A Spatio-Temporal Track Association Algorithm Based on Marine Vessel Automatic Identification System Data
A Spatio-Temporal Track Association Algorithm Based on Marine Vessel Automatic Identification System Data
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DOI：
10.1109/tits.2022.3187714
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发表时间：
2022-07-15
影响因子：
8.5
通讯作者：
Ding, Yu
中科院分区：
文献类型：
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作者：
Ahmed, Imtiaz;Jun, Mikyoung;Ding, Yu
在动态威胁环境中实时跟踪多个运动目标是国家安全与监控系统的重要组成部分。它有助于准确定位和区分对其他正常物体构成威胁的潜在候选者，并监控异常轨迹，直到进行干预。为了定位运动的异常模式，需要有一种准确的数据关联算法，该算法可以将位置和运动的顺序观测与底层移动对象相关联，从而在对象移动时建立对象的轨迹。在这项工作中，我们开发了一种时空方法来跟踪海上船舶，因为船舶的位置和运动观测是由自动识别系统收集的。提出的方法是为了应对数据关联挑战，其中故意隐瞒船只数量以及船只识别，并在数据集中创建时间间隔，以模拟威胁环境下的真实操作复杂性。挑战赛提供了三个训练数据集和五个测试集，数据挑战赛组织者设计了一套量化的绩效指标，用于评估和比较参与者开发的结果方法。将本文提出的航迹关联算法应用到五个测试集上，取得了非常有竞争力的性能。
Tracking multiple moving objects in real-time in a dynamic threat environment is an important element in national security and surveillance system. It helps pinpoint and distinguish potential candidates posing threats from other normal objects and monitor the anomalous trajectories until intervention. To locate the anomalous pattern of movements, one needs to have an accurate data association algorithm that can associate the sequential observations of locations and motion with the underlying moving objects, and therefore, build the trajectories of the objects as the objects are moving. In this work, we develop a spatio-temporal approach for tracking maritime vessels as the vessel's location and motion observations are collected by an Automatic Identification System. The proposed approach is developed as an effort to address a data association challenge in which the number of vessels as well as the vessel identification are purposely withheld and time gaps are created in the datasets to mimic the real-life operational complexities under a threat environment. Three training datasets and five test sets are provided in the challenge and a set of quantitative performance metrics is devised by the data challenge organizer for evaluating and comparing resulting methods developed by participants. When our proposed track association algorithm is applied to the five test sets, the algorithm scores a very competitive performance.