A new simultaneous source separation algorithm using frequency-diverse filtering
Ying Ji, E. Kragh, P. A. F. Christie · 2012
We describe a new simultaneous source separation algorithm using frequency-diverse filtering. The method combines the array response at different frequencies to suppress spatial aliasing and converts the data separation problem into a one-norm (l1) or zero-norm (l0) optimization problem. Synthetic and field data tests show that the algorithm works well with both spatially aliased and unaliased data. The method requires further work to reduce the computation cost.