摘要
舰船目标跟踪成为各国关注的热点,针对当前舰船目标跟踪算法存在的跟踪速度慢、跟踪精度低等缺陷,以提高舰船目标跟踪效果为目标,设计了基于节点信息融合的舰船目标跟踪算法。首先采用多个传感器对舰船目标状态信息进行收集,并对信息进行一定融合,减少舰船目标状态信息的重复率,然后引入跟踪-学习-检测技术对舰船目标进行跟踪,最后采用舰船目标跟踪实验测试其性能。结果表明,本文算法可以动态、准确地对舰船目标进行检测和跟踪,相对于当前其他舰船目标跟踪算法,无论是跟踪精度或者是跟踪实时,均具有十分明显的优势。
Ship target tracking has become a hot spot of attention in various countries. Aiming at the slow tracking speed and low tracking precision of the current ship target tracking algorithm, the target tracking effect of ship target tracking is improved, and a ship target tracking algorithm based on node information fusion is designed. At first, several sensors are used to collect the state information of ship target, and the information is fused to reduce the repetition rate of ship target state information. Then the strong tracking filtering technique is introduced to track the ship target, and the performance of the ship target tracking experiment is tested at the end. The results show that the algorithm can detect and track the ship targets dynamically and accurately. Compared with other ship target tracking algorithms, both tracking precision and tracking real-time, all of these algorithms have very obvious advantages.
出处
《舰船科学技术》
北大核心
2018年第8X期34-36,共3页
Ship Science and Technology
基金
重庆市教委科学技术研究资助项目(KJ1717372)
重庆市教委科学技术研究资助项目(KJ1601702)