifio. During EP E1-Nino, the geopotential height anomaly at 500 hPa （Z500） exhibits a Pacific-North America （PNA） pattern. During CP EI-Nifio, the Z500 anomaly shows a north positive-south negative pattern over the North Pacific. The anomalous distributions of baroclinicity and storm track are consistent with those of upper-level zonal wind for both EP and CP EI-Nino, suggesting impacts of mean flow on storm track variability. Anticyclonic wave breaking （AWB） oczurs less frequently in EP EI-Nino years, while cyclonic wave breaking （CWB） occurs more frequently in CP EI-Nino years over the North Pacific sector. Outside the North Pacific, more CWB events occur over North America during EP Ei-NiNo. When AWB events occur less frequently over the North Pacific during EP EI-Nino, Z500 decreases locally and the zonal wind is strengthened （weakened） to the south （north）. This is because AWB events reflect a monopoie high anomaly at the centroid of breaking events. When CWB events occur more frequently over the North Pacific under CP EI-Nino conditions, and over North America under EP EI-Nino condition, Z500 increases （decreases） to the northeast （southwest）, since CWB events are related to a northeast-southwest dipole Z500 anomaly. The anomalous RWB events act to invigorate and reinforce the circulation anomalies over the North Pacific-North America region linked with the two types of EI-Nino.

Seasonal Variation Features of Western North Pacific Tropical Cyclone Tracks with Their Predictability

Analysis is done of monthly and seasonal variations as climatic features of the tracks from 1196 tropical cyclones originating in the western North Pacific over the period 1949 to 1980, followed by the investigation of 301 onland cyclone tracks over China mainland in terms of methodology for nonlinear system. Obtained by computing the accumulated distance distribution function of the tracks Cm (l) is the characteristic chaos quantity for the related dynamic systems and then the fractual dimensionality d = 4.86 and Kolmogorov entropy approximation K2 = 0.0164, thereby leading to the predictability time scale = 2.54 days. It is found that the reference path among the onland typhoon No.23 of 1971, or Bess in the international nomenclature. Our results could be of operational use as a kind of reference.

地震叠后和叠前混合驱动下的页岩油储层多尺度裂缝预测方法

不同尺度、不同类型的天然裂缝的系统性表征有利于识别优质储层、改进开发效果.建立可靠的多尺度裂缝模型是提高页岩油储层钻遇率的重要依据,其关键在于精细预测小尺度裂缝的空间分布,指导钻井钻进和压裂过程.然而,基于地震属性的传统裂缝预测方法只能各自突出单一尺度的断裂,不同裂缝属性的数学独立性给综合裂缝系统的识别带来严峻挑战.我们提出一套改进的全尺度裂缝系统评估方案,其关键在于通过优化的各向异性蚁群裂缝识别算法确定小尺度裂缝的发育概率,将小尺度裂缝的发育概率与传统蚂蚁追踪产生的大尺度断层的概率进行融合,得到的综合裂缝系统可以实现全尺度裂缝的感知.详细的属性分析过程表明,方位各向异性能够精确描述微观裂缝特征.基于此,我们将各向异性分析得到的裂缝密度和裂缝走向融入蚁群追踪裂缝的各个阶段,在提高裂缝密集区搜索强度的同时,还对小断距裂缝的发育方向实现了精准刻画.针对页岩油藏的应用案例证明,根据改进方案得到的全尺度裂缝系统能够同时表征大尺度断层、小裂缝和裂缝破碎带的分布情况.研究区的成像测井结果进一步验证了小尺度裂缝预测发育方向的准确性及可靠性,能够为页岩油水平井开发部署提供理论指导.

Improved chirp scaling algorithm integrated motion compensation for parallel-track bistatic synthetic aperture radar

To compensate motion errors of images from the parallel-track bistatic synthetic aperture radar（BiSAR）,an improved chirp scaling algorithm（CSA） is proposed.Since velocity vector of the moving aircrafts in the parallel-track BiSAR system can not remain invariant in an aperture,an actual aperture is divided into subapertures so that it is reasonable to assume that the aircrafts move with constant acceleration vector in a subaperture.Based on this model,an improved CSA is derived.The new phase factors incorporate three-dimensional acceleration and velocity.The motion compensation procedure is integrated into the CSA without additional operation required.The simulation results show that the presented algorithm can efficiently resolve motion compensation for parallel-track BiSAR.

共同富裕背景下中国中等收入群体规模测度及质量追踪

在推进共同富裕背景下,中国中等收入群体规模加速扩张,但基尼系数仍居高不下,收入分配不均衡问题依然严峻,中国中等收入群体的规模和质量需进一步探究。基于CFPS2010—2018年的调查数据,测度不同层面的中等收入群体规模变化及持续韧度,构建多维度质量评价指标体系,追踪规模扩张及韧度差距背后的质量差异,并实证检验其作用。研究表明:(1)城乡和不同受雇类型的群体间中等收入群体规模增速存在较大差距,中等收入群体的整体持续韧度较差;(2)中等收入群体规模扩张速度较快和持续韧度较好的群体,在财产、就业和人力资本方面的质量均具有较大优势,财产质量尤为明显;(3)财产、就业和人力资本方面的质量均会显著正向影响中等收入群体规模的增速和持续韧度,且财产质量的影响作用较大。研究结果不仅有助于明晰中等收入群体的规模与质量,也为促进中等收入群体的“提质扩容”和推进共同富裕进程提供政策启示。

基于核相关滤波的深空目标跟踪算法

随着天基红外探测器接近目标,目标在焦平面的成像会由小变大,在近距离时以面目标形式成像,随着距离的接近,目标的尺度变化会越来越剧烈。针对经典核相关滤波算法无法应对尺度变化及遮挡的问题,论文提出了一种融合尺度滤波的核相关滤波跟踪算法。在位置滤波器预测目标位置之后,由尺度滤波器计算尺度响应以解决目标尺度变化问题。针对目标跟踪过程中的遮挡问题,提出了一种遮挡判别依据,遮挡情况下停止更新模板以实现稳定、鲁棒的跟踪。通过对比实验表明,该算法可以有效地应对尺度变化及遮挡情况,且帧率可以达到120 FPS,满足实时要求。

2017-2021年北京足尺路面环道中心站沥青路面结构内部温度场监测数据集

温度是表征路面结构服役行为的重要参量,沥青路面的各类服役性能指标都与路面结构的温度状态密切相关,沥青路面结构内部温度场分布及变化规律具有重要的研究价值。本数据集包含北京足尺路面试验环道19种主沥青路面结构内部不同层位温度观测数据,温度数据采用埋设于路面各个结构层层底的温度传感器进行实时监测,并通过专用采集器采集后传输至数据中心进行存储,存储的信息包括数据采集时间、温度、传感器编号和位置。所采集的数据由专人定期下载和处理分析,以保证数据的完整和准确。本数据集可为沥青路面结构温度场的研究、沥青路面使用性能评价及沥青路面设计模型建立提供基础数据。

CRTSⅢ型板式轨道自适应多尺度损伤演变模型

为解决现有宏观模型无法准确反映CRTSⅢ型板式轨道在复杂荷载下的损伤演变和全细观模型耗费大量计算资源的问题,建立一种自适应多尺度模型。该模型结合宏观梁单元、二维实体单元和混凝土细观模型3种尺度,通过损伤指标对临界区域进行识别,在计算过程中,随着损伤的逐渐加剧,梁单元会转换为二维实体单元,二维实体单元会进一步细化为表征混凝土细观特性的骨料、砂浆与界面单元,使理想化为均质材料的混凝土逐渐被非均质多相材料所取代。通过对比叠合梁模型、二维实体模型与三维实体模型的计算结果,三者应力水平差异较小,验证了梁单元转换为二维实体单元的合理性。同时,基于自适应多尺度模型对自密实混凝土的四点弯曲试验进行数值模拟,与试验结果进行对比。该模型能够以较小的自由度模拟出试件的细观断裂过程,整个过程的荷载-位移曲线吻合度较好,验证了二维实体模型细化为混凝土细观模型的合理性。将自适应多尺度模型应用于CRTSⅢ型板式轨道结构力学特性分析,以较小的自由度研究轨道结构宏观和细观力学性能,能够预测轨道结构的潜在破坏,并反映出精确的应力水平和完整的细观破坏过程。该研究模型可进一步为轨道设计和维护提供重要依据,更好地评估和优化轨道结构的性能。

Improved chirp scaling algorithm for parallel-track bistatic SAR

The curvature factor of the parallel-track bistatic SAR is range dependent, even without variation of the effective velocity. Accounting for this new characteristic, a parallel-track chirp scaling algorithm （CSA） is derived, by introducing the method of removal of range walk （RRW） in the time domain. Using the RRW before the CSA, this method can reduce the varying range of the curvature factor, without increasing the computation load obviously. The azimuth dependence of the azimuth-FM rate, resulting from the RRW, is compensated by the nonlinear chirp scaling factor. Therefore, the algorithm is extended into stripmap imaging. The realization of the method is presented and is verified by the simulation results.

2017-2018年北京足尺环道中心站沥青路面力学响应观测数据集

结构力学响应数据是道路服役性能的重要指标,能够有效反映道路结构内部状态。对道路工程领域有着十分重要的研究意义,特别是连续稳定的长期实车加载响应数据更是国内外常规研究手段难以获得的高价值数据。本数据集包含北京大杜社公路材料腐蚀与工程安全国家野外科学观测研究站足尺路面环道中心站半刚性结构路段2017年至2018年的连续实车加载响应数据。本数据集由专用设备采集,通过抽检、冗余存储等手段确保数据质量,并且从采集、整理和存储均有专人负责。可为沥青路面结构的力学计算、沥青路面使用性能评价及沥青路面设计模型建立提供基础数据。

融合DSST-KCF算法的城市低空反无人机自动图像追踪系统

面向复杂城市低空环境中的“低、慢、小”无人机的精准快速跟踪难题,提出了融合DSST-KCF算法的反无人机自动追踪系统。该系统由双光图像采集单元和显示控制单元两部分组成;双光图像采集单元采集低空图像,然后由融合DSST-KCF算法对图像进行实时处理;融合DSST-KCF跟踪算法包括位置滤波器和尺度滤波器,其中位置滤波器采用循环矩阵形成的数据集进行训练,然后预测出下一帧目标位置;尺度滤波器从目标位置中心提取出33种不同尺度下的特征进行训练,然后确定跟踪框的尺寸;最后采用DSST-KCF-云台控制策略,使无人机保持在视场中心附近实现有效跟踪。在校园环境中,利用本系统对空中无人机进行实时跟踪测试,测试结果表明,改进后算法相比原KCF算法检测成功率平均提升了31.51%,跟踪精度平均提升了43%,适用于小型运动目标的跟踪。