scholarly journals EFFICIENT LOCALIZATION ALGORITHM OF MIXED FAR-FIELD AND NEAR-FIELD SOURCES USING UNIFORM CIRCULAR ARRAY

2016 ◽  
Vol 51 ◽  
pp. 139-146 ◽  
Author(s):  
Bing Xue ◽  
Guangyou Fang ◽  
Yi-Cai Ji
Keyword(s):  
Near Field ◽  
Far Field ◽  
Circular Array ◽  
Localization Algorithm

scholarly journals Mixed Incoherent Far-Field and Near-Field Source Localization under Uniform Circular Array

Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1432 ◽  
Author(s):  
Xiaolong Su ◽  
Zhen Liu ◽  
Xin Chen ◽  
Xiang Li
Keyword(s):  
Source Localization ◽  
Near Field ◽  
Far Field ◽  
Circular Array ◽  
Field Source

Passive Localization of Mixed Near-Field and Far-Field Sources Without Eigendecomposition via Uniform Circular Array

2020 ◽  
Vol 39 (10) ◽  
pp. 5298-5317
Author(s):  
Xiaolong Su ◽  
Zhen Liu ◽  
Tianpeng Liu ◽  
Bo Peng ◽  
Xin Chen ◽  
...  
Keyword(s):  
Near Field ◽  
Far Field ◽  
Circular Array ◽  
Passive Localization

scholarly journals Joint Space and Time Processing for Unknown Mutual Coupling Blind Calibration and Mixed Sources Identification Using Uniform Circular Array

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 525 ◽  
Author(s):  
Kai Wang ◽  
Ling Wang ◽  
Jian Xie ◽  
Yuexian Wang ◽  
Zhanolin Zhang
Keyword(s):  
Mutual Coupling ◽  
Near Field ◽  
Joint Space ◽  
Space Time ◽  
Far Field ◽  
Circular Array ◽  
Rank Reduction ◽  
Time Processing ◽  
Sources Identification ◽  
Blind Calibration

In classification and localization of mixed far-field and near-field sources, the unknown mutual coupling degrades the performance of most high-resolution algorithms. In practice, the assumption of an ideal receiving sensor array is rarely satisfied. This paper proposes an effective algorithm of mixed sources identification using uniform circular array under unknown mutual coupling. Firstly, according to rank reduction and joint space–time processing, the directions of arrival of far-field sources is estimated directly without mutual coupling elimination. Addition, the joint space–time processing can improve the estimation results in the case of low signal noise ratio of incoming signal sources and small number of snapshots. Then, these estimates are adopted to reconstruct the mutual coupling matrix. Finally, both direction and range parameters of near-field sources are obtained through spatial search after mutual coupling effects and far-field components elimination. The proposed algorithm is described in detail, and its behavior is illustrated by numerical examples.

Mixed near field and far field sources localization algorithm based on MEMS vector hydrophone array

Measurement ◽  
2020 ◽  
Vol 151 ◽  
pp. 107109 ◽  
Author(s):  
Zhenzhen Shang ◽  
Wendong Zhang ◽  
Guojun Zhang ◽  
Xiaoyong Zhang ◽  
Songxiang Ji ◽  
...  
Keyword(s):  
Near Field ◽  
Far Field ◽  
Localization Algorithm ◽  
Vector Hydrophone ◽  
Hydrophone Array

Passive localisation of mixed far‐field and near‐field sources using uniform circular array

2016 ◽  
Vol 52 (20) ◽  
pp. 1690-1692 ◽  
Author(s):  
Bing Xue ◽  
Guangyou Fang ◽  
Yicai Ji
Keyword(s):  
Near Field ◽  
Far Field ◽  
Circular Array

A Low Complexity Localization Algorithm for Mixed Far-Field and Near-Field Sources

2021 ◽  
pp. 1-1
Author(s):  
Zhikai Huang ◽  
Bing Xue ◽  
Wei Wang ◽  
Fuwang Dong ◽  
Di Wang
Keyword(s):  
Near Field ◽  
Low Complexity ◽  
Far Field ◽  
Localization Algorithm

A One-Snapshot Localization Algorithm for Mixed Far-Field and Near-Field Sources

2020 ◽  
Vol 24 (5) ◽  
pp. 1010-1014
Author(s):  
Zhikai Huang ◽  
Wei Wang ◽  
Fuwang Dong ◽  
Di Wang
Keyword(s):  
Near Field ◽  
Far Field ◽  
Localization Algorithm

scholarly journals Mixed Far-Field and Near-Field Source Localization Algorithm via Sparse Subarrays

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Jiaqi Song ◽  
Haihong Tao ◽  
Jian Xie ◽  
Chenwei Sun
Keyword(s):  
Near Field ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Far Field ◽  
Localization Algorithm ◽  
Range Estimation ◽  
Field Source ◽  
Quarter Wavelength ◽  
Shift Invariance ◽  
Array Aperture

Based on a dual-size shift invariance sparse linear array, this paper presents a novel algorithm for the localization of mixed far-field and near-field sources. First, by constructing a cumulant matrix with only direction-of-arrival (DOA) information, the proposed algorithm decouples the DOA estimation from the range estimation. The cumulant-domain quarter-wavelength invariance yields unambiguous estimates of DOAs, which are then used as coarse references to disambiguate the phase ambiguities in fine estimates induced from the larger spatial invariance. Then, based on the estimated DOAs, another cumulant matrix is derived and decoupled to generate unambiguous and cyclically ambiguous estimates of range parameter. According to the coarse range estimation, the types of sources can be identified and the unambiguous fine range estimates of NF sources are obtained after disambiguation. Compared with some existing algorithms, the proposed algorithm enjoys extended array aperture and higher estimation accuracy. Simulation results are given to validate the performance of the proposed algorithm.

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