Open AccessPassive localisation of mixed far‐field and near‐field sources using uniform circular array
Author(s) -
Xue Bing,
Fang Guangyou,
Ji Yicai
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2016.2091
Subject(s) - subspace topology , signal subspace , signal (programming language) , algorithm , near and far field , multiple signal classification , covariance matrix , matrix (chemical analysis) , field (mathematics) , noise (video) , mathematics , direction of arrival , projection (relational algebra) , acoustics , computer science , artificial intelligence , optics , telecommunications , physics , antenna (radio) , image (mathematics) , materials science , composite material , pure mathematics , programming language
Using uniform circular array, a passive localisation algorithm is presented for the scenarios where both far‐field and near‐field narrow‐band signals may exist synchronously. The differencing matrix and the orthogonal projection matrix of the signal subspace are built to classify the mixed signals and to estimate the 2D direction‐of‐arrivals (DOAs) of the near‐field signals (NFSs). Then, the covariance matrix of signals is decomposed to obtain the noise subspace. Meanwhile, 1D multiple signal classification (MUSIC) is used to estimate the ranges of the NFSs and 2D MUSIC is used to estimate the DOAs of far‐field signals (FFSs). Compared with two‐stage MUSIC (TSMUSIC), the proposed algorithm can provide higher resolution for the DOAs so that the signals can be separated. In addition, compared with TSMUSIC and four‐order cumulant MUSIC, the proposed algorithm has higher accuracy for localisation of both FFSs and NFSs. Simulation results are carried out to verify the performance of the proposed algorithm.