传统波束成形算法在高速车载天线定位和信道估计的准确性方面遇到严重挑战。本课题探索研究基于接收天线与训练天线分离（SRTA）的高速车载多天线自适应波束成形定位算法，着重从天线定位错位、天线接收信噪比、预测天线信号AOA估计三个方面考虑解决波束成形技术带来的接收天线与预测天线位置的定位错位及接收信噪比下降问题。给出基于SRTA的BS端部分传输天线自适应关闭和激活的波束成形算法，自适应调整波束宽度及覆盖面，满足车载接收天线接收信噪比需求。提出基于SRTA的多项式插值信道估计波束成形算法，精确估计信道参数，在此基础上设计高速车载多天线自适应波束成形算法，改善车载天线接收信噪比，以消除或减小车载天线定位错位。探索研究AOA动态波束成形算法估计预测天线来波方向和角度，辅助多项式插值SRTA算法和BS端部分传输天线自适应关闭和激活的SRTA算法，改善接收信噪比、消除车载天线波束成形定位错位。

Traditional beamforming algorithms have serious challenges in the accuracy of vehicle antennas positioning and channel estimation with high speed. In this proposal, we try to researching multi-antennas adaptive beamforming positioning algorithm based on separate receive and training antennas (SRTA) for very fast moving vehicle. Project Mainly solve the problems of vehicle received SNR decreased and position mispointing between receiving antennas and predictor antennas in three aspects including vehicle antennas mispointing, vehicle antennas receiving signal-to-noise ratio, AOA estimation of predictor antenna transmitted signals. We propose beamforming algorithm which adaptive switch off or active part of transmission antennas of BS based on SRTA, which can adaptive adjust beam width and coverage, with the aim to meet the needs of vehicle antennas received SNR. SRTA with polynomial interpolation channel estimation beamforming algorithm is presented, which can accurately estimate the channel parameters. Then, a fast moving vehicles multi-antennas adaptive beamforming algorithm has been explored. In this scheme, algorithm can improve vehicle received SNR and decrease or eliminate beamforming mispointing. Try to researching AOA dynamic beamforming algorithm to estimate the direction and angle of predictor antenna signals. In this scheme, we combine it with SRTA polynomial interpolation algorithm and part of transmission antennas adaptive switch off and active beamforming algorithm of BS based on SRTA to improve vehicle receiving SNR and eliminating vehicle multi-antennas beamforming mispointing.