计算机与现代化

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动目标数据实时分析技术研究与实现

  

  1. (华北计算技术研究所地理与图形图像研发部,北京100083)
  • 收稿日期:2019-06-05 出版日期:2020-02-13 发布日期:2020-02-13
  • 作者简介:侯博(1994-),男,山西太原人,硕士研究生,研究方向:计算机图形学,分布式数据库,E-mail: 765227120@qq.com; 聂颖(1972-),女,北京人,高级工程师,硕士,研究方向:计算机图形图像,图形处理架构研究和算法,E-mail: niey@cetc15.net。
  • 基金资助:
    总装“十三五”预研项目(31511070401)

Research and Implementation of Real-time Analysis Technology of Moving Target Data

  1. (Research and Development Department of Geography, Graphics and Images,
    North China Institute of Computing Technology, Beijing 100083, China)
  • Received:2019-06-05 Online:2020-02-13 Published:2020-02-13

摘要: 针对动目标的实时轨迹数据,分析已有研究出现的问题,提出2种实时分析的解决思路:基于五点微分法的轨迹预测方法,此方法可以较快速地预测动目标下一个位置点,实时性较强;基于Storm的历史频次统计分析方法,此方法根据历史轨迹频次进行分析,准确率较高。上述2种方法解决了实时分析的2个重点问题:实时、准确,有较高的实用性。

关键词: 动目标; 实时分析, 流数据框架

Abstract: Aiming at the real-time trajectory data of moving object, this paper analyzes the problems consisting in the existing research, and proposes two solutions for real-time analysis. The first one is trajectory prediction method based on five-point method, which can predict the next point’s position of moving object rapidly and has strong real-time performance. The second one is Storm-based historical frequency statistical analysis method, which analyzes historical track frequency with high accuracy. These two methods solve two important problems in real-time analysis: real-time, accurate, and have high practicability.

Key words: moving object, real-time analysis, stream data framework

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