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

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.

Magnetic Tag Antenna for UHF Near-field and Far-Field RFID Applications

2015 ◽  
Vol 5 (2) ◽  
pp. 119
Author(s):  
Mondher Dhaouadi ◽  
M. Mabrouk ◽  
T. Vuong ◽  
A. Ghazel
Keyword(s):  
Near Field ◽  
Far Field ◽  
Rfid Applications

Far field modeling of the Mamala Bay outfalls

1998 ◽  
Vol 38 (10) ◽  
pp. 323-330
Author(s):  
Philip J. W. Roberts
Keyword(s):  
Field Model ◽  
Near Field ◽  
Far Field ◽  
Field Modeling ◽  
Visitation Frequency ◽  
Statistical Variation ◽  
Long Time ◽  
Harmonic Average ◽  
Ocean Outfall ◽  
Acoustic Doppler Current Profilers

The results of far field modeling of the wastefield formed by the Sand Island, Honolulu, ocean outfall are presented. A far field model, FRFIELD, was coupled to a near field model, NRFIELD. The input data for the models were long time series of oceanographic observations over the whole water column including currents measured by Acoustic Doppler Current Profilers and density stratification measured by thermistor strings. Thousands of simulations were made to predict the statistical variation of wastefield properties around the diffuser. It was shown that the visitation frequency of the wastefield decreases rapidly with distance from the diffuser. The spatial variation of minimum and harmonic average dilutions was also predicted. Average dilution increases rapidly with distance. It is concluded that any impact of the discharge will be confined to a relatively small area around the diffuser and beach impacts are not likely to be significant.

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