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Moving Objects Tracking in Distributed Maritime Observation Systems

机译:分布式海上观测系统中的运动目标跟踪

摘要

This paper considers the processes of target tracking complicated by big data gaps in complex media such as Distributed Maritime Observation System (DMOS). The main purpose of DMOS is to support the favorable navigation conditions, monitoring, life-saving on the sea for different ships in harbors, maritime roads and open sea. DMOS can be considered as a heterogeneous distributed computer system, it includes different layers of services at different levels of abstraction: ship, harbor; regional and global levels. Such a framework is based on several satellite and maritime information systems that nowadays favor the integration of maritime data (e.g., AIS, ECDIS, OPTIMARE, GMDSS). Despite of the input data big volume the situations exist when gaps (e.g., time delays from minutes to hours) between target observations’ points are different. Well known algorithms of target tracking do not work properly in such situations. The proposed approach describes synthesis of analytical and simulation methods at tactical hypothesis development for the cases when suitable direct analytics is not applicable. Also, a joined artificial techniques’ scenario approach to tactical situation hypothesis development is proposed.
机译:本文考虑了在诸如分布式海事观察系统(DMOS)之类的复杂介质中由于大数据缺口而导致的目标跟踪过程。 DMOS的主要目的是为港口,海上道路和公海中的各种船舶提供良好的导航条件,监控,海上救生。 DMOS可以看作是一种异构的分布式计算机系统,它包括处于不同抽象级别的不同服务层:船舶,港口;区域和全球层面。这样的框架是基于当今支持海上数据集成的若干卫星和海上信息系统(例如,AIS,ECDIS,OPTIMARE,GMDSS)。尽管输入数据量很大,但是当目标观测点之间的间隔(例如,从几分钟到几小时的时间延迟)不同时,仍然存在这种情况。在这种情况下,众所周知的目标跟踪算法无法正常工作。对于合适的直接分析方法不适用的情况,所提出的方法描述了战术假设开发中分析和模拟方法的综合。此外,还提出了一种联合人工技术的情景方法来发展战术情景假设。

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