Adaptive filtering for incident plane wave estimation

Plane wave propagation is an important field of interest in magnetic theory. In this paper, we propose an adaptive filtering noise canceller that enables us to estimate an incident plane wave from the total plane wave seen in a medium. In order to test the proposed canceller, a comparison between the performances of the least mean square (LMS), recursive least squares (RLS) and recursive inverse (RI) algorithms is investigated. Simulation results show that the RI algorithm outperforms the LMS algorithm in terms of convergence rate and the ability of estimating the incident wave. Also, it outperforms the RLS algorithm in terms of the number of mathematical operations required at each iteration and the ability of suppressing noise.