相似性测度算法是根据航迹模式完成各局部航迹分配的关联方法, 关联效果较好。为减小相似性测度计算过程中不确定因素对航迹关联的不利影响, 实现信息融合系统性能的持续改进, 基于不确定性分析提出了修正相似性测度关联算法。分析了归一化航迹相似性测度关联中存在的不确定性; 综合考虑了传感器虚情、漏情、未检测区域以及参数未确知性等因素对航迹关联的影响, 计算出相应的影响因子, 并用这些影响因子对航迹的相似性测度进行修正。实验表明, 修正的航迹关联算法能获得更低的关联错误率, 有效提高系统鲁棒性。

The similarity measurement algorithm is a data association method for assigning the local tracks based on the pattern similarity,which has a fine association effect.In order to reduce the adverse impact of uncertain factors on the track correlation and improve the information fusion performance,an improved similarity measurement correlation method was proposed based on uncertainty analysis.The uncertainties existed in similarity correlation of track were analyzed by taking the influence of such uncertain factors as false positive track,false negative track,undetected area and unascertained performance of the sensors on track correlation into consideration.The corresponding impact factors were calculated out,which were then used to modify the similarity measurement of the track.The experiment showed that the modified track correlation algorithm has lower false correlation rate and higher system robustness.