DOA tracking algorithm for railway wireless radio signals based on cloud platform
DAI Sai
SUN Xiaofang
ZUO Ying
WU Xinmeng
DING Jianwen
SUN Bin
ZHONG Zhangdui
Abstract：In high-speed railway scenarios,accurate estimation and tracking of the Direction of Arrival(DOA) of radio signals can significantly enhance the quality of wireless communication services. How-ever,the rapidly changing radio channels in high-speed railway environments present unique challenges in terms of speed and accuracy for signal processing. Traditional DOA estimation algorithms based on signal subspaces are not suitable for DOA tracking in fast time-varying systems due to their computa-tional complexity. To solve this problem,in this paper,a DOA tracking algorithm,named Kalman Filter-Orthonormal Projection Approximation and Subspace Tracking of deflation (K-OPASTd),is pro-posed. Firstly,a dynamic direction finding system for railway signals is established on a cloud platform. Then,a model for the signals received by trains is developed,and the K-OPASTd algorithm is intro-duced for dynamic DOA tracking. Finally,the root-mean-square errors of the estimated angles obtained by the algorithm proposed in this paper are compared with the OPASTd algorithm. The results demon-strate that,at a signal-to-noise ratio of 10 dB,the proposed algorithm achieves a 60％ reduction in root-mean-square error compared to the OPASTd algorithm;with an array size of 20 elements,the proposed algorithm reduces the root-mean-square error by approximately 80％.
Keywords：direction of arrival trackingOPASTdKalman filtercloud platform
Publication Date：2024-04-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 115-121 )