多传感器模糊-概率交互作用的数据关联算法

本文基于估计理论和模糊系统理论,提出了一种多传感器多回波模糊－概率交互作用的数据关联滤波算法,以解决密集杂波干扰环境中多传感器跟踪机动目标的数据关联问题。模糊关联度和关联概率共同组成了各有效回波的加权系数,弥补了概率数据关联滤波方法（ＰＤＡＦ）的不足,提高了杂波环境中机动目标的跟踪性能。     

相控阵雷达多目标跟踪原理及数据关联算法研究

介绍了目标跟踪原理,并以多功能相控阵雷达为背景,研究了多目标跟踪数据关联过程.针对数据关联过程中量测起源的不确定性问题及概率数据关联算法(PDA)和联合概率数据关联算法(JPDA)的不足,给出了一种改进的概率数据关联算法(MPDA),该算法既不像PDA算法那样不考虑公共测量值对航迹的影响,也不像JPDA算法对所用的关联解进行搜索,而是重点分析了跟踪门交叠区域中的公共测量值对航迹更新的影响.蒙特卡罗仿真结果表明,该算法具有较小计算量及较好的实时跟踪性能,适于相控阵雷达的数据处理.     

一种基于模糊推理的JPDAF新方法

多目标跟踪中的数据关联一直是信息融合领域的难点和热点问题,针对杂波环境下多目标跟踪中的数据关联问题,提出了一种基于模糊推理的JPDAF新方法。该方法中,首先详细分析了杂波环境多目标观测数据的特点,定义了多目标环境下的标准化新息变量及新息的一阶微分变量;然后将其作为模糊推理的两个输入变量,通过设计合适的模糊隶属度函数和模糊推理规则,自适应计算目标观测的关联概率来代替传统联合概率数据关联滤波器（JPDAF）中的关联概率,实现对多个目标的有效跟踪。实验结果表明,提出方法的目标跟踪性能要好于传统的JPDAF和Fitzgerald’s方法,在实时性方面,提出方法也要远好于传统的JPDAF方法,接近Fitzgerald’s方法,能够有效对多目标进行关联跟踪。      

一种基于最大熵模糊聚类的数据关联算法

针对联合概率数据关联算法计算量上存在的组合爆炸问题,本文引入最大熵模糊聚类算法实现多目标的数据关联。使用最大熵模糊聚类得到的模糊隶属度表示目标与量测之间的联合互联概率;分析了公共回波对航迹更新的影响,对公共回波的权值进行衰减,对非公共回波的权值进行扩大,避免了航迹合并;此外根据差异因子的特性,给出剔除无效回波的方法,减少了计算量。仿真结果表明,与现有数据关联算法相比,新算法具有更优的跟踪效果。     

基于语言值模糊关系的关联规则挖掘算法

针对模糊关联规则挖掘时隶属函数的确定困难以及区间划分边界过硬等问题,提出了模糊关系关联规则挖掘算法,确定了关系等级数目和相邻等级相似度,将语言表达式(事务的属性值)根据模糊运算规则映射到标签集的各个等级上得到等级权值。在这些权值的基础上定义了模糊关系支持度和置信度,阐述了算法的详细步骤,最后给出了算法在服务信任领域挖掘关联规则的应用过程。     

Cheap Joint Probabilistic Data Association with Adaptive Neuro-Fuzzy Inference System State Filter for Tracking Multiple Targets in Cluttered Environment

The cheap joint probabilistic data association (CJPDA) with the adaptive neuro-fuzzy inference system state filter (ANFISSF) is presented for tracking multiple targets in the presence of low and high cluttered environments. The state update step of the CJPDA filter (CJPDAF) is realized with the ANFISSF instead of Kalman filter. The adaptive neuro-fuzzy inference system (ANFIS) has the advantages of expert knowledge of fuzzy inference system and learning capability of neural networks. A hybrid learning algorithm, which combines the least square method and the backpropagation algorithm, is used to identify the parameters of ANFIS. The tracks estimated by using the method proposed in this paper for different tracking scenarios are in very good agreement with the original tracks.     

Improved adaptive joint probabilistic data association filter formultiple targets angles tracking

The joint probabilistic data association filter that uses a modified algorithm for update time selection is presented. Simulation results illustrate the effectiveness, in terms of data association, of the proposed algorithm for multiple targets angles tracking     

Bearings-only maneuvering target tracking based on fuzzy clustering in a cluttered environment

This paper proposes a novel bearings-only maneuvering target tracking algorithm based on maximum entropy fuzzy clustering in a cluttered environment. In the proposed algorithm, the interacting multiple model (IMM) approach is used to solve the maneuvering problem of target, and the false alarms generated by clutter are accommodated through a probabilistic data association filter (PDAF). To reduce the computational load, the association probability is substituted by fuzzy membership degree provided by a modified version of fuzzy clustering algorithm based on maximum entropy principle, and the “maximum validation distance” is also defined based on the discrimination factor, which enables the algorithm eliminate invalid measurements. Moreover, to avoid the unobservability problem of passive target tracking, a nonlinear measurement model of multiple passive sensors is formulated. Finally, simulation results show that the proposed algorithm has advantages over the conventional IMM-PDAF algorithm in terms of simplicity and efficiency.     

多传感器多目标联合概率数据关联研究

联合概率数据关联(JPDA)算法对单传感器多目标跟踪是一种良好的算法,但对于多传感器密集多目标跟踪,则计算量剧增,数据关联成功率下降。因此,改进联合概率数据关联(AJPDA)算法对多传感器多目标量测进行同源划分及单一传感器测量数据转换,然后采用JPDA算法求解空间目标轨迹交叉时的数据关联。仿真结果表明,AJPDA算法提高了成功关联概率,降低了求解数据关联概率的难度,可以解决密集目标的正确跟踪问题。     

遗传模糊聚类算法在数据关联中的应用

针对传统数据关联算法存在计算量偏大或关联精度不高的问题,提出了一种利用遗传模糊聚类策略来求解数据关联问题的算法。该算法将多传感器多目标的数据关联问题看作是一类约束条件下的组合优化问题,先通过对同一时刻不同传感器提供的量测按照其相似性用遗传算法进行模糊聚类,再用聚类后的等效量测对各目标的状态进行估计。聚类方式的改进不仅增加了算法的局部寻优能力,有效地减少了计算的复杂度,而且还具备一定的野值剔除能力。仿真结果表明该算法关联精度较高,计算量适中,具有一定的工程应用价值。     

基于小波变换的快速多目标多帧多空间数据关联

该文提出一种基于小波变换的快速多目标多帧多空间数据关联算法。小波变换的引入把数据关联推广到多帧情况。该算法具有不依赖先验知识的特点,在复杂杂波环境下表现出较好的关联效果。算法的关联性能在多被动传感器多目标跟踪系统中进行了评估。仿真实验表明新算法在复杂杂波环境下表现出比联合概率数据关联等算法小的计算复杂度和好的关联效果。     

模糊观测数据的关联和目标跟踪

本文针对侦察预警网中观测数据具有不确定性和模糊性的特点,提出了一种数据关联和目标跟踪的方法。该方法采用模糊逻辑推理进行数据关联,加权最小二乘滤波器进行目标跟踪。文中给出了观测数据的模糊集合定义,推导出关联判断隶属度。仿真实验表明,对于模糊观测数据,本文的方法仍能有效地进行数据关联和目标跟踪。     

一种新的联合概率数据互联算法

点迹与航迹数据互联是多目标跟踪中迫切需要解决的问题。分析了目前解决数据互联问题的方法与最新研究成果,建立了一个多目标数据互联模型,提出了一种新的联合概率数据互联算法,最后给出了计算机仿真结果。     

被动传感器组网模糊综合贴近度的数据关联算法

针对被动传感器采样非周期且采样数据缺乏距离信息等特点,提出了一种用于解决目标航迹与传感器量测相关联的模糊综合贴近度的数据关联算法.由于被动传感器的量测没有距离信息且传感器探测范围小,本算法首先设置两个关联波门进行量测筛选;然后采用航向确定法得出航向角信息,并综合方位角、俯仰角信息,使用模糊综合的方法进行最终的关联,以解决关联错误率高的问题;最后使用扩展卡尔曼滤波进行目标状态与协方差的更新.实验结果证明了该算法方法的有效性.     

Extended-Hungarian-JPDA: exact single-frame stem cell tracking

The fields of bioinformatics and biotechnology rely on the collection, processing and analysis of huge numbers of biocellular images, including cell features such as cell size, shape, and motility. Thus, cell tracking is of crucial importance in the study of cell behaviour and in drug and disease research. Such a multitarget tracking is essentially an assignment problem, NP-hard, with the solution normally found in practice in a reduced hypothesis space. In this paper we introduce a novel approach to find the exact association solution over time for single-frame scan-back stem cell tracking. Our proposed method employs a class of linear programming optimization methods known as the Hungarian method to find the optimal joint probabilistic data association for nonlinear dynamics and non-Gaussian measurements. The proposed method, an optimal joint probabilistic data association approach, has been successfully applied to track hematopoietic stem cells.     

Fuzzy Peer Groups for Reducing Mixed Gaussian-Impulse Noise From Color Images

The peer group of an image pixel is a pixel similarity-based concept which has been successfully used to devise image denoising methods. However, since it is difficult to define the pixel similarity in a crisp way, we propose to represent this similarity in fuzzy terms. In this paper, we introduce the fuzzy peer group concept, which extends the peer group concept in the fuzzy setting. A fuzzy peer group will be defined as a fuzzy set that takes a peer group as support set and where the membership degree of each peer group member will be given by its fuzzy similarity with respect to the pixel under processing. The fuzzy peer group of each image pixel will be determined by means of a novel fuzzy logic-based procedure. We use the fuzzy peer group concept to design a two-step color image filter cascading a fuzzy rule-based switching impulse noise filter by a fuzzy average filtering over the fuzzy peer group. Both steps use the same fuzzy peer group, which leads to computational savings. The proposed filter is able to efficiently suppress both Gaussian noise and impulse noise, as well as mixed Gaussian-impulse noise. Experimental results are provided to show that the proposed filter achieves a promising performance.     

改进的K-Means算法在特征关联中的应用

特征关联是无源多传感器辐射源融合识别的一个关键步骤。特征关联是根据来源于同一辐射源的量测数据所具有的相似性,采用一定的算法和分配策略将多传感器获取的对多辐射源的量测值进行分类划分和关联判定,利用辐射源的特征信息来消除关联模糊。特征关联过程中一个重要环节就是分类算法的选取。K-Means算法是基于划分的聚类算法,已经广泛应用于诸多领域。改进了 K-Means算法,用灰关联度代替传统的距离度量定义了样本点间的距离,并对模拟产生的雷达辐射源特征参数样本集 Radar-da-tabase进行了分类。仿真结果表明,改进的K-Means算法提高了关联正确率,但消耗了更多时间。     

一种辐射源多特征数据关联的新方法

提出了一种辐射源多特征数据关联的新方法,对数据关联的相似性度量进行了讨论,给出了一种新的多特征参量统计相似性度量,并用谱系聚类法作数据关联,对所得关联结果进行了统计检验,计算机仿真结果证实了本方法的有效性。     

融合热释电红外传感器与视频监控器的多目标跟踪算法

现有基于热释电红外传感器的多目标跟踪系统在目标之间距离较近或者轨迹相交的情况下存在着误差较大的缺点.针对此缺点,提出了一种新型的基于热释电红外传感器与视频监测器协同工作的多目标跟踪方案.该方案可以充分利用两种传感器的优势,弥补在目标跟踪中的不足.算法采用最小二乘法利用热释电信息进行定位,并通过从图像或热释电传感器信号的幅频特性中提取特征信息来校正联合概率数据关联算法的关联矩阵,有效避免了错误关联.实验表明,该方案在多目标交叉情况下跟踪误差仅为其它算法的八分之一到四分之一.     

一种基于模糊聚类的PHD航迹维持算法

针对杂波环境下数量变化的多目标航迹关联问题,提出一种基于模糊聚类的PHD航迹维持算法.该算法充分利用多帧信息,对当前时刻状态进行多步预测,并根据惯性进行加权,然后利用模糊聚类求得当前估计属于每条航迹的隶属度,从而得到最终的航迹.与传统的估计与航迹关联算法不同,该算法在更新每条航迹信息时,不仅仅是简单地对相邻帧之间的对数似然比进行求和,而是通过加权聚类等操作综合考虑了多帧信息.实验结果表明,所提算法能够更好地保持目标航迹,即使在目标出现交叉的地方也能达到很好的跟踪精度,具有较强的鲁棒性和优良的航迹维持性能.