Localization of Near-Field Signals Based on Linear Prediction and Oblique Projection Operator

2018 ◽  
Author(s):  
Wenyi Liu ◽  
Weiliang Zuo ◽  
Jingmin Xin ◽  
Nanning Zheng ◽  
Akira Sano
Keyword(s):  
Projection Operator ◽  
Linear Prediction ◽  
Near Field ◽  
Oblique Projection

Localization of Near-Field Sources Based on Linear Prediction and Oblique Projection Operator

2019 ◽  
Vol 67 (2) ◽  
pp. 415-430 ◽  
Author(s):  
Weiliang Zuo ◽  
Jingmin Xin ◽  
Wenyi Liu ◽  
Nanning Zheng ◽  
Hiromitsu Ohmori ◽  
...  
Keyword(s):  
Projection Operator ◽  
Linear Prediction ◽  
Near Field ◽  
Oblique Projection

A weighted linear prediction method for near-field source localization

2005 ◽  
Vol 53 (10) ◽  
pp. 3651-3660 ◽  
Author(s):  
E. Grosicki ◽  
K. Abed-Meraim ◽  
Yingbo Hua
Keyword(s):  
Source Localization ◽  
Linear Prediction ◽  
Near Field ◽  
Prediction Method ◽  
Field Source

scholarly journals A Novel Method Based on Oblique Projection Technology for Mixed Sources Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Weijian Si ◽  
Xiaolin Li ◽  
Yilin Jiang ◽  
Liangtian Wan
Keyword(s):  
Array Signal Processing ◽  
Near Field ◽  
Location Estimation ◽  
Noise Power ◽  
Oblique Projection ◽  
Computation Complexity ◽  
Range Estimation ◽  
Localization Algorithms ◽  
Partial Area ◽  
Novel Method

Reducing the computational complexity of the near-field sources and far-field sources localization algorithms has been considered as a serious problem in the field of array signal processing. A novel algorithm caring for mixed sources location estimation based on oblique projection is proposed in this paper. The sources are estimated at two different stages and the sensor noise power is estimated and eliminated from the covariance which improve the accuracy of the estimation of mixed sources. Using the idea of compress, the range information of near-field sources is obtained by searching the partial area instead of the whole Fresnel area which can reduce the processing time. Compared with the traditional algorithms, the proposed algorithm has the lower computation complexity and has the ability to solve the two closed-spaced sources with high resolution and accuracy. The duplication of range estimation is also avoided. Finally, simulation results are provided to demonstrate the performance of the proposed method.

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