针对目标跟踪系统中存在的无序量测问题, 在前向预测的基础上, 提出使用协方差交叉法处理无序量测的滤波算法。新算法首先在前向预测框架下, 构建包含延迟量测信息的重构航迹, 而后采用协方差交叉法对重构航迹与已有航迹进行融合, 实现再更新。通过采用信息滤波器和协方差交叉法, 避免了状态转移矩阵求逆及求解航迹相关性等复杂运算,新算法可处理一步和多步延迟无序量测情形。理论分析和仿真实验说明, 新算法在保证滤波精度的基础上, 减小了存储量与计算量, 实时性更好。

Since Out-of-Sequence Measurement(OOSM) problem may occur in target tracking system, a filtering algorithm using covariance intersection was proposed to solve the problem on the basis of forward prediction.Based on forward prediction, a reconstructed track containing delay measurement information was established.Then the covariance intersection method was applied to fuse the reconstructed track with the existing track to achieve the update again.Through adopting information filter and covariance intersection method, the complex operations, such as calculating the inverse of state transition matrix and track correlation, were not needed again.The new algorithm can deal with both the one-step-lag and multi-step-lag OOSM situations.Theoretical analysis and simulation results show that the new algorithm achieves better real-time performance with less storage and computation cost while keeping the filtering precision.