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作 者:张静[1] 黄铭[2] 黄靥欢 刘鸿博[1] ZHANG Jing;HUANG Ming;HUANG Ye-huan;LIU Hong-bo(Sichuan Water Conservancy Vocational College,Chongzhou 610000,China;Sichuan Technology and Business College,Dujiangyan 611830,China;College of Geosciences and Engineering,Nanjing University,Nanjing 210023,China)
机构地区:[1]四川水利职业技术学院,四川崇州610000 [2]四川工商职业技术学院,四川都江堰611830 [3]南京大学地球科学与工程学院,江苏南京210023
出 处:《舰船科学技术》2020年第6期58-60,共3页Ship Science and Technology
基 金:四川省教育厅科研项目(18ZB0501,18ZB0499)
摘 要:现有时变海面舰船多目标优化跟踪数学模型由于技术的不成熟,存在跟踪效果差的问题。为了解决上述问题,提出时变海面舰船多目标优化跟踪数学模型研究。以雷达获取的海面图像为前提,采用可变部件模型检测舰船多目标,利用光流法生成舰船多目标轨迹片段,将得到的舰船多目标轨迹片段映射到成本流量网络中,形成网络流图,得到最小网络流的舰船多目标方程,通过最短路径算法求解最小网络流网络,实现了时变海面舰船多目标的优化跟踪。通过仿真对比实验结果表明,与现有的时变海面舰船多目标优化跟踪数学模型相比较,构建的时变海面舰船多目标优化跟踪数学模型极大的提升了跟踪效果,充分说明构建的时变海面舰船多目标优化跟踪数学模型具备更好的性能。Due to the immature technology, the existing mathematical model of time-varying sea surface ship multi-objective optimal tracking has the problem of poor tracking effect. In order to solve the above problems, the mathematical model of time-varying sea surface ship multi-objective optimal tracking is proposed. Based on the sea surface image obtained by radar, the multi-target of ship is detected by the variable component model, and the multi-target track segment of ship is generated by the optical flow method. The multi-target track segment of ship is mapped to the cost flow network to form the network flow diagram, and the multi-target equation of the minimum network flow is obtained. The minimum network flow network is solved by the shortest path algorithm, and the time is achieved multi-objective optimal tracking of variable sea surface ships. The simulation results show that compared with the existing time-varying sea surface ship multi-objective optimal tracking mathematical model, the constructed time-varying sea surface ship multi-objective optimal tracking mathematical model greatly improves the tracking effect, which fully shows that the constructed time-varying sea surface ship multi-objective optimal tracking mathematical model has better performance.
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