摘要
空间邻近目标跟踪过程中存在航迹交错现象,传统的航迹关联与融合算法可靠性大大降低。提出基于跟踪状态监视的稳健航迹关联与融合跟踪算法:首先,采用滑窗式全局最优关联方法利用多帧航迹数据确认航迹关联对,并建立系统航迹;然后,根据确认关联航迹的实时关联状态检测航迹交错;最后,根据航迹衰减残差识别运动状态,自适应选择融合量测或者融合状态估计完成系统航迹的状态更新。仿真结果表明,算法能够提高融合航迹精度,实现稳健航迹关联与融合。
There exists track swap when tracking closely spaced targets,which may decrease the reliability of traditional track association and fusion algorithms greatly. Thus we proposed a robust track association and fusion algorithm with tracking state monitoring. Firstly,a sliding window global optimum association was adopted to ascertain associated track pair and establish system tracks with multiple frame track data. Then the real-time association relation of associated track pair was used to detect track swap. Lastly,track attenuated residual was used to identify maneuver in order to select the fused measurements or fused state estimation adaptively in updating state of system tracks. Simulation result shows that the proposed algorithm can improve accuracy of fusion tracks and realize robust track association and fusion.
出处
《电光与控制》
北大核心
2015年第1期6-10,共5页
Electronics Optics & Control
基金
国家自然科学基金(61032001)
山东省自然基金(ZR2012FQ004)
关键词
航迹关联
航迹融合
跟踪状态监视
空间邻近目标
track association
track fusion
tracking state monitoring
Closely Spaced Objects（CSO）
