Spectral factorization for integer-interval sampled sequence and its applications in array processing

Spectral factorization (SF) has been well developed for a uniformly sampled sequence (USS). Our recent study found important applications of SF for a non-uniformly sampled sequence (NUSS) in array processing, especially considering arbitrary arrays. Since SF for an arbitrarily sampled sequence is intractable, in this paper, we propose a new SF method for an integer-interval sampled sequence (IISS). Its applications in robust adaptive beamforming and array pattern synthesis for a non-uniform linear array (NULA) are studied. Simulation results show the outstanding performance of the proposed method.