Title
Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm.
Abstract
Non-Gaussian impulsive noise widely exists in the real world, this paper takes the alpha-stable distribution as the mathematical model of non-Gaussian impulsive noise and works on the joint direction-of-arrival (DOA) and range estimation problem of near-field signals in impulsive noise environment. Since the conventional algorithms based on the classical second order correlation statistics degenerate severely in the impulsive noise environment, this paper adopts two robust correlations, the fractional lower order correlation (FLOC) and the nonlinear transform correlation (NTC), and presents two related near-field localization algorithms. In our proposed algorithms, by exploring the symmetrical characteristic of the array, we construct the robust far-field approximate correlation vector in relation with the DOA only, which allows for bearing estimation based on the sparse reconstruction. With the estimated bearing, the range can consequently be obtained by the sparse reconstruction of the output of a virtual array. The proposed algorithms have the merits of good noise suppression ability, and their effectiveness is demonstrated by the computer simulation results.
Year
DOI
Venue
2018
10.3390/s18041066
SENSORS
Keywords
Field
DocType
near-filed,direction of arrival,range estimation,impulsive noise,sparse reconstruction,robust correlation
Degenerate energy levels,Noise suppression,Direction of arrival,Near and far field,Algorithm,Bearing (mechanical),Correlation,Source localization,Correlation function,Engineering
Journal
Volume
Issue
Citations 
18
4.0
0
PageRank 
References 
Authors
0.34
13
5
Name
Order
Citations
PageRank
Sen Li12711.31
Bing Li200.68
Bin Lin3149.36
Xiaofang Tang400.34
Rongxi He510814.70