Lightning Nowcasting with an Algorithm of Thunderstorm Tracking Based on Lightning Location Data over the Beijing Area

A thunderstorm tracking algorithm is proposed to nowcast the possibility of lightning activity over an area of concern by using the total lightning data and neighborhood technique.The lightning radiation sources observed from the Beijing Lightning Network(BLNET)were used to obtain information about the thunderstorm cells,which are significantly valuable in real-time.The boundaries of thunderstorm cells were obtained through the neighborhood technique.After smoothing,these boundaries were used to track the movement of thunderstorms and then extrapolated to nowcast the lightning approaching in an area of concern.The algorithm can deliver creditable results prior to a thunderstorm arriving at the area of concern,with accuracies of 63%,80%,and 91%for lead times of 30,15,and 5 minutes,respectively.The real-time observations of total lightning appear to be significant for thunderstorm tracking and lightning nowcasting,as total lightning tracking could help to fill the observational gaps in radar reflectivity due to the attenuation by hills or other obstacles.The lightning data used in the algorithm performs well in tracking the active thunderstorm cells associated with lightning activities.

Use of Smartphones for Rapid Location Tracking in Mega Scale Soil Sampling

Conventional, grid-based sampling location tracking approach with GPS or topographic maps is time-consuming and inconvenient. Therefore, this study combined the freely available virtual/digital globe with recent advancements of smartphone geo-browsers to develop a new sampling location tracking approach. The sampling frame was developed with pre-uploaded point map formulated in GIS environment by combining land-use map and one-kilometer grid with center coordinates. The sampling location grid was uploaded to smartphone and each point was tracked with Google Map path finder using point ID (coded grid coordinate) when searching each sampling location. The suitability of the new approach was tested for soil sample collection from paddy lands distributed in 0.9 million hectares in Sri Lanka. The sampling locations could be reached conveniently with the help of Google path-finder voice direction guide and optional routes. The efficiency of new approach was found to be remarkably high, i.e., over 99% of the 9000 sampling points, which were spread across Sri Lanka having an area of 65,610 km2. All sampling points in the country could be covered with twelve member field investigation crew who were guided through smartphones uploaded with sampling point grid on six motorbikes within 60 days. The new sampling location tracking approach is effective in terms of cost, time, human resource requirements, thus can be adopted in large-scale soil/plant sampling frames with high accuracy.

Northward Shift in Landfall Locations of Tropical Cyclones over the Western North Pacific during the Last Four Decades

This study analyzes landfall locations of tropical cyclones(TCs)over the western North Pacific during 1979–2018.Results demonstrate that the landfall locations of TCs over this region have shifted northward during the last four decades,primarily due to the shift of landfalling TC tracks,with the decreasing/increasing proportion of westward/northward TC tracks.In particular,the northward shift of the landfalling TCs was not related to their formation locations,which have not markedly changed,whereas"no-landed"TCs have significantly shifted northward.TC movement was significantly and positively correlated to the zonal component of the steering flow,while the correlation between TC movement and the meridional component of the steering flow was relatively unobvious.The westward steering flow in the tropical central Pacific that occurred around the formation and early development of the westward TCs was significantly weakened,which was unfavorable for their westward movement,thereby,causing the higher proportions of northward moving tracks.This weakened westward flow was related to the northward shift of the subtropical high ridge,which was caused by significant weakening of the southern part of the subtropical high.The vertical wind shear,sea surface temperature,and convective available potential energy also showed that the northern region of the western North Pacific became more favorable for TC development,whereas the upper divergence,low-layer relative vorticity,and accumulated water vapor content were not obviously related to the northward shift of TCs.

Vision-based long-distance lane perception and front vehicle location for full autonomous vehicles on highway roads

A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.

An online fast multi-track locating algorithm for high-resolution single-event effect test platform

To improve the efficiency and accuracy of single-event effect(SEE)research at the Heavy Ion Research Facility at Lanzhou,Hi’Beam-SEE must precisely localize the position at which each heavy ion hitting the integrated circuit(IC)causes SEE.In this study,we propose a fast multi-track location(FML)method based on deep learning to locate the position of each particle track with high speed and accuracy.FML can process a vast amount of data supplied by Hi’Beam-SEE online,revealing sensitive areas in real time.FML is a slot-based object-centric encoder-decoder structure in which each slot can learn the location information of each track in the image.To make the method more accurate for real data,we designed an algorithm to generate a simulated dataset with a distribution similar to that of the real data,which was then used to train the model.Extensive comparison experiments demonstrated that the FML method,which has the best performance on simulated datasets,has high accuracy on real datasets as well.In particular,FML can reach 238 fps and a standard error of 1.6237μm.This study discusses the design and performance of FML.

Bearings-only fusion tracking for maneuvering target with wavelettransform in three dimensional space

A new fusion tracking algorithm is presented to track maneuvering target in three-dimensional (3D) space with bearings-only measurements. With the introduction of passive location and interacting multiple model (IMM) algorithm based on multirate model, the high-rate sequence measurements of two sensors are utilized. Simulation results show that the performance of tracking has been improved. The new algorithm removes the barrier of processing high-rate bearings-only measurements.

Services and Applications Based on Mobile User’s Location Detection and Prediction

Many wireless applications are deployed and available to customers via their mobile phones. Variety of these applications and services are based on determination of the current or future location of mobile user. Location based services (LBS) are one of the vital applications which are subdivided into two main categories: economical category and public category. Economic applications include mobile marketing, entertainment and tracking applications. Whereas, emergency cases, safety, traffic management, Muslims’ applications and public information applications are sort of public applications. The first part of the paper presents a new proposed system with developed procedure to recreate public and economic applications with high positioning accuracy and good authentication of users’ data. The developed system is created to enhance both location based services and network allocation resources within mobile network platform using either normal or GPS supported mobile equipment. The second part of the paper introduces future location prediction of mobile user dependent applications. New algorithm is developed depending on utilizing both intra-cell Movement Pattern algorithm (ICMP) [1] and hybrid uplink time Difference of Arrival and Assisted GPS technique (UTDOA_AGPS) [2]. It has been noticed that ICMP algorithm outperforms other future location prediction algorithms with high precision and within suitable time (less than 220) msec. However, UTDOA_AGPS guarantees high precession of mobile user independent of the surrounding environment. The proposed technique is used to enhance reliability and efficiency of location based services using cellular network platform.

A novel architecture for cargos location and safety in networked RFID

Using Networked RFID equipped in warehouse or supermarket distribution, Enterprise information system (EIS) can gather and deal with cargos information. Nevertheless, when cargos are in traffic, the Networked RFID can’t monitor the cargos any more as the products tagged aren’t within range of a reader. This paper proposes a solution framework which combines Networked RFID and GPS tracking, and then equip with this system in container to make the cargos monitored even if the cargos are in traffic. This solution can solve the accurate consignments, position tracking and advanced theft happening through drilling holes in container. In addition, customhouse and checkpoint can get an electronic shipment manifest rapidly and safely when a vehicle gets through a checkpoint.

Tracking data management using topology of moving object database system for moving object constrained trajectory in LBS application

Advances in wireless technologies and positioning technologies and spread of wireless devices, an interest in LBS(Location Based Service) is arising. To provide location based service, tracking data should have been stored in moving object database management system (called MODBMS) with proper policies and managed efficiently. So the methods which acquire the location information at regular time intervals then, store and manage have been studied. In this paper, we suggest tracking data management techniques using topology that is corresponding to the moving path of moving object. In our techniques, we update the MODBMS when moving object arrived at a street intersection or a curved road which is represented as the node in topology and predict the location at past and future with attribute of topology and linear function. In this technique, location data that are corresponding to the node in topology are stored, thus reduce the number of update and amount of data. Also in case predicting the location, because topology are used as well as existing location information, accuracy for prediction is increased than applying linear function or spline function.

Track Patterns of Landfalling and Coastal Tropical Cyclones in the Atlantic Basin, Their Relationship with the North Atlantic Oscillation (NAO), and the Potential Effect of Global Warming

Even though the degree of damage inflicted by North Atlantic tropical cyclones (TCs) is highly dependent upon track location and proximity to land, the spatial characteristics of TCs are generally understudied. We investigated the spatial relationships between landfall locations and track patterns of all Cape Verde-type landfalling and coastal TCs that have affected the continental coastline of the western Atlantic Basin by region for the period 1851-2008. The degree of recurvature for these TCs increases progressively from the Central America/Caribbean coast (CA) through the Gulf of Mexico (GOM), Florida peninsula (FLOR), and Atlantic (ATL) coasts. The date (month) of occurrence shows similar increases from the GOM through ATL. These patterns for landfall location, track pattern, and occurrence date generally follow the intra-seasonal movement and intensity variations of the Bermuda High (BH), as represented by increasing North Atlantic Oscillation (NAO) index values from CA through FLOR. Analysis suggests that the region of landfall is primarily controlled by two factors: the amplitude of track recurvature and the longitude at which recurvature begins to dominate track shape. Both of these important steering controls are predominantly influenced by the strength and position of the BH, with increasing strength and/or more northeasterly position of the BH progressively driving landfall from Central America through the Gulf of Mexico and the Atlantic seaboard out to the open sea. The paleorecord suggests that the latitudinal position of the BH exerts an important control over the location of hurricane landfall along the western North Atlantic on millennial time scales. This suggests that global warming may result in a northern shift in TC tracks and increased frequency of landfalls in northern locations.

Object Tracking and Tracing:Hidden Semi-Markov Model Based Probabilistic Location Determination

The enhancement of radio frequency identification(RFID) technology to track and trace objects has attracted a lot of attention from the healthcare and the supply chain industry.However,RFID systems do not always function reliably under complex and variable deployment environment.In many cases,RFID systems provide only probabilistic observations of object states.Thus,an approach to predict,record and track real world object states based upon probabilistic RFID observations is required.Hidden Markov model(HMM) has been used in the field of probabilistic location determination.But the inherent duration probability density of a state in HMM is exponential,which may be inappropriate for modeling of object location transitions.Hence,in this paper,we put forward a hidden semi-Markov model(HSMM) based approach for probabilistic location determination. We evaluated its performance comparing with that of the HMM-based approach.The results show that the HSMM-based approach provides a more accurate determination of real world object states based on observation data.

Influence of Qinghai-Xizang Plateau snow cover on interannual variability of Western North Pacific tropical cyclone tracks

Track density function(TDF)was computed for all Western North Pacific tropical cyclones(WNP TCs)tracks from 1950 to 2018,and the TDFs were further investigated using principal component analysis(PCA)to analyze their inter-annual spatial and temporal variability.Then,the relationships between each empirical orthogonal function(EOF)mode and the typhoon count,typhoon landfall count,track pattern,and the Qinghai-Xizang Plateau snow cover(QXPSC)were examined,and the possible physical mechanisms implied by the statistical relationship were explored.The results show the QXPSC significantly affected the surface-atmosphere heat exchange through snow cover(SC)level,then changed the East Asian summer monsoon regional circulation pattern,influenced the subtropical high-pressure system strength and location,and ultimately affected the WNP TCs track patterns and thus changed their landfall locations.

小兴安岭南麓野猪春冬季行为状态的生境选择

野猪(Sus scrofa)造成的人兽冲突是我国目前野生动物管理中急需解决的问题之一,但往往管理成本高,却效果甚微。了解野猪觅食、卧息等重要行为状态的生境选择规律,对科学管理策略的制定及避免人兽冲突极为重要。以小兴安岭南坡农林混交区域的野猪(5只雌性,8只雄性)为研究对象,基于其2019—2022年春冬季卫星定位项圈追踪数据,运用隐马尔科夫模型(HMM)识别野猪觅食、卧息和移动的三种行为状态,然后用步选择函数(SSF)研究这三种行为状态的生境选择。结果表明:野猪觅食、卧息和移动的生境需求不同,但均回避落叶针叶林,且性别差异明显,雌性野猪回避农田;地形是影响雌性野猪春季和雌雄野猪冬季三种行为状态生境选择的主要因子,地形和植被类型是影响雄性野猪春季三种行为状态生境选择的主要因子;雌性野猪,在春季,选择海拔高、坡度小的生境卧息、觅食及移动,且卧息和觅食均偏爱阴坡,冬季则选择海拔高,坡度大的阳坡卧息及觅食,偏爱在混交林和阳坡移动;雄性野猪,在春季,选择在混交林和坡度大的阴坡卧息,在混交林、落叶阔叶林和海拔低的区域觅食,在落叶阔叶林、常绿阔叶林内、海拔低、坡度小和距河流近的区域移动,在冬季,选择坡度大、海拔高、接近河流的阳坡卧息,在距河流近、坡度小的区域觅食,在常绿阔叶林、坡度小和距河流近的阳坡移动。本研究结果可为该区域的野猪毁田的预测和预警,捕获地点的选择等管控措施的制定提供依据和新思路。

六自由度机械手轨迹位置跟踪控制策略研究

针对六自由度机器人轨迹的位置控制,设计了带有滑动扰动观测器的滑模控制方法(SMCSPO)和积分滑模控制(ISMC)两种不同的控制方法。SMCSPO对由非线性、参数不确定性和外部干扰组成的扰动具有较强的鲁棒性,但不易辨识系统参数。ISMC在多自由度机器人的位置控制方面,不需要推导多自由度机器人的运动方程或进行系统辨识,能够通过控制输入的开关增益实现了扰动的补偿。与SMCSPO相比,ISMC具有较高的轨迹位置跟踪精度。两种控制方法均在MATLAB/Simulink中进行了模拟仿真,结果表明ISMC的跟踪误差均小于SMCSPO的跟踪误差,且具有较好的收敛速度。

一种融合时差频差和测向的运动目标跟踪方法

传统的星载无源定位系统对空中辐射源定位求解通常采用假设高程的方法,高程假设误差将对定位跟踪精度造成较大影响。为实现未知高程运动辐射源的高精度定位跟踪,针对异轨三星构型的无源定位系统,提出了一种基于时差、频差和二维测向融合的迭代扩展卡尔曼滤波(Iterative Extended Kalman Filter,IEKF)跟踪方法。在WGS-84坐标系下建立了状态方程和观测方程,并采用IEKF方法对目标状态进行估计。仿真结果表明,该方法可对未知高程的运动目标进行高精度状态估计,典型仿真场景下的目标高程估计精度达到百米量级,相对于已有方法收敛时间更短,并且在卫星覆盖范围内具有更大的高精度定位跟踪区域。

基于亚像素定位的图像边缘检测策略研究

针对图像处理与计算机视觉技术中低对比度、边缘模糊图像的边缘检测问题,参考局部极值与梯度方向两种因素,并结合图像边缘方向趋势,提出了一种单像素边缘跟踪策略。相较于应用广泛的Canny算法,该跟踪策略无需设置全局阈值,实现方式更为简洁、高效;提取的图像边缘连续、平滑、完整,并有效地减少了图像边缘的冗余像素,进而提升了图像后续处理的效率;边缘跟踪方向抗干扰性强,具有较强的鲁棒性。为了减小检测的图像边缘与真实图像边缘之间的偏差、提高图像边缘检测的精度,参考边缘像素点的相邻区域灰度,以边缘像素点的梯度分布为依据对该像素点进行亚像素定位。经实验验证,经过亚像素优化的图像边缘检测策略可用于检测边缘模糊、对比度低的图像,检测的图像边缘完整、连续且平滑。该策略有效地消除了程序运算中引入的截断误差,提升了图像边缘检测精度,且适用于亮度5~100000 lx的高动态成像场景中。

基于定位收缩法的局部阴影条件下光伏最大功率点跟踪

光伏最大功率点跟踪是提高光伏发电效率的重要手段。在局部阴影条件下,光伏阵列的特性曲线呈现多峰形状,常规的传统算法容易陷入局部最优。如何在局部阴影条件下找到全局最大功率点(global maximum power point,GMPP)至关重要。提出了一种定位收缩法(locate and shrink algorithm,LSA),采用收缩边界的思想使得边界逐渐收缩到GMPP。LSA第一阶段提出了一种峰的定位方法,通过自适应采样结合I-V特性曲线能够定位主要峰的占空比范围。定位法能够与其他单峰算法结合,具有较强的扩展性。第二阶段提出了一种基于三点准则的收缩法,能够在单峰范围内通过收缩边界快速找到峰值点,并且具有很强的环境适应性。将LSA与多个算法进行仿真和硬件实验对比,结果表明LSA在跟踪速度、跟踪精度和稳态振荡方面有着明显优势。

采摘机器人的定位和轨迹预测算法研究——基于大数据技术

建立了采摘机器人运动学模型,并设计了基于深度神经网络和大数据技术的多元信息融合模型,实现了对采摘机器人的定位和轨迹预测。仿真结果表明:模型对采摘机器人的预测精度较高,误差在允许的范围内,对采摘机器人定位和轨迹预测具有一定参考意义。

利用扣件位置关系定位图像边缘处不完整扣件的方法

扣件定位在扣件检测过程中具有至关重要的作用,其准确性直接关系到后续检测的可靠性。在使用线阵相机采集扣件图像时,扣件在图像中的位置并不固定,将会导致同一扣件可能横跨连续的2张图像,并在图像边缘处被截断。本文将这些被截断的扣件称为不完整扣件,其上半部分和下半部分分别出现在2张连续图像边缘处。不完整扣件由于形状缺失,难以定位其位置,从而降低了扣件检测的可靠性。为解决上述问题,本文提出一种利用扣件位置关系定位不完整扣件的方法。首先,通过像素统计法定位原始图像中的钢轨位置,并基于先验知识获得包含钢轨和扣件的原始图像子图,本文称所获得子图像为条形钢轨图;然后,拼接条形钢轨图,保证图像内存在多对扣件;接着,利用模板匹配获得与扣件模板最相似的位置,再利用该位置信息以及扣件之间的位置关系判断图像中是否存在不完整扣件并获取不完整扣件位置信息;最后,将2部分不完整扣件拼合为一张完整的扣件图像。研究结果表明,本文提出的方法能够100%定位采集图像中115对不完整扣件图像。研究结果具有实际工程价值,能够有效地解决图像边缘处不完整扣件定位问题,提高扣件检测的可靠性。

基于强化学习的激光导航无人车路径跟踪控制

针对智能仓储无人车运动轨迹控制精度的问题,提出了一种基于强化学习的激光导航无人车路径跟踪控制算法。建立了智能仓储无人车的数学模型,设计了一种激光导航定位算法,提出了一种Actor-Critic强化学习路径跟踪算法,最终实现对无人车路径跟踪的高精度控制。通过对比仿真验证了设计的路径跟踪算法具有更优的控制效果和更高的控制精度,最大路径跟踪误差仅为0.3 m,最大x坐标跟踪误差仅为0.1 m,最大y坐标跟踪误差仅为0.29 m,大幅提高了对仓储无人车运动轨迹的跟踪精度。