Robust subspace tracking methods based on fast and stable DPM algorithm

The data projection method can be used in tracking the signal subspace. However, when the signal is interfered by impulse noise, the data projection method will lose its tracking ability during the period impulse noise appears. In this paper, two stable and low complexity subspace tracking algorithms are proposed to solve this problem. The basic idea is to multiply a weight coefficient before the step size of the fast and stable data projection method. When the impulse noise occurs, the weight coefficient will reduce significantly. As a result, the step size will shrink and the adverse effect of subspace tracking caused by the outlier data will be reduced. In addition, both algorithms are verified through numerical simulations, and the effect caused by signal-to-noise ratio is discussed in the simulations.