针对大量传感器同时跟踪同一目标产生海量目标量测数据而一般融合滤波算法难以处理的问题，提出了通过数学统计原理提取跟踪状态信息并应用交互式多模型统计滤波算法进行解决的方法。该方法首先利用数学统计原理从海量目标量测数据中统计出目标跟踪滤波过程中所需要信息，并利用改进的交互式当前统计模型算法对所提取信息进行滤波，在不影响跟踪精度的情况下很好地解决了的海量目标量测信息的融合跟踪问题。理论分析和仿真结果证明了该方法的有效性。

When a large number of sensors are used to track the same target at the same time,massive amount of data will be produced which is difficult to deal with by using normal fusion filter algorithm.To solve the problem a method was proposed using interacting multiple model statistic filter algorithm based on mathematical statistics.The algorithm utilized mathematical statistics to figure out the information used in target tracking from the massive amount of target data.The improved interacting current statistical model algorithm was used for filtering the extracted data which solved the fused tracking problem without decreasing the tracking precision.The theoretical analysis and simulation results show the effectiveness of the proposed algorithm.