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本文主要研究文［１］提出的分层融合算法的数学、物理性质．定义了分层融合估计中的融合航迹的新息和融合增益，分析并证明了它们所具有的数学、物理性质，最后得出并证明该分层融合估计，就是基于各传感器的滤波及其预测的线性无偏最小方差估计的结论．这进一步揭示了分层融合估计的本质，并对正确使用该算法解决多传感器多目标跟踪问题有参考意义．
This paper mainly studies the mathematical and physical properties of the hierarchical fusion algorithm proposed in [1]. Define the new information and fusion gain of the fusion track in the hierarchical fusion estimation, analyze and prove their mathematical and physical properties, and finally conclude and prove that the hierarchical fusion estimation is based on the filtering of each sensor and its Prediction of linear unbiased minimum variance estimation conclusion. This further reveals the nature of the hierarchical fusion estimation, and is of reference significance for the correct use of the algorithm to solve the multi-sensor multi-target tracking problem.