A Spatial Self-Interference Cancellation Algorithm of LEO Navigation Augmentation System Based on WIMUSIC and LCMV
Xiangfang Meng, Qingwu Yi, Song Xie, Guanghua Zhang · 2022 IEEE International Conference on Unmanned Systems (ICUS) · 2022
Aiming at the issue that the navigation augmentation signal interferes with the normal received signal of the LEO-NA (Low Earth Orbit Navigation Augmentation) payload in the LEO-NA system, a spatial self-interference cancellation algorithm based on WIMUSIC (Weighted Improved Multiple Signal Classification) and LCMV (Linearly Constrained Minimum Variance) is proposed. First, a new covariance matrix is obtained by reconstructing the covariance matrix of the received data. The corresponding noise subspace is constructed by decomposing the new covariance matrix with singular value decomposition. Then, the weighted value is built using the eigenvalue, and the DOA (Direction of Arrival) estimation of the received signal is realized. Finally, the LCMV adaptive beamforming algorithm is used to form null at the self-interference signal direction and gain at the interest signal direction. Simulation results indicate that compared with the existing improved MUSIC (Multiple Signal Classification) methods, our algorithm can achieve accurate DOA estimation of the received signal when SNR (Signal-to-Noise Ratio) is low, and the signal angle interval is small. Compared with the existing variable step size LMS (Least Mean Square) algorithms, ICR (Interference Cancellation Ratio) is improved by 7.3dB.