满足高精度测量的GNSS自适干扰抑制算法

日益复杂的电磁环境严重干扰了全球卫星导航系统（Global Navigation Satellite System，GNSS）的正常有效运行.多天线空域自适应处理能够有效抑制电磁干扰，但是空域自适应处理算法可能会引入卫星信号载波相位误差.此外，多天线组成的阵列本身存在各种不理想因素也会引入误差，这些对高精度测量系统来说是不可容忍的.为此，本文首先分析了GNSS中常用的空域自适应处理算法在抑制干扰的同时对载波相位测量的影响，在此基础上提出了一种不需要阵列流形信息的盲波束形成算法——二次解重扩算法.其核心思想是在解重扩（De-spread Re-spread，DR）算法的基础上增加频率精估计环节，并根据精估后的载波频率重新构造本地参考信号与接收数据进行相关，从而最小化波束形成权矢量与卫星信号的导向矢量之间的误差，减小了空域抗干扰对卫星信号载波相位的影响.

GNSS Adaptive Interference Suppression Algorithm for High Accuracy Measurement

The increasingly complex radio frequency electromagnetic environment seriously interferes the normal operation of GNSS.Spatial adaptive processing using multi antenna can effectively suppress the interference,but the spatial adaptive processing algorithm may introduce the satellite signal carrier phase measurement error.In addition,nonideal factors of the array will also introduce errors,which is intolerable for high-precision measurement systems.Therefore,in this paper,the influence of the frequently-used spatial adaptive processing algorithm on the carrier phase measurement is analyzed theoretically.Furthermore,a blind adaptive processing algorithm does not need the array manifold information is proposed,which can effectively increase the antenna gain in the direction of the desired satellite while forming reception nulls towards the interference,meanwhile,the introduced carrier phase measurement error is reduced effectively,referred to as two step De-spread Re-spread (DR) algorithm.The core idea of the proposed algorithm is to add a high accuracy frequency estimation modular to the DR algorithm,the fine carrier frequency estimation is then used to construct the local reference signal,so as to ensure the error between the steering vector obtained beamforming weight vector and the satellite signal as small as possible.