A Novel AoA Estimation Algorithm Based on Phase Compensation of Linear Array

2019 ◽  
pp. 179-186
Author(s):  
Xiaolong Yang ◽  
Yuan She ◽  
Jiacheng Wang ◽  
Mu Zhou ◽  
Zengshan Tian
Keyword(s):  
Linear Array ◽  
Estimation Algorithm ◽  
Phase Compensation

scholarly journals DOA Estimation for Coprime Linear Array Based on MI-ESPRIT and Lookup Table

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3043 ◽  
Author(s):  
Weike Zhang ◽  
Xi Chen ◽  
Kaibo Cui ◽  
Tao Xie ◽  
Naichang Yuan
Keyword(s):  
Linear Array ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Spatial Spectrum ◽  
Angle Measurement ◽  
Lookup Table ◽  
Signal Parameters ◽  
Estimation Precision ◽  
Simulation Results ◽  
The Relationship

In order to improve the angle measurement performance of a coprime linear array, this paper proposes a novel direction-of-arrival (DOA) estimation algorithm for a coprime linear array based on the multiple invariance estimation of signal parameters via rotational invariance techniques (MI-ESPRIT) and a lookup table method. The proposed algorithm does not require a spatial spectrum search and uses a lookup table to solve ambiguity, which reduces the computational complexity. To fully use the subarray elements, the DOA estimation precision is higher compared with existing algorithms. Moreover, the algorithm avoids the matching error when multiple signals exist by using the relationship between the signal subspace of two subarrays. Simulation results verify the effectiveness of the proposed algorithm.

Under the Uniform Linear Array Related Research of Broadband Signal DOA Estimation Algorithm

2014 ◽  
Vol 513-517 ◽  
pp. 2698-2701
Author(s):  
Fa Tang Chen ◽  
Lu Gang Wang ◽  
Dan Wang
Keyword(s):  
Frequency Band ◽  
Linear Array ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Signal Frequency ◽  
Music Algorithm ◽  
Uniform Linear Array ◽  
Narrowband Signal ◽  
Broadband Signal ◽  
Signal Doa Estimation

In order to solve the positioning problem of radar and communications, broadband signal and improve the positioning accuracy, this paper proposes a method of DOA estimation under uniform linear array, the method based on fast Fourier transform, using narrowband MUSIC algorithm principle, the broadband signal decomposition for multiple narrowband signal frequency band, and then for each frequency band for narrowband signal DOA estimation. The simulation results show that the algorithm has good performance.

DOA Estimation Algorithm for Non-Uniform Linear Array with Parallel Factor and Power Loading

2014 ◽  
Vol 556-562 ◽  
pp. 3361-3364
Author(s):  
Chi Jiang ◽  
Xiao Fei Zhang ◽  
Li Cen Zhang
Keyword(s):  
Linear Array ◽  
Simulation Analysis ◽  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Signal Source ◽  
Signal To Noise ◽  
Uniform Linear Array ◽  
Power Loading ◽  
Parallel Factor

The algorithm of DOA estimation for non-uniform linear array with Parallel Factor (PARAFAC) and power loading is carried out detailed studies and simulation in this paper, and we use Trilinear Alternating Least Squares (TALS) estimation algorithm to estimate the DOA of signal source. In addition, we make a simulation analysis and comparison of different parameters (Signal-to-noise ratio, the number of snapshots, the number of antenna elements, the number of targets, the similar angles) and different algorithm. Finally the thesis summarizes the work.

scholarly journals Off-Grid DoA Estimation on Non-Uniform Linear Array Using Constrained Hermitian Matrix

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5775
Author(s):  
Hyeonjin Chung ◽  
Jeungmin Joo ◽  
Sunwoo Kim
Keyword(s):  
Toeplitz Matrix ◽  
Linear Array ◽  
Hermitian Matrix ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Uniform Linear Array ◽  
Atomic Norm ◽  
Array Structures ◽  
Simulation Results

In this paper, an off-grid direction-of-arrival (DoA) estimation algorithm which can work on a non-uniform linear array (NULA) is proposed. The original semidefinite programming (SDP) representation of the atomic norm exploits a summation of one-rank matrices constructed by atoms, where the summation of one-rank matrices equals a Hermitian Toeplitz matrix when using the uniform linear array (ULA). On the other hand, when the antennas in the array are placed arbitrarily, the summation of one-rank matrices is a Hermitian matrix whose diagonal elements are equivalent. Motivated by this property, the proposed algorithm replaces the Hermitian Toeplitz matrix in the original SDP with the constrained Hermitian matrix. Additionally, when the antennas are placed symmetrically, the performance can be enforced by adding extra constraints to the Hermitian matrix. The simulation results show that the proposed algorithm achieves higher estimation accuracy and resolution than other algorithms on both array structures; i.e., the arbitrary array and the symmetric array.

An Efficient DOA Estimation Algorithm for Spatial-Temporal Correlated Sources

2013 ◽  
Vol 716 ◽  
pp. 554-558
Author(s):  
Xiang Yang Huang ◽  
Ming Shun Ai ◽  
Peng Peng Yu
Keyword(s):  
Linear Array ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Mean Value ◽  
Algebraic Solution ◽  
The Novel ◽  
Correlated Sources ◽  
Nonzero Mean ◽  
Correlated Signals ◽  
Better Than

This paper presents a signal direction-of-arrival (DOA) estimation approach that possesses excellent performance in spatial and temporal correlated signals environments. Firstly, an algebraic solution of the null subspace is derived based on the Vandermonde structured steering vectors of uniform linear array when all the sources possess identical nonzero mean value, and then, the DOA estimation is obtained with a polynomial rooting method. The novel algorithm performs much better than the conventional algorithms in the situation that the sources are closely spaced or correlated, and simulations have verified the validity of the algorithm.

scholarly journals Channel state information-based multi-dimensional parameter estimation for massive RF data in smart environments

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xiaolong Yang ◽  
Yuan She ◽  
Liangbo Xie ◽  
Zhaoyu Li
Keyword(s):  
Parameter Estimation ◽  
Channel State Information ◽  
Linear Array ◽  
Estimation Algorithm ◽  
Sampling Theorem ◽  
Spatial Sampling ◽  
Channel State ◽  
State Information ◽  
Signal Parameters ◽  
Parameter Estimation Algorithm

AbstractSmart environment sensing and other applications play a more and more important role along with the rapid growth of device-free sensing-based services, and extracting parameters contained in channel state information (CSI) accurately is the basis of these applications. However, antenna arrays in wireless devices are all planar arrays whose antenna spacing does not meet the spatial sampling theorem while the existing parameter estimation methods are almost based on the array satisfying the spatial sampling theorem. In this paper, we propose a parameter estimation algorithm to estimate the signal parameters of angle of arrival (AoA), time of flight (ToF), and Doppler frequency shift (DFS) based on the service antenna array, which does not satisfy the spatial sampling theorem. Firstly, the service antenna array is mapped to a virtual linear array and the array manifold of the virtual linear array is calculated. Secondly, the virtual linear array is applied to estimate the multi-dimensional parameters of the signal. Finally, by calculating the geometric relationship between the service antenna and the virtual linear array, the parameters of the signal incident on the service antenna can be obtained. Therefore, the service antenna can not only use the communication channel for information communication, but also sense the surrounding environment and provide related remote sensing and other wireless sensing application services. Simulation results show that the proposed parameter estimation algorithm can accurately estimate the signal parameters when the array antenna spacing does not meet the spatial sampling theorem. Compared with TWPalo, the proposed algorithm can estimate AoA within 3∘, while the error of ToF and DFS parameter estimation is within 1 ns and 1 m/s.

scholarly journals A Conceptual Framework for the Use of Minimum Redundancy Linear Arrays and Flexible Arrays in Future Smartphones

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ashish Patwari ◽  
G. Ramachandra Reddy
Keyword(s):  
Conceptual Framework ◽  
Linear Array ◽  
Array Processing ◽  
Uniform Linear Array ◽  
Phase Compensation ◽  
Linear Arrays ◽  
Array Pattern ◽  
Conformal Arrays ◽  
Processing Modes ◽  
Area Of Application

This work applies existing array processing principles to devise a new area of application. The properties of minimum redundancy linear arrays (MRLAs) and flexible arrays are studied, keeping in mind the possibility of using them in flexible 5G smartphones of the future. Millimeter frequencies for 5G communications enabled the use of a decent number of array elements, even at the user equipment (UE). MRLAs possess attractive properties among linear sparse arrays and flexible conformal arrays (flexible arrays) operate satisfactorily even when the surface they are built into changes shape. To the best of our knowledge, MRLAs were not applied to smartphones previously. In this work, a 16-element uniform linear array (ULA) and a 7-element MRLA (with the same aperture) are considered for simulations. Array factors of both the arrays in flat and bent positions have been computed using MATLAB. The effect of phase compensation and bending radii on the array pattern were verified. That phase compensation using the projection method (PM) restores the array pattern even for a bent MRLA is a major finding. Possible array processing modes have been suggested for a 5G smartphone in which the array could be made to operate in any of the four configurations: a flat ULA, a bent ULA, a flat MRLA, and a bent MRLA.

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