基于综合相关判别的无源航迹关联算法

航迹关联是多目标航迹处理中的重要问题,综合利用无源传感器获取的其他信息是改善航迹关联的重要途径。利用辐射源航迹得到正确的目标关联航迹较困难,因此,提出了一种辐射源航迹自关联和目标平台航迹互关联的两步关联综合相关判别算法,在充分运用无源传感器获取到的角度信息的同时,利用丰富的综合属性信息对航迹进行关联。仿真结果表明,该算法能够有效解决多无源传感器的航迹关联问题,并且有较高的关联正确概率。     

基于多维分配和灰色理论的航迹关联算法

针对目前应用于分布式多传感器系统中航迹关联算法只能解决两局部节点航迹相关的问题,该文提出了一种基于多维分配的灰色航迹关联算法。该算法运用灰色理论获取各传感器航迹间的灰色关联度,以此关联度为多传感器系统的全局统计量构造多维灰色关联度矩阵,并根据此矩阵形成的多维分配问题的解获得各传感器航迹间的关联结果。仿真结果表明,在密集目标环境下和/或交叉、分岔及机动航迹较多的场合,该算法的性能明显优于传统方法,其正确关联率较灰色航迹关联算法提高了大约8.8%。     

基于融合邻接矩阵的多时态局域电网拓扑分析技术

针对传统邻接矩阵在进行多个节点的电网拓扑分析时存在矩阵计算量大、效率偏低且难以满足实时性要求等问题,文中提出了一种基于融合邻接矩阵的多时态局域电网拓扑分析技术。该技术在将电网模型抽象为映射图的基础上,建立与映射图对应的邻接矩阵,通过该矩阵计算相应的全连通矩阵。同时为了提高计算效率,还在计算全连通矩阵的过程中引入了准平方的思想,并在每计算出一个新的连通矩阵元素后,使用该元素更新老元素及其对称位置元素的值,以得到全连通矩阵,从而完成电网拓扑中的母线与电气岛分析。测试结果表明,在相同的实验条件下,所提方法的运算次数相较于其他算法减少了60%以上,且运算时间大幅缩短。     

基于区间数及DS证据理论的多传感器航迹关联方法

针对多传感器航迹关联问题,提出了一种基于区间数和DS(Dempster/Shafer)证据理论的解决方法。该方法通过分析误差对参数测量的影响,构建传感器探测目标参数真实值区间数,通过计算区间数之间的相对支持度,获取目标参数对于航迹相关的支持程度,基于DS证据理论将不同参数对航迹相关的支持程度进行合成,以此解决航迹关联问题。实例表明,该方法能够较好地解决多传感器航迹关联问题。     

基于类型辅助灰色关联度的红外传感器和ESM航迹关联算法

红外传感器与ESM是军事多传感器信息融合系统的重要组成部分。针对二者之间的航迹关联问题,提出了一种综合利用灰色关联度和类型信息的航迹关联算法。该算法将红外传感器和ESM的航迹序列看作离散时间函数,通过计算各航迹间的灰色B型关联度,形成灰色关联矩阵;通过归一化信息熵判断目标和辐射源类型信息的有效性,结合目标和辐射源的配属关系并利用VBS理论将不同框架下的证据转换到相同框架下,然后采用Jousselme距离度量证据的一致性,从而形成类型关联矩阵;最后,综合利用灰色关联矩阵和类型关联矩阵进行航迹关联判别。仿真结果表明,当可用数据点较多时,基于灰色关联度的航迹关联算法具有较高的关联正确率;当传感器分类效果较好时,基于类型辅助灰色关联度的航迹关联算法具有更好的关联性能。      

基于JVC的紧凑型地波雷达海上目标点迹-航迹最优关联方法

紧凑型地波雷达由于接收天线阵列孔径减小导致对海上目标的定位精度低,在多目标跟踪算法中采用序贯式的点迹-航迹关联方式易发生误关联导致航迹断裂、误跟踪等问题。对此,该文将多目标点迹-航迹关联转化为最优分配问题,提出一种基于JVC算法的多目标点迹-航迹最优关联方法。对于关联波门重叠区域内存在公共候选点迹的多条航迹,首先以雷达获取的目标多普勒速度、距离与方位角作为目标特征参数,利用最小代价函数确定公共候选点迹与所有航迹之间的相似度,得到关联代价矩阵;然后以总关联代价最小化作为优化准则,采用JVC算法求解得到最优的点迹-航迹关联结果。利用仿真与实测目标数据开展了点迹-航迹关联实验,并与序贯最近邻关联方法的关联结果进行了对比。实验结果表明:采用该文所提方法跟踪得到的航迹时长明显优于序贯最近邻关联方法的结果,解决了序贯式关联因关联错误导致的航迹断裂、误跟踪等问题,提高了航迹跟踪的连续性。     

航迹关联和相对系统误差估计

航迹关联是多传感器多目标跟踪系统中的关键问题。当存在系统误差时航迹关联问题变得更复杂。该文将最优Bayes联合决策估计(JDE)法应用于存在系统误差的航迹关联中,并提出了简化的JDE法。最优Bayes JDE,通过在航迹关联时考虑传感器相对系统误差的估计误差,在相对系统误差估计时考虑航迹关联误差,来提高航迹关联的正确率和相对系统误差的估计精度。提出的简化JDE法可减少了计算量,其性能比最优JDE稍差。并给出了matlab仿真结果来验证方法的有效性。     

基于JVC的紧凑型地波雷达海上目标点迹-航迹最优关联方法

紧凑型地波雷达由于接收天线阵列孔径减小导致对海上目标的定位精度低,在多目标跟踪算法中采用序贯式的点迹-航迹关联方式易发生误关联导致航迹断裂、误跟踪等问题.对此,该文将多目标点迹-航迹关联转化为最优分配问题,提出一种基于JVC算法的多目标点迹-航迹最优关联方法.对于关联波门重叠区域内存在公共候选点迹的多条航迹,首先以雷达获取的目标多普勒速度、距离与方位角作为目标特征参数,利用最小代价函数确定公共候选点迹与所有航迹之间的相似度,得到关联代价矩阵;然后以总关联代价最小化作为优化准则,采用JVC算法求解得到最优的点迹-航迹关联结果.利用仿真与实测目标数据开展了点迹-航迹关联实验,并与序贯最近邻关联方法的关联结果进行了对比.实验结果表明:采用该文所提方法跟踪得到的航迹时长明显优于序贯最近邻关联方法的结果,解决了序贯式关联因关联错误导致的航迹断裂、误跟踪等问题,提高了航迹跟踪的连续性.     

雷达

TN95 2007011721人工神经网络在航迹关联中的应用/张池平,崔平远,张英俊(哈尔滨工业大学理学院)//黑龙江大学(自然科学学报).―2006,23(1).―38～41.针对在密集目标环境下和运动出现交叉或分岔等难于处理的情况,将导致较多的错、漏相关航迹的问题,提出一种利用神经网络进行航迹关联的方法。该方法有效地应用了神经网络的泛化能力以及自组织自适应的学习功能,且通过对网络输入结点的设计,能够很好地解决复杂航迹关联问题。仿真实验验证了该算法在多传感器系统的航迹关联问题中的有效性。图5表0参8     

基于改进盖尔-沙普利算法的自动识别系统与双频地波雷达断裂航迹关联

高频地波雷达(HFSWR)可以实现大范围海上船只目标的连续探测,但是海杂波等干扰因素的影响容易造成跟踪航迹的断裂。目前关于地波雷达航迹关联的研究中,通常忽略了航迹断裂的情况,将航迹关联视为二分图匹配问题,这会导致可能将单一目标的断裂航迹判断为多个目标,从而引起目标的误关联。针对上述情况,该文结合模糊综合评判和迭代搜索算法,首次将盖尔-沙普利(GS)算法引入航迹关联领域,并且对其进行改进以满足航迹断裂时的多对多航迹关联情况,提出了改进的盖尔-沙普利(IGS)算法。在该算法中,通过计算航迹之间的模糊综合评判值来得到航迹之间的倾向度序列,再由迭代搜索对航迹进行聚类以获得航迹集群,最后将航迹集群及倾向度序列输入盖尔-沙普利算法来进行数轮博弈以给出关联结果。利用双频率高频地波雷达和船只自动识别系统(AIS)的仿真数据与实测数据进行实验测试,实验结果表明：所提出的算法解决了在航迹断裂情况下的多传感器航迹关联问题,且在密集区域的航迹关联效果优于传统算法。     

Distributed fusion architectures and algorithms for target tracking

Modern surveillance systems often utilize multiple physically distributed sensors of different types to provide complementary and overlapping coverage on targets. In order to generate target tracks and estimates, the sensor data need to be fused. While a centralized processing approach is theoretically optimal, there are significant advantages in distributing the fusion operations over multiple processing nodes. This paper discusses architectures for distributed fusion, whereby each node processes the data from its own set of sensors and communicates with other nodes to improve on the estimates, The information graph is introduced as a way of modeling information flow in distributed fusion systems and for developing algorithms. Fusion for target tracking involves two main operations: estimation and association. Distributed estimation algorithms based on the information graph are presented for arbitrary fusion architectures and related to linear and nonlinear distributed estimation results. The distributed data association problem is discussed in terms of track-to-track association likelihoods. Distributed versions of two popular tracking approaches (joint probabilistic data association and multiple hypothesis tracking) are then presented, and examples of applications are given.     

Enumeration of minimal cutsets from matrix representation of directed/undirected networks

This paper describes an algorithm for finding the minimal cutsets between a specified source and terminal nodes of directed/undirected networks. Adjacent nodes of a source node/merged node are determined by the collection of node numbers of columns corresponding to non-zero elements of the first row of the adjacency matrix to form the reduced adjacency matrix (RAM) corresponding to merged nodes. Connectivity of RAM has been checked to obtain the minimal cutsets.     

分布式紧耦合虚拟专用网可靠性计算方法

为了评估构建在互联网络基础上,具有多个服务质量约束要求的分布式紧耦合虚拟专用网可靠性能,该文提出一套可靠性指标计算方法。首先,在赋有权值参数的互联网络中,计算出所有满足约束条件的分布式紧耦合节点之间路由。然后,根据这些路由建立满足服务质量要求的网络邻接矩阵,对邻接矩阵进行分解与整合等变换,求得满足约束条件的不交化网络状态集。最后,根据不交化网络状态集得到可靠性指标的计算式,进而完成可靠性指标计算。由于所有过程都实现了代数化或逻辑代数化计算,所以易于计算机编程实现。论述了算法关键环节的正确性。通过算例、实验以及与传统算法结果比较等方式,说明新算法能够非常贴切地反映出分布式紧耦合虚拟专用网的可靠性。     

An Energy Efficient Barrier Coverage Algorithm for Wireless Sensor Networks

Intrusion detection is one of the most important applications of wireless sensor networks. When mobile objects are entering into the boundary of a sensor field or are moving cross the sensor field, they should be detected by the scattered sensor nodes before they pierce through the field of sensor (barrier coverage). In this paper, we propose an energy efficient scheduling method based on learning automata, in which each node is equipped with a learning automaton, which helps the node to select best node to guarantee barrier coverage, at any given time. To apply our method, we used coverage graph of deployed networks and learning automata of each node operates based on nodes that located in adjacency of current node. Our algorithm tries to select minimum number of required nodes to monitor barriers in deployed network. To investigate the efficiency of the proposed barrier coverage algorithm several computer simulation experiments are conducted. Numerical results show the superiority of the proposed method over the existing methods in term of the network lifetime and our proposed algorithm can operate very close to optimal method.     

基于改进的Floyd算法求节点间所有最短路径

网络节点间的最短路径可能不止一条.首先运用加速的Floyd算法得到最短路径长度矩阵;然后根据最短路径长度矩阵构造各个节点的到达距离矩阵,用来与最短路径长度矩阵进行对比;最后得到每个节点的后继节点,进而得到所有最短路径.计算机仿真验证了该算法的高效性.     

A Distributed Algorithm for Minimum Weight Directed Spanning Trees

A distributed algorithm is presented for constructing minimum weight directed spanning trees (arborescences), each with a distinct root node, in a strongly connected directed graph. A processor exists at each node. Given the weights and origins of the edges incoming to their nodes, the processors follow the algorithm and exchange messages with their neighbors until all arborescences are constructed. The amount of information exchanged and the time to completion areO(|N|^{2}).     

负载约束的C-V2X车辆缓存节点选择算法

为了解决城市环境下的C-V2X车辆拓扑高度动态化且车辆节点负载能力有限的问题,提高车辆缓存的利用率,减轻基站负荷,提出了负载约束下的车辆缓存节点选择算法。首先,通过定义链路稳定性度量,构建预测权重邻接矩阵,微观地描述车辆拓扑关系;其次,在负载约束和无重叠覆盖约束下构建目标函数,以最少的缓存节点实现全覆盖且最大化簇平均链路权重;最后,引入贪婪思想并合理定义节点状态,求解负载约束下车辆拓扑的最小支配集,并择优选择服务邻居节点。仿真结果表明,所提算法在缓存节点个数和簇平均链路权重均值方面接近全局最优,其重复应答率恒为零,请求应答率可达理论上界并可有效提高缓存源应答次数。     

Mobility prediction in mobile ad hoc networks using a lightweight genetic algorithm

A mobile ad hoc network is a collection of wireless mobile nodes creating a network without using any existing infrastructure. Much research has been carried out to find out an optimal routing protocol for the successful transmission of data in this network. The main hindrance is the mobility of the network. If the mobility pattern of the network can be predicted, it will help in improving the QoS of the network. This paper discusses a novel approach to mobility prediction using movement history and existing concepts of genetic algorithms, to improve the MANET routing algorithms. The proposed lightweight genetic algorithm performs outlier removal on the basis of heuristics and parent selection using the weighted roulette wheel algorithm. After performing the genetic operations a node to node adjacency matrix is obtained from which the predicted direction of each node is calculated using force directed graphs and vector calculations. The technique proposes a new approach to mobility prediction which does not depend on probabilistic methods and which is completely based on genetic algorithms.     

A site entropy rate and degree centrality based algorithm for image co-segmentation

In this paper, we propose a graph based algorithm that efficiently segments common objects from multiple images. We first generate a number of object proposals from each image. Then, an undirected graph is constructed based on proposal similarities and co-saliency maps. Two different methods are followed to extract the proposals containing common objects. They are: (1) degree centrality of nodes obtained after graph thresholding and (2) site entropy rate of nodes calculated on the stationary distribution of Markov chain constructed on the graph. Finally, we obtain the co-segmented image region by selecting the more salient of the object proposals obtained by the two methods, for each image. Multiple instances of the common object are also segmented efficiently. The proposed method has been compared with many existing co-segmentation methods on three standard co-segmentation datasets. Experimental results show its effectiveness in co-segmentation, with larger IoU values as compared to other co-segmentation methods.     

Generation of directed circuits in a directed graph

A new matrix algorithm has been presented to generate all directed circuits in a given directed graph. The method is based on multiplication of the modified adjacency matrix of the graph by itself according to some modified rules of matrix multiplication.