A New Near-Field Source Localization Algorithm without Pairing Parameters

2006 ◽  
Author(s):  
Junli Liang ◽  
Shuyuan Yang ◽  
Junying Zhang
Keyword(s):  
Source Localization ◽  
Near Field ◽  
Localization Algorithm ◽  
Field Source

scholarly journals Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm

Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 1066 ◽  
Author(s):  
Sen Li ◽  
Bing Li ◽  
Bin Lin ◽  
Xiaofang Tang ◽  
Rongxi He
Keyword(s):  
Source Localization ◽  
Near Field ◽  
Sparse Reconstruction ◽  
Localization Algorithm ◽  
Field Source

Statistical analysis of achievable resolution limit in the near field source localization context

2012 ◽  
Vol 92 (2) ◽  
pp. 547-552 ◽  
Author(s):  
Mohammed Nabil El Korso ◽  
Rémy Boyer ◽  
Alexandre Renaux ◽  
Sylvie Marcos
Keyword(s):  
Statistical Analysis ◽  
Source Localization ◽  
Near Field ◽  
Resolution Limit ◽  
Field Source

scholarly journals Efficient Localization Algorithm for Near-Field Noncircular Sources via Dual-Polarization Sensor Array

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Jiaqi Song ◽  
Haihong Tao
Keyword(s):  
Source Localization ◽  
Near Field ◽  
Nuisance Parameter ◽  
Estimation Accuracy ◽  
Localization Algorithm ◽  
Dual Polarization ◽  
Rank Reduction ◽  
Localization Accuracy ◽  
Noncircular Signals ◽  
Polarization Sensor

Noncircular signals are widely used in the area of radar, sonar, and wireless communication array systems, which can offer more accurate estimates and detect more sources. In this paper, the noncircular signals are employed to improve source localization accuracy and identifiability. Firstly, an extended real-valued covariance matrix is constructed to transform complex-valued computation into real-valued computation. Based on the property of noncircular signals and symmetric uniform linear array (SULA) which consist of dual-polarization sensors, the array steering vectors can be separated into the source position parameters and the nuisance parameter. Therefore, the rank reduction (RARE) estimators are adopted to estimate the source localization parameters in sequence. By utilizing polarization information of sources and real-valued computation, the maximum number of resolvable sources, estimation accuracy, and resolution can be improved. Numerical simulations demonstrate that the proposed method outperforms the existing methods in both resolution and estimation accuracy.

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