access icon free Matching pursuit for direction of arrival estimation in the presence of Gaussian noise and impulsive noise

Two high-resolution direction of arrival (DOA) estimation approaches of non-stationary narrowband signals based on matching pursuit (MP) are developed. The first sensor output is considered as the reference and decomposed by MP. As the MP is a linear decomposition, the obtained MP coefficients contain the steering vector information. So, the MP coefficients corresponding to the leading decomposition atoms are used to develop the MP-MUSIC algorithm for the DOA estimation. In addition, the chosen MP atoms are used to implement the modified spatial time–frequency distribution (STFD) based on Wigner Ville (WV) distribution as well, and this method named MP-WV. It has been demonstrated that these two methods can be applied for underdetermined problems and are robust against Gaussian and impulsive noises. The authors show that using either coefficients or chosen atoms to estimate the DOA in array processing by considering the source discriminative capability outperforms the conventional MUSIC and STFD. Some simulation results showing the performance of the two proposed approaches based on MP, conventional MUSIC and STFD are presented.

Inspec keywords: direction-of-arrival estimation; Gaussian noise; array signal processing; time-frequency analysis; signal classification; Wigner distribution; impulse noise

Other keywords: Wigner Ville distribution; high-resolution direction of arrival estimation approaches; matching pursuit; linear decomposition; modified spatial time-frequency distribution; decomposition atoms; MP-MUSIC algorithm; impulsive noise; source discriminative capability; Gaussian noise; steering vector information; WV distribution; DOA estimation approaches; array processing; STFD

Subjects: Other topics in statistics; Other topics in statistics; Signal processing and detection; Signal processing theory

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