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 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.

scholarly journals Gridless Sparse Direction Finding Method for Correlated Signals with Gain-Phase Errors

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 557 ◽  
Author(s):  
Xuan Zhang ◽  
Linxi Liu ◽  
Peng Chen ◽  
Zhenxin Cao ◽  
Zhimin Chen
Keyword(s):  
Optimization Problem ◽  
Schur Complement ◽  
Doa Estimation ◽  
Direction Finding ◽  
Phase Errors ◽  
Sparse System ◽  
Atomic Norm ◽  
Correlated Signals ◽  
Finding Method ◽  
Better Than

In practical array systems, the gain-phase errors among antennas degrade the performance of direction finding significantly. In this paper, a novel sparse system model for direction of arrival (DOA) estimation in the scenario with gain-phase errors is proposed by exploiting the signal sparsity in the spatial domain. In contrast to the existing sparse-based methods using the grids to construct the dictionary matrix, a novel gridless method based on atomic norm and convex optimization is proposed, where the gain-phase errors are described by a diagonal matrix. With the Schur complement, a semidefinite programming is formulated from the optimization problem, and can be solved efficiently. With the gain-phase errors, the corresponding Cram’er-Rao lower bound (CRLB) of direction finding is derived as an estimation benchmark. Simulation results show that the proposed method performs better than the state-of-the-art methods in the scenario with correlated signals and gain-phase errors.

DOA Estimation for Uniform Linear Array with Compressive Sensing

2015 ◽  
Vol 713-715 ◽  
pp. 1239-1243
Author(s):  
Ying Zhang ◽  
Guang Yao Xin ◽  
Xiao Fei Zhang
Keyword(s):  
Compressive Sensing ◽  
Linear Array ◽  
Signal To Noise Ratio ◽  
High Sensitivity ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Signal To Noise ◽  
Uniform Linear Array ◽  
High Demand ◽  
Estimation Algorithms

This paper discusses that the application of compressive sensing in direction of arrival (DOA) estimation. Traditional DOA estimation algorithms, such as MUSIC, ESPRIT, have shortcomings of high demand of initialization and sufficient number of snapshots and high sensitivity to signal-to-noise ratio (SNR). The proposed DOA estimation algorithm via OMP method based on compressed sensing (CS) can solve the above-mentioned problem and has good estimation performance. Computer simulations verify the effectiveness of the OMP algorithm.

2D-DOA Estimation for MIMO Radar on Monostatic L-Shaped Minimum-Redundancy Linear Arrays

2014 ◽  
Vol 926-930 ◽  
pp. 2871-2875
Author(s):  
Ying Li ◽  
Gong Zhang
Keyword(s):  
High Efficiency ◽  
Linear Array ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Radar System ◽  
Signal Classification ◽  
Multiple Signal Classification ◽  
Linear Arrays ◽  
2D Doa Estimation ◽  
Better Than

This paper discussed the problem of two dimensional (2D) direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar. The minimum-redundancy linear array (MLRA) is introduced into the transmitting array and receiving array, which enables the high efficiency of the radar system. By utilizing the algorithm of multiple signal classification (MUSIC), we illustrate that the proposed scheme performs better than the uniform linear arrays (ULA) configuration under the same conditions. Simulation results verify the effectiveness of our scheme.

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