Source number estimation in impulsive noise environments using bootstrap techniques and robust statistics

We consider the problem of source number estimation in array processing when impulsive noise is present. To combat impulsive noise more effectively, two robust estimators with high breakdown points, i.e., the minimum covariance determinant (MCD) estimator and the MM-estimator are applied in combination with the bootstrap. The MCD estimator is applied to discard the outliers in observations caused by impulsive noise, while the MM-estimator is suggested to estimate robustly the covariance matrix of observations. Simulations show the significant performance gain offered by the two proposed methods in terms of correctly estimating the number of sources at low SNR in the presence of impulsive noise.