Abstract: As one fuses the position information obtained from anti-aircraft lookout post and the track from bearings-only tracking sensors，there are different observation dimensions，different sampling rates and longer intervals between them.On the base of the sample fusion algorithm，a new fusion algorithm is presented to the problem that fusion between the observation data from the anti-aircraft lookout post network and the local tracks from the bearings-only tracking sensors.The new algorithm not only alters the corresponding track data，but also alters the neighbor track data in some degree.The experimental results illustrate the proposed algorithm has better performance than the traditional simple fusion algorithm.

摘要： 在对观察哨获得的目标位置数据和只测角跟踪航迹数据进行融合时，两者观测维数不一致，数据采样率也不一致，而且观察哨数据时间间隔相对要长。在简单航迹融合算法的基础上，针对对空观察哨和只测角局部航迹的融合问题，提出了一种新的融合算法，与传统的简单航迹融合算法相比，该算法不但对时刻一致的航迹数据进行修正，而且对被修正数据相邻的数据也进行不同程度的修正。仿真结果表明，新算法在对空观察哨与只测角传感器航迹的融合中具有较好的融合性能。