基于模糊聚类的海洋目标跟踪过程智能数据处理

Zheng Zhang, Yanwei Du
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引用次数: 0

摘要

针对海上救援场景中多目标跟踪存在的跟踪不准确、航迹初始化困难等问题,提出了一种基于模糊聚类的海上跟踪数据智能处理方法。测量装置的传感器接收到的测量信息在一段时间内进行模糊聚类处理,然后利用隶属矩阵中的熵来判断目标数量的变化情况。这样可以确定目标数量的数量,更准确地跟踪目标。本文还通过仿真实验对该方法进行了分析和改进,以解决实际情况中聚类不准确等问题。该方法能够满足跟踪速度和跟踪精度的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Data Processing of Marine Target Tracking Process Based on Fuzzy clustering
Aiming at the inaccurate tracking and the difficulty of the track initialization during multi-target tracking in marine rescue scenes, this article proposes an intelligent processing method for marine tracking data based on fuzzy clustering. The measurement information received by the sensor of the measuring device is subjected to the fuzzy clustering process in a period of time, then the entropy from the subjection matrix is used to judge the change in the number of targets. In this way, the number of the target quantity can be determined and the target can be tracked more accurate. This article also analyzes and improves the method through simulation experiments to solve to problems such as inaccurate clustering in real situations. And the method can meet the needs of tracking velocity and tracking accuracy.
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