GPS空时自适应滤波矩阵重构抗干扰算法

小快拍数、干扰移动及天线平台震动引起协方差矩阵估计误差增加，导致现有的全球定位系统(global positioning system，GPS)空时自适应滤波抗干扰算法的性能急剧下降，为此提出了一种基于矩阵重构的GPS空时自适应滤波抗干扰算法.该算法利用Capon空间谱估计方法重构干扰加噪声协方差矩阵，并对矩阵进行时域平滑得到空时滤波权值.仿真结果表明，该算法在多干扰、低信噪比、小快拍数情况下降低了阵列误差的影响，提高了阵列天线输出信干噪比，与对角加载算法和矩阵锐化算法相比提升5dB左右.

Anti-jamming Algorithm of Space-Time AdaptiveFiltering for GPS Based on MatrixReconstruction

Global positioning system (GPS) anti-jamming algorithms suffer from severe performance degradation in the presence of covariance matrix estimation errors due to small snapshots, jamming movement and antenna vibration. In view of this problem, we present an anti-jamming algorithm of space-time adaptive filtering based on covariance matrix reconstruction. In this algorithm, the covariance matrix that includes noise and interference is reconstructed using the Capon spectral estimation method. The matrix is smoothed in the time domain to obtain space-time filter weights, thus helping reduce the influence of array errors. We analyze three aspects of the algorithm performance: space frequency response spectrum, different signal-to-noise ratio and different number of snapshots. Simulation results show that the proposed algorithm can suppress both wideband and narrowband interferences, improve signal-to-interference-plus-noise ratio of the array output under the condition of low signal-to-noise ratio and low level of snapshots. The output signal-to-interference-plus-noise ratio is improved by 5 dB, better than the diagonal loading algorithm and the covariance matrix taper algorithm.