共查询到17条相似文献,搜索用时 171 毫秒
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多传感器多目标跟踪中的数据关联问题是目标跟踪领域中的难点及核心。若传感器是只有角度量测的被动传感器,关联问题则变得更为复杂。针对纯方位多被动传感器系统的多目标跟踪问题,提出了一种基于高斯-厄密特滤波的动态多维分配方法。首先建立了直角坐标系下多被动传感器的高斯-厄密特滤波模型;在该模型的基础上,采用多维分配问题的思想,直接建立各传感器角度量测与目标角度预测值的候选关联组合,并将其进行动态地分配,提高了关联效率。仿真实验表明,该方法可以实时、高效地解决多被动传感器系统中的数据关联问题,并且能够对多目标进行稳定的跟踪。 相似文献
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基于多维分配和灰色理论的航迹关联算法 总被引:5,自引:0,他引:5
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%。 相似文献
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针对主被动传感器异地配置情况,利用视线测量转换过程,对主被动联合探测的数据关联算法进行了改进:首先,计算视线垂足至主动传感器的距离,以方位测量与该距离之差(测量差)构造新的统计量,通过视线间距以及测量差两个统计量检验初选出候选关联集;接着,主被动视线交叉将不完整的被动测量补充为完整测量,用精度加权法实现多角度测量之间的融合,得到候选集的定位点估计,计算各定位点与目标的关联概率;然后,以视线间距和测量差构造测量距离,利用测量距离之和表征关联集内部各视线的紧密度,给出视线关联度;最后,用视线关联度修正关联概率,最大值搜索正确关联组合。仿真实验结果验证了算法的有效性。 相似文献
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该文针对无源测向交叉定位系统提出了基于多维指派算法的被动多目标跟踪方案。该方案是将三维空间的基准线最小代价算法与动态2D指派算法相结合。该方案的特点是:三维空间的基准线最小代价算法是一种快速数据关联算法,它能够快速削减候选关联集合并简化关联代价的计算,完成航迹起始任务;动态2D指派算法则能够简单而准确地实现观测与航迹的关联。仿真结果证明该方案可以有效地完成无源测向交叉定位系统中的多目标跟踪任务。 相似文献
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杂波环境下多被动传感器单目标跟踪算法 总被引:1,自引:1,他引:0
由于被动传感器只能获得目标的角度量测,因此杂波环境下基于被动传感器的关联问题较主动传感器更为困难。针对杂波环境下纯方位多被动传感器系统的单目标跟踪问题,提出了一种基于扩展卡尔曼滤波的模糊综合贴近度关联跟踪方法。该方法采用直角坐标系下多被动传感器系统的扩展卡尔曼滤波对目标进行跟踪。首先利用目标航迹的预测信息,针对每个传感器建立确认跟踪门;在获得候选关联组合后,直接利用角度信息建立各候选关联组合与角度预测值间的模糊综合贴近度,通过在所获得的全部模糊综合贴近度中寻求最优解完成量测到航迹的关联。仿真实验表明,该方法可以有效地解决杂波环境下多被动传感器系统的单目标跟踪问题。 相似文献
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Tracking and Coordination of Multiple Agents Using Sensor Networks: System Design, Algorithms and Experiments 总被引:2,自引:0,他引:2
Songhwai Oh Schenato L. Chen P. Sastry S. 《Proceedings of the IEEE. Institute of Electrical and Electronics Engineers》2007,95(1):234-254
This paper considers the problem of pursuit evasion games (PEGs), where the objective of a group of pursuers is to chase and capture a group of evaders in minimum time with the aid of a sensor network. The main challenge in developing a real-time control system using sensor networks is the inconsistency in sensor measurements due to packet loss, communication delay, and false detections. We address this challenge by developing a real-time hierarchical control system, named LochNess, which decouples the estimation of evader states from the control of pursuers via multiple layers of data fusion. The multiple layers of data fusion convert noisy, inconsistent, and bursty sensor measurements into a consistent set of fused measurements. Three novel algorithms are developed for LochNess: multisensor fusion, hierarchical multitarget tracking, and multiagent coordination algorithms. The multisensor fusion algorithm converts correlated sensor measurements into position estimates, the hierarchical multitarget tracking algorithm based on Markov chain Monte Carlo data association (MCMCDA) tracks an unknown number of targets, and the multiagent coordination algorithm coordinates pursuers to chase and capture evaders using robust minimum-time control. The control system LochNess is evaluated in simulation and successfully demonstrated using a large-scale outdoor sensor network deployment 相似文献
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LIU Hu ZHU Li-li ZHANG Huan-chun 《中国电子科技》2006,4(1):12-17
For data association in multisensor and multitarget tracking, a novel parallel algorithm is developed to improve the efficiency and real-time performance of FGAs-based algorithm. One Cluster of Workstation (COW) with Message Passing Interface (MPI) is built. The proposed Multi-Deme Parallel FGA (MDPFGA) is run on the platform. A serial of special MDPFGAs are used to determine the static and the dynamic solutions of generalized m-best S-D assignment problem respectively, as well as target states estimation in track management. Such an assignment-based parallel algorithm is demonstrated on simulated passive sensor track formation and maintenance problem. While illustrating the feasibility of the proposed algorithm in multisensor multitarget tracking, simulation results indicate that the MDPFGAs-based algorithm has greater efficiency and speed than the FGAs-based algorithm. 相似文献
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