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。
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.
作者
侯博
聂颖
HOU Bo;NIE Ying(Research and Development Department of Geography,Graphics and Images,North China Institute of Computing Technology,Beijing 100083,China)
出处
《计算机与现代化》
2020年第1期17-21,27,共6页
Computer and Modernization
基金
总装“十三五”预研项目(31511070401)
关键词
动目标
实时分析
流数据框架
moving object
real-time analysis
stream data framework
