摘要
针对情报与侦察监视领域中目标轨迹预测问题,提出了一种基于无监督学习的预测方法。首先,根据历史信息分析目标历史活动规律;其次,构建隐马尔科夫模型,通过无监督学习自动实现预测目标在栅格网中的运动方向;最后,根据学习得到的运动方向和目标运动速度信息,计算未来短期内的目标轨迹。数值仿真验证了该方法能够有效地预测目标在未来短时刻内(通常为5 min)的运动轨迹。
Aiming at the problem of target trajectory prediction in the fie ld of intelligence and reconnais-sance surveillance,a prediction method based on unsupervised learning is proposed. F irs t ly,a target histori-cal activity pattern is analyzed according to historical information. Secondly,the hidden Markov model is constructed and the motion direction of the prediction target in the grid is automatically realized by unsu-pervised learning. Final ly,The target trajectory in the short term is calculated according to the learning d i-rection of motion and the speed of target motion. Numerical simulations show that the proposed method can effectively predict the trajectory of the target in the short time ( usually 5 minutes).
出处
《电讯技术》
北大核心
2018年第2期174-177,共4页
Telecommunication Engineering
关键词
情报侦察监视
目标轨迹预测
目标历史信息
活动规律分析
无监督学习
柵格化
intelligence and reconnaissance surveillance
target trajectory prediction
target historical infor-mation
activity pattern analysis
unsupervised learning
rasterize