Anti-jamming algorithm of space-time adaptive filtering for GPS based on matrix reconstruction

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.