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一种时空联合约束的多源航迹相似性度量模型
引用本文:孙璐,周伟,姜佰辰,关键. 一种时空联合约束的多源航迹相似性度量模型[J]. 系统工程与电子技术, 2017, 39(11): 2405-2413. DOI: 10.3969/j.issn.1001-506X.2017.11.03
作者姓名:孙璐  周伟  姜佰辰  关键
作者单位:1. 海军航空工程学院信息融合研究所, 山东 烟台 264001;;2. 海军航空工程学院电子信息工程系, 山东 烟台 264001
摘    要:针对传统方法无法有效度量多源异步航迹时空相似性的问题,该文提出了一种适用于多源异步航迹的相似性度量模型。基于时间和空间联合约束下寻找近似时空特征匹配点的思想,通过设置时间和空间阈值上寻找符合要求的匹配点,并通过空间相似函数度量匹配点的相似性,确定最优匹配点并计算多源航迹间的航迹时空相似度。实测数据表明,该模型可以有效度量异类传感器航迹的相似性,且时间性能较优。基于该模型的航迹关联算法在仿真的复杂多目标环境中的关联准确性优于现有算法,且在对海雷达误差估计中得到了应用。


Multi-source trajectories similarity measure model with spatial and temporal constraints
SUN Lu,ZHOU Wei,JIANG Baichen,GUAN Jian. Multi-source trajectories similarity measure model with spatial and temporal constraints[J]. System Engineering and Electronics, 2017, 39(11): 2405-2413. DOI: 10.3969/j.issn.1001-506X.2017.11.03
Authors:SUN Lu  ZHOU Wei  JIANG Baichen  GUAN Jian
Affiliation:1. Research Institute of Information Fusion, Naval Aeronautical and Astronautical University,Yantai 264001, China;2. Institute of Electronics and Information Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, China
Abstract:In order to solve the problem that the spatial-temporal similarity of asynchronous multi-source multi-track cannot be measured effectively, a new trajectory similarity model for asynchronous multi-source multi-track is proposed. Based on the idea of searching the potential data points under the spatial and temporal constraints, the optimal matched point is determined from the sets of nearly matched points by setting spatial and temporal thresholds, and the similarity measure between multi-source trajectories is obtained. The experiment result conducted on a real data set shows that the model can evaluate the similarity of multi-source trajectory effectively, with lowers the time cost. When applied to a simulated complex multi-target scenario, the performance of the correlation algorithm based on this model is better than existing methods, and the algorithm has been applied to estimating bias of maritime radar.
Keywords:
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