Passive Localization of Mixed Far-Field and Near-Field Sources without Estimating the Number of Sources

Sensors

Jian Xie²  Haihong Tao¹  Xuan Rao² 

[1] National Key Laboratory for Radar Signal Processing, School of Electronic Engineering, Xidian University, No.2 Taibai South Road, Xi'an 710071, China;

关键词: sensor array signal processing;    DOA estimation;    far-field;    near-field;    source localization;    range estimation;    fourth-order cumulants;   

DOI  :  10.3390/s150203834

来源: mdpi

【 摘 要 】

This paper presents a novel algorithm for the localization of mixed far-field sources (FFSs) and near-field sources (NFSs) without estimating the source number. Firstly, the algorithm decouples the direction-of-arrival (DOA) estimation from the range estimation by exploiting fourth-order spatial-temporal cumulants of the observed data. Based on the joint diagonalization structure of multiple spatial-temporal cumulant matrices, a new one-dimensional (1-D) spatial spectrum function is derived to generate the DOA estimates of both FFSs and NFSs. Then, the FFSs and NFSs are identified and the range parameters of NFSs are determined via beamforming technique. Compared with traditional mixed sources localization algorithms, the proposed algorithm avoids the performance deterioration induced by erroneous source number estimation. Furthermore, it has a higher resolution capability and improves the estimation accuracy. Computer simulations are implemented to verify the effectiveness of the proposed algorithm.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.