Generalized Sidelobe Canceller with Variable Step-Size Least Mean Square Algorithm Controlled by Signal-to-Noise Ratio
Shizhao Li, Quanli Liu, Wei Wang · 2022 5th International Conference on Data Science and Information Technology (DSIT) · 2022
In this paper, the generalized sidelobe canceller is improved to reduce the noise component in its output signal. The noise reduction ability of the generalized sidelobe canceller will decrease under the influence of diffusion noise, and the normalized least mean square algorithm also has a large steady-state error. To reduce the influence of diffusion noise, the power ratio of the output signal of generalized sidelobe canceller and blocking matrix is taken as the signal-to-noise ratio. And the proportion of noise component in output signal of generalized sidelobe canceller is introduced to control the step size. The signal-to-noise ratio and proportion of noise are used to jointly control the updating of weight coefficient of the adaptive noise canceller. In addition, the variable step size least mean square algorithm is used instead of the normalized least mean square algorithm. And a new step size update formula is proposed to further reduce the noise component in the output signal of the generalized sidelobe canceller. Experimental results show the effectiveness of the proposed algorithm in diffuse noise environment.