scholarly journals Nested Hybrid Cylindrical Array Design and DoA Estimation for Massive IoT Networks

Author(s):  
Zhipeng Lin ◽  
Tiejun Lv ◽  
Wei Ni ◽  
J. Andrew Zhang ◽  
Ren Ping Liu
2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hao Feng ◽  
Lutao Liu ◽  
Biyang Wen

Most conventional direction-of-arrival (DOA) estimation algorithms are affected by the effect of mutual coupling, which make the performance of DOA estimation degrade. In this paper, a novel DOA estimation algorithm for conformal array in the presence of unknown mutual coupling is proposed. The special mutual coupling matrix (MCM) is applied to eliminate the effect of mutual coupling. With suitable array design, the decoupling between polarization parameter and angle information is accomplished. The two-demission DOA (2D-DOA) estimation is finally achieved based on estimation of signal parameters via rotational invariance techniques (ESPRIT). The proposed algorithm can be extended to conical conformal array as well. Two parameter pairing methods are illustrated for cylindrical and conical conformal array, respectively. The computer simulation verifies the effectiveness of the proposed algorithm.


2021 ◽  
pp. 103268
Author(s):  
Xiangnan Li ◽  
Weijiang Wang ◽  
Xiaohua Wang ◽  
Shiwei Ren

Author(s):  
Xianxiang Yu Xianxiang Yu ◽  
Cuiguo Long Cuiguo Long ◽  
Shangwei Gao Shangwei Gao ◽  
Lingjiang Kong Lingjiang Kong

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Changbo Ye ◽  
Luo Chen ◽  
Beizuo Zhu

In this paper, a sparse array design problem for non-Gaussian signal direction of arrival (DOA) estimation is investigated. Compared with conventional second-order cumulant- (SOC-) based methods, fourth-order cumulant- (FOC-) based methods achieve improved DOA estimation performance by utilizing all information from received non-Gaussian sources. Considering the virtual sensor location of vectorized FOC-based methods can be calculated from the second order difference coarray of sum coarray (2-DCSC) of physical sensors, it is important to devise a sparse array design principle to obtain extended degree of freedom (DOF). Based on the properties of unfolded coprime linear array (UCLA), we formulate the sparse array design problem as a global postage-stamp problem (GPSP) and then present an array design method from GPSP perspective. Specifically, for vectorized FOC-based methods, we divide the process of obtaining physical sensor location into two steps; the first step is to obtain the two consecutive second order sum coarrays (2-SC), which can be modeled as GPSP, and the solutions to GPSP can also be utilized to determine the physical sensor location sets without interelement spacing coefficients. The second step is to adjust the physical sensor sets by multiplying the appropriate coprime coefficients, which is determined by the structure of UCLA. In addition, the 2-DCSC can be calculated from physical sensors directly, and the properties of UCLA are given to confirm the degree of freedom (DOF) of the proposed geometry. Simulation results validate the effectiveness and superiority of the proposed array geometry.


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