BeiDou B1I/B3I Signals Joint Tracking Algorithm Based on Kalman Filter

Dual-frequency satellite positioning receivers are widely used because they can eliminate ionospheric delay and solve the full-circumference ambiguity quickly.However,in traditional dual-frequency receivers,the relevance of dual-frequency signals are not considered,and,with no improvement imposed to the tracking loop,two independent tracking loops are used to achieve the tracking of dual-frequency signals.In this paper,the Bei Dou dual-frequency signals joint tracking algorithm based on Kalman filter is proposed for the tracking of Bei Dou B1I and B3I dual-frequency signals.Taking the relevance of B1I and B3I signals into consideration,the algorithm adds a Kalman filter between the phase detector and carrier loop filter of the traditional dual-frequency independent tracking loop.The output results of the phase detectors of the B1I and B3I branches are then combined and filtered by the Kalman filter,and the results are input to the carrier loop filters of the corresponding branches.Proved by experiments,the algorithm not only enables the loop to enter a stable tracking state quickly,but also reduces the noise bandwidth of the two loop filters by about 10 Hz with the same tracking performance obtained.

Joint tracking and classification of extended targets with complex shapes

This paper addresses the problem of joint tracking and classification(JTC) of a single extended target with a complex shape. To describe this complex shape, the spatial extent state is first modeled by star-convex shape via a random hypersurface model(RHM), and then used as feature information for target classification. The target state is modeled by two vectors to alleviate the influence of the high-dimensional state space and the severely nonlinear observation model on target state estimation, while the Euclidean distance metric of the normalized Fourier descriptors is applied to obtain the analytical solution of the updated class probability. Consequently, the resulting method is called the "JTC-RHM method." Besides, the proposed JTC-RHM is integrated into a Bernoulli filter framework to solve the JTC of a single extended target in the presence of detection uncertainty and clutter, resulting in a JTC-RHM-Ber filter. Specifically, the recursive expressions of this filter are derived. Simulations indicate that:(1) the proposed JTC-RHM method can classify the targets with complex shapes and similar sizes more correctly, compared with the JTC method based on the random matrix model,(2) the proposed method performs better in target state estimation than the star-convex RHM based extended target tracking method,(3) the proposed JTC-RHM-Ber filter has a promising performance in state detection and estimation, and can achieve target classification correctly.

Modified joint probabilistic data association with classification-aided for multitarget tracking

Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are similar for different closely spaced targets, there is ambiguity in using the kinematic information alone; the correct association probability will decrease in conventional joint probabilistic data association algorithm and track coalescence will occur easily. A modified algorithm of joint probabilistic data association with classification-aided is presented, which avoids track coalescence when tracking multiple neighboring targets. Firstly, an identification matrix is defined, which is used to simplify validation matrix to decrease computational complexity. Then, target class information is integrated into the data association process. Performance comparisons with and without the use of class information in JPDA are presented on multiple closely spaced maneuvering targets tracking problem. Simulation results quantify the benefits of classification-aided JPDA for improved multiple targets tracking, especially in the presence of association uncertainty in the kinematic measurement and target maneuvering. Simulation results indicate that the algorithm is valid.

Tracking multiple targets in MIMO radar via adaptive asymmetric joint diagonalization with deflation

In view of the low performance of adaptive asymmetric joint diagonalization（AAJD）, especially its failure in tracking high maneuvering targets, an adaptive asymmetric joint diagonalization with deflation（AAJDd） algorithm is proposed. The AAJDd algorithm improves performance by estimating the direction of departure（DOD） and direction of arrival（DOA） directly, avoiding the reuse of the previous moment information in the AAJD algorithm.On this basis, the idea of sequential estimation of the principal component is introduced to turn the matrix operation into a constant operation, reducing the amount of computation and speeding up the convergence. Meanwhile, the eigenvalue is obtained, which can be used to estimate the number of targets. Then, the estimation of signal parameters via rotational invariance technique（ESPRIT） algorithm is improved to realize the automatic matching and association of DOD and DOA. The simulation results show that the AAJDd algorithm has higher tracking performance than the AAJD algorithm, especially when the high maneuvering target is tracked. The efficiency of the proposed method is verified.

End-to-End Joint Multi-Object Detection and Tracking for Intelligent Transportation Systems

Environment perception is one of the most critical technology of intelligent transportation systems(ITS).Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking(MOT).However,most existing MOT algorithms follow the tracking-by-detection framework,which separates detection and tracking into two independent segments and limit the global efciency.Recently,a few algorithms have combined feature extraction into one network;however,the tracking portion continues to rely on data association,and requires com‑plex post-processing for life cycle management.Those methods do not combine detection and tracking efciently.This paper presents a novel network to realize joint multi-object detection and tracking in an end-to-end manner for ITS,named as global correlation network(GCNet).Unlike most object detection methods,GCNet introduces a global correlation layer for regression of absolute size and coordinates of bounding boxes,instead of ofsetting predictions.The pipeline of detection and tracking in GCNet is conceptually simple,and does not require compli‑cated tracking strategies such as non-maximum suppression and data association.GCNet was evaluated on a multivehicle tracking dataset,UA-DETRAC,demonstrating promising performance compared to state-of-the-art detectors and trackers.

Joint resource allocation scheme for target tracking in distributed MIMO radar systems

A joint resource allocation scheme concerned with the sensor subset,power and bandwidth for range-only target tracking in multiple-input multiple-output(MIMO)radar systems is proposed.By selecting an optimal subset of sensors with the predetermined size and implementing the power allocation and bandwidth strategies among them,this algorithm can help achieving a better performance within the same resource constraints.Firstly,the Bayesian Cramer-Rao bound(BCRB)is derived from it.Secondly,a criterion for minimizing the BCRB at the target location among all targets tracking in a certain range is derived.Thirdly,the optimization problem involved with three variable vectors is formulated,which can be simplified by deriving the relationship between the optimal power allocation vector and the bandwidth allocation vector.Then,the simplified optimization problem is solved by the cyclic minimization algorithm incorporated with the sequential parametric convex approximation(SPCA)algorithm.Finally,the validity of the proposed method is demonstrated with simulation results.

Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅰ)

Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Car-tesian space mainly through increasing the number of knots on the path and the number of the path′s segments, which results in the heavier online computational burden for the robot controller. Aiming at overcoming this drawback, the authors propose a new kind of real-time accurate hand path tracking and joint trajectory planning method. Through selecting some extra knots on the specified hand path by a certain rule and introducing a sinusoidal function to the joint displacement equation of each segment, this method can greatly raise the path tracking accuracy of robot′s hand and does not change the number of the path′s segments. It also does not increase markedly the computational burden of robot controller. The result of simulation indicates that this method is very effective, and has important value in increasing the application of industrial robots.

Trajectory tracking control of the bionic joint of the musculoskeletal leg mechanism

Pneumatic artificial muscles(PAMs) have properties similar to biological muscles,which are widely used in robotics as actuators.It is difficult to achieve high-precision position control for robotics system driven by PAMs.A 3-DOF musculoskeletal bionic leg mechanism is presented,which is driven by PAMs for quadruped robots.PAM is used to simulate the compliance of biological muscle.The kinematics of the leg swing is derived,and the foot desired trajectory is planned as the sinusoidal functions.The swing experiments of the musculoskeletal leg mechanism are conducted to analyse the extension and flexion of joints.A proportional integral derivative(PID) algorithm is presented for controlling the flexion/extension of the joint.The trajectory tracking results of joints and the PAM gas pressure are obtained.Experimental results show that the developed leg mechanism exhibits good biological properties.

基于特征增强的光学遥感视频多目标跟踪算法

高分辨率视频卫星的出现为遥感视频目标的检测和跟踪提供了重要数据源,在灾害检测、军事侦察等领域都有重要作用。针对遥感视频复杂地物背景下目标尺寸弱小、目标特征相似、云雾遮挡和背景噪声干扰导致目标误检、误跟、漏跟问题,提出基于特征增强的光学遥感视频多目标跟踪算法FE-MOT,设计了基于边缘特征增强的特征提取网络,在微小目标缺乏纹理特征的情况下更好地融合语义与空间特征,通过构建基于交叉熵损失和中心损失的Re-ID分支结构,提高了对具有相似特征的微小目标的可分性。在吉林一号遥感视频多目标跟踪数据集AIR-MOT上的实验结果表明,FE-MOT在原模型的基础上MOTA提高了14.28个百分点,IDF1提高了15.47个百分点,FN降低了24个百分点,对于遥感视频多目标跟踪中目标身份维持能力和跟踪稳定性有显著提升,在2个Tesla T4 GPU上的运行速度达到19.9FPS,满足实时运行的需要。

Passive target tracking with intermittent measurement based on random finite set

In the tracking problem for the maritime radiation source by a passive sensor,there are three main difficulties,i.e.,the poor observability of the radiation source,the detection uncertainty(false and missed detections)and the uncertainty of the target appearing/disappearing in the field of view.These difficulties can make the establishment or maintenance of the radiation source target track invalid.By incorporating the elevation information of the passive sensor into the automatic bearings-only tracking(BOT)and consolidating these uncertainties under the framework of random finite set(RFS),a novel approach for tracking maritime radiation source target with intermittent measurement was proposed.Under the RFS framework,the target state was represented as a set that can take on either an empty set or a singleton; meanwhile,the measurement uncertainty was modeled as a Bernoulli random finite set.Moreover,the elevation information of the sensor platform was introduced to ensure observability of passive measurements and obtain the unique target localization.Simulation experiments verify the validity of the proposed approach for tracking maritime radiation source and demonstrate the superiority of the proposed approach in comparison with the traditional integrated probabilistic data association(IPDA)method.The tracking performance under different conditions,particularly involving different existence probabilities and different appearance durations of the target,indicates that the method to solve our problem is robust and effective.

换填接缝后连续型无砟轨道温度应力控制措施研究

夏季高温作用下,连续型无砟轨道易发生层间离缝甚至热胀上拱失稳,严重影响高速列车运行安全。建立连续型无砟轨道温度应力计算模型,研究整体温升50℃时,不同植筋方案对换填接缝后连续型无砟轨道损伤和受力的影响。研究表明,(1)在4种植筋方案中,方案4层间界面损伤峰值为0.9,方案2层间界面损伤峰值为0.81,均未超过1。(2)4种植筋方案均表现为轨道板顶面纵向应力发生显著下降,而轨道板底面纵向应力显著上升,这表明接缝换填后,接缝附近轨道板顶面纵向应力得到释放,而轨道板底面应力大幅增加;方案3轨道板顶面应力降幅最大,为38.8%,最有利于释放轨道板温度应力;方案4轨道板底面应力增幅最大,达35.2%,对轨道板最为不利。

42号大号码道岔心轨不解锁问题研究

42号大号码道岔通常设置于高铁正线2条线路交汇处或线路所,而作为不同高铁线路的岔路口,线路所多为无人值守。当道岔出现故障后,维修人员处理时间相对较长,对行车影响较大。为此,沈阳高铁基础设施段经过近3年对京哈高速线、哈大高速线22组42号大号码道岔心轨不解锁问题进行深度分析,发现温度变化和结构因素是造成道岔心轨不解锁的主要原因。通过数据比对和研究试验,采取调整道岔框架尺寸、几何参数、道岔密贴力,以及改进外锁闭配件结构等措施,同时规范42号大号码道岔工电联合整治作业流程,可初步解决42号大号码道岔心轨不解锁问题,有益于保障高速铁路行车安全。

基于联合GLMB滤波器的可分辨群目标跟踪

针对联合广义标签多伯努利(joint generalized labeled multi-Bernoulli, J-GLMB)滤波算法中群目标之间距离较近、容易关联错误的问题,结合超图匹配(hypergraph matching, HGM)提出一种基于HGM-J-GLMB滤波器的可分辨群目标跟踪算法。首先,采用J-GLMB滤波器估计群内各目标的状态、数目及轨迹信息,并利用HGM结果提升量测与预测状态之间的关联性能。其次,通过图理论计算邻接矩阵,获取群结构信息和子群数目。随后,利用群结构信息估计协作噪声,进而校正目标的预测状态。最后,通过平滑算法改善滤波效果,并设置轨迹长度阈值,使其在平滑状态达到消除短轨迹的目的。仿真实验表明,所提算法在线性系统下能有效提升群目标跟踪性能。

温升作用下CRTSⅡ型板宽窄接缝受力及损伤分析

为研究宽窄接缝在温升作用下的受力和损伤,根据混凝土塑性损伤理论和内聚力理论,建立考虑新旧混凝土界面的宽窄接缝细部的有限元模型;计算不同温升条件下的宽窄接缝应力和损伤因子,并分析宽窄接缝强度和窄接缝宽度的影响.研究结果表明:窄接缝挤碎是一种渐变受压损伤,宽、窄接缝交界处断裂是一种脆性受拉损伤;与宽、窄接缝交界处断裂相比,窄接缝挤碎对结构受力影响更大;宽窄接缝尺寸不均匀导致宽、窄接缝交界处垂向受拉,这是宽窄接缝产生损伤的主要原因;提高宽窄接缝的混凝土强度可有效降低垂向拉应力和受拉损伤,但对纵向应力和受压损伤影响较小;为改善受力并降低损伤,建议宽窄接缝混凝土与轨道板等强,并且宽窄接缝上下等宽.

双轨正性暗示在发育性髋关节发育不良患者手术室等候期间的应用研究

目的 探讨双轨正性暗示在发育性髋关节发育不良(DDH)患者手术室等候期间的应用效果。方法 选取医院2021年8月-2023年10月拟行手术治疗的DDH患者108例,以随机数字表法分为对照组(54例)、观察组(54例);对照组于手术室等候期间行常规护理,研究组基于对照组行双轨正性暗示护理;对比两组生理应激反应、焦虑程度、心理等候时间及满意度。结果 观察组麻醉成功时心率(HR)、平均动脉压(MAP)较对照组低,差异有统计学意义(P<0.05);观察组入手术室时、术后1d焦虑自评量表(SAS)评分较对照组低,差异有统计学意义(P<0.05);观察组心理等候时间较对照组短,总满意度较对照组高,差异有统计学意义(P<0.05)。结论 DDH患者手术室等候期间采用双轨正性暗示护理可减轻生理应激反应,改善焦虑程度,缩短心理等候时间,提高满意度。

中低速磁浮梁轨一体轨道梁钢混接头试验研究

针对中低速磁浮分离式轨道梁建筑高度较大、无法考虑F轨刚度贡献等问题,提出了一种开孔钢板式梁轨一体轨道梁结构,并针对其钢-混结合部的静力性能开展足尺模型试验和有限元仿真计算分析.首先,介绍了梁轨一体轨道梁工程背景以及钢-混结合部的结构特征;其次,设计了钢-混结合部静载模型试验,测试F轨、钢连接件和混凝土等构件在各级荷载下的应力和位移;最后,建立了钢-混结合部实体有限元模型,并结合试验数据分析了钢-混结合部的受力性能、传力机理以及设计参数影响.研究结果表明:1)在1.50倍设计荷载内,钢-混结合部基本处于弹性状态,连接件承载力满足设计要求;荷载继续增大时,F轨的荷载-应力曲线表现出一定的非线性;5.47倍设计荷载下,混凝土梁体发生开裂破坏.2)F轨内外磁极位移均较小,钢-混结合部刚度较大;F轨内外磁极位移差在设计荷载下满足设计限值;1.58倍设计荷载下内外磁极位移差达到0.54 mm,开始超过位移差限值;表明钢混结合部刚度的富裕量小于强度,钢连接件应以刚度控制设计.3)在正常运营状态,磁浮列车荷载主要由钢连件的钢板承压传递,焊钉与开孔钢板传力比例较小;钢连接件中开孔直径、贯穿钢筋直径对传力影响较小,钢连接件腹板厚度增加使得钢混结合部处传力更加平顺.

低复杂度的大规模MIMO分布式信道估计

针对大规模多输入多输出(multiple-input multiple-output,MIMO)系统传统信道矩阵获取方式导频开销大、计算复杂度高的问题,提出了一种低复杂度的二阶段分布式信道估计方案。该方案的初始阶段在基站侧采用传统压缩感知算法恢复信道矩阵,第2阶段在用户端利用信道的时间相关性,将大规模MIMO的角度域信道分解为密集部分和稀疏部分,并分别估计以实现连续信道追踪。稀疏部分信道通过所提的分布式自适应弱匹配追踪(distributed adaptive weak matching pursuit,DAWMP)算法,利用子信道的联合稀疏性进行多维重建。相比于线性最小均方误差(linear minimum mean square error,LMMSE)算法,所提方案的信道分解策略有效减少了在用户端进行信道估计的计算复杂度。仿真结果表明,所提算法与经典压缩感知信道估计算法相比,计算复杂度降低了约33%,算法性能提升了约0.5 dB。

Vessel fusion tracking with a dual-frequency high-frequency surface wave radar and calibrated by an automatic identification system

High-frequency surface wave radar（HFSWR） and automatic identification system（AIS） are the two most important sensors used for vessel tracking.The HFSWR can be applied to tracking all vessels in a detection area,while the AIS is usually used to verify the information of cooperative vessels.Because of interference from sea clutter,employing single-frequency HFSWR for vessel tracking may obscure vessels located in the blind zones of Bragg peaks.Analyzing changes in the detection frequencies constitutes an effective method for addressing this deficiency.A solution consisting of vessel fusion tracking is proposed using dual-frequency HFSWR data calibrated by the AIS.Since different systematic biases exist between HFSWR frequency measurements and AIS measurements,AIS information is used to estimate and correct the HFSWR systematic biases at each frequency.First,AIS point measurements for cooperative vessels are associated with the HFSWR measurements using a JVC assignment algorithm.From the association results of the cooperative vessels,the systematic biases in the dualfrequency HFSWR data are estimated and corrected.Then,based on the corrected dual-frequency HFSWR data,the vessels are tracked using a dual-frequency fusion joint probabilistic data association（JPDA）-unscented Kalman filter（UKF） algorithm.Experimental results using real-life detection data show that the proposed method is efficient at tracking vessels in real time and can improve the tracking capability and accuracy compared with tracking processes involving single-frequency data.

横向贯通式中低速磁浮一体轨道梁钢-混结合部试验研究

为解决中低速磁浮分离式轨道梁存在的养护难、构件多,以及无法考虑F轨刚度贡献等问题,提出一种横向贯通式梁轨一体轨道梁结构,针对其钢-混结合部的静力性能开展有限元分析和足尺模型试验研究,并对关键设计参数进行参数分析。结果表明,在5倍设计荷载内,钢-混结合部基本处于弹性状态,承载力满足设计要求,且具备较高富裕量;竖向荷载主要通过钢板承压作用传递至混凝土梁体,焊钉对竖向荷载的传递作用较小;设计参数分析表明,适量提高钢连接件钢板厚度有利于竖向荷载的平顺传递。研究结果可以为梁轨一体轨道梁设计提供参考。