This paper aims to design a method of multi-source data fusion in multi-target collaborative navigation. First, the respective features of GPS/INS/RS/MO data in the navigation process are clarified. Then a multi-source data fusion method is designed including GPS/INS data fusion with adaptive Kalman filter, RS/MO data fusion with ranging table matching of observation targets, and joint adjustment with fused GPS/INS and RS/MO data. Finally, a simulation experiment is carried out to verify the improvement in positioning efficiency and precision. The results show that collaborative navigation based on multi-source data fusion can increase the stability and accuracy of the navigation service.

本文旨在设计一种多目标协同导航中的多源数据融合方法。首先，明确GPS/INS/RS/MO数据在导航过程中的各自特点。然后设计了一种多源数据融合方法，包括自适应卡尔曼滤波的GPS/INS数据融合、观测目标测距表匹配的RS/MO数据融合以及融合GPS/INS和RS/MO数据的联合平差。最后通过仿真实验验证了定位效率和精度的提高。结果表明，基于多源数据融合的协同导航可以提高导航服务的稳定性和准确性。