tailieunhanh - Báo cáo toán học: " Joint DOA and multi-pitch estimation based on subspace techniques"

Tuyển tập các báo cáo nghiên cứu khoa học ngành toán học được đăng trên tạp chí toán học quốc tế đề tài: Joint DOA and multi-pitch estimation based on subspace techniques | Zhang et al. EURASIP Journal on Advances in Signal Processing 2012 2012 1 http content 2012 1 1 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Joint DOA and multi-pitch estimation based on subspace techniques Johan Xi Zhang1 Mads Gr sboll Christensen2 Soren Holdt Jensen1 and Marc Moonen3 Abstract In this article we present a novel method for high-resolution joint direction-of-arrivals DOA and multi-pitch estimation based on subspaces decomposed from a spatio-temporal data model. The resulting estimator is termed multi-channel harmonic MUSIC MC-HMUSIC . It is capable of resolving sources under adverse conditions unlike traditional methods for example when multiple sources are impinging on the array from approximately the same angle or similar pitches. The effectiveness of the method is demonstrated on a simulated an-echoic array recordings with source signals from real recorded speech and clarinet. Furthermore statistical evaluation with synthetic signals shows the increased robustness in DOA and fundamental frequency estimation as compared with to a state-of-the-art reference method. Keywords multi-pitch estimation direction-of-arrival estimation subspace orthogonality array processing 1. Introduction The problem of estimating the fundamental frequency or pitch of a period waveform has been of interest to the signal processing community for many years. Fundamental frequency estimators are important for many practical applications such as automatic note transcription in music audio and speech coding classification of music and speech analysis. Numerous algorithms have been proposed for both the single- and multi-pitch scenarios 1-5 . The problem for single-pitch scenarios is considered as well-posed. However in real-world signals the multi-pitch scenario occurs quite frequently 2 6 . The multi-pitch estimation algorithms are often based on . various modification of the auto-correlation .