基于虚拟锚点的室内融合定位方法OA

The use of virtual anchor point(VAP)formed by specular reflections of communication signals for terminal lo-calization has become a research hotspot in recent years.The"birth-death"phenomenon of VAP in the localization pro-cess was studied,and an indoor fusion localization algorithm based on VAP was proposed for single-input single-output(SISO)networks.Firstly,prior information provided by the state transition equation was utilized to filter out non-specular clutter in the observation set.Then,predicted observation sets corresponding to different positions on the plane and the Hungarian algorithm were employed to construct a positioning model,and a swarm optimization algorithm was applied to estimate the terminal position.Furthermore,the prior position information provided by the state equation was fused with the estimated position through a fusion-based filtering method.Simulation results show that,compared with existing methods,the proposed method effectively improves localization accuracy.The experimental results obtained from the software radio test system show that the proposed method achieves an average localization accuracy of 0.47 m in real environments.