A Simple Nonparametric Preprocessing Technique to Correct for Nonstationary Effects in Measured Data

The general approach for modeling systems assumes that the measured signals are (weakly) stationary, i.e., the power spectrum is time invariant. However, the stationarity assumption is violated when: 1) transient effects due to experimental conditions are dominant; 2) data are missing due to, for instance, sensor failure; or 3) the amplitude of the excitation signals smoothly varies over time due to, for instance, actuator problems. Although different methods exist to deal with each of these nonstationary effects specifically, no unified approach is available. In this paper, a new and general technique is presented to handle nonstationary effects, based on processing overlapping subrecords of the measured data. The proposed method is a simple preprocessing step where the user does not need to specify which nonstationary effect is present, nor the time interval where the nonstationary effect appears. The merits of the proposed approach are demonstrated on an operational wireless system suffering from interrupted link effects.