摘要
针对经典的中断航迹关联算法在机动目标环境下航迹预测准确性差、关联效果恶化严重的问题,提出基于先验信息的多假设运动模型中断航迹关联算法。所提算法充分利用目标属性、目标运动特征、使用场景等先验信息,基于多假设思想,建立多种可能的目标运动模型并实施航迹预测,基于位置和速度信息的模糊相关函数描述预测航迹与新起始航迹的模糊匹配关系,最后基于多项式拟合原理连接满足关联关系的新、老航迹。经仿真验证,在中断区间目标发生机动运动的条件下,所提算法的关联效果相对于经典的中断航迹关联算法有显著提升。所提算法对于复杂环境具有较强的适应能力,经50次蒙特卡罗仿真,在中断时间小于18个滤波周期条件下,机动目标的平均正确关联率达到90%以上,机动环境的全局关联正确率达到85%以上。
As tracks forecasting and associating accuracy of the traditional track segment association algo- rithms deteriorates seriously in maneuvering targets environment, a new algorithm based on multiple-hypothesis motion models with priori information is proposed. The algorithm firstly builds multiple hypothesis motion models for tracks forecasting according to the priori information, for instance target property, target motion fea- tures, scenario condition, then describes the matching relations between forecasted old tracks and new tracks according to fuzzy correlation function on location and velocity information. Finally, the associated track seg- ments on the basis of polynomial fitting connected. Simulation results showed that in the maneuvering targets scenario, the proposed algorithm remarkably outperformed the traditional track segment association algorithm. The proposed algorithm is suitable for complicated environment, after 50 times Monte Carlo simulation, when the break interval is less than 18, the average correct association rate of the maneuvering targets is more than 90%, and the global correct association rate is more than 85%.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2015年第4期732-739,共8页
Systems Engineering and Electronics
基金
山东省自然科学基金青年基金项目(ZR2012FQ004)
飞行器测控与通信教育部重点实验室开放基金(CTTC-FX201302)资助课题
关键词
中断航迹关联
先验信息
多假设
模糊相关函数
航迹拟合
track segment association （TSA）
priori information~ multiple-hypothesis
fuzzy correlationfunction
tracks fitting
作者简介
齐林（1989-），男，博士研究生，主要研究方向为目标跟踪、多传感器信息融合。E—mail：3278pirate@163．com
王海鹏（1985-），男，讲师，博士，主要研究方向为群目标跟踪、多传感器信息融合。E—mail：armystudent@sohu．com
熊伟（1977-），男，教授，博士，主要研究方向为状态估计、指挥自动化。E—mail：xiongweimail@tom．com
董凯（1986-），男，讲师，博士，主要研究方向为航迹关联、多传感器信息融合。E—mail：188dongkai@163．com
