Application of the bootstrap to source detection in nonuniform noise

We consider the problem of source number estimation in the presence of unknown spatially nonuniform noise. A sequential hypothesis test is formulated based on Gerschgorin´s theorem. As no assumption is made on the distribution of the noise or the signals, the bootstrap is used to estimate the distribution of the proposed test statistics. Performance of the new detector is assessed through simulations and its advantage is illustrated in different scenarios against a Gerschgorin-based information criterion.