scholarly journals Two-Dimensional DOA Estimation in Compressed Sensing with Compressive-Reduced Dimension-lp-MUSIC

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Weijian Si ◽  
Xinggen Qu ◽  
Lutao Liu ◽  
Zhiyu Qu
Keyword(s):  
Compressed Sensing ◽  
Estimation Method ◽  
Doa Estimation ◽  
Superior Performance ◽  
Two Dimensional ◽  
Improve Performance ◽  
Performance Simulation ◽  
Pair Matching ◽  
Reduced Dimension ◽  
Simulation Results

This paper presents a novel two-dimensional (2D) direction of arrival (DOA) estimation method in compressed sensing (CS) to remove the estimation failure problem and achieve superior performance. The proposed method separates the steering vector into two parts to construct two corresponding noise subspaces by introducing electric angles. Then, electric angles are estimated based on the constructed noise subspaces. In order to estimate the azimuth and elevation angles in terms of estimates of electric angles, arc-tangent operations are exploited. The arc-tangent is a one-to-one function and allows the value of the argument to be larger than unity so that the proposed method never fails. The proposed method can avoid pair matching to reduce the computational complexity and extend the number of snapshots to improve performance. Simulation results show that the proposed method can avoid estimation failure occurrence and has superior performance as compared to existing methods.

scholarly journals DOA Estimation for Mixed Uncorrelated and Coherent Sources in Multipath Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Heping Shi ◽  
Wen Leng ◽  
Anguo Wang ◽  
Tongfeng Guo
Keyword(s):  
Linear Array ◽  
Estimation Method ◽  
Doa Estimation ◽  
Spatial Smoothing ◽  
Uniform Linear Array ◽  
Performance Simulation ◽  
Coherent Sources ◽  
Multipath Environment ◽  
Simulation Results ◽  
Effectiveness And Efficiency

A novel direction-of-arrival (DOA) estimation method is proposed to cope with the scenario where a number of uncorrelated and coherent narrowband sources simultaneously impinge on the far-field of a uniform linear array (ULA). In the proposed method, the DOAs of uncorrelated sources are firstly estimated by utilizing the property of the moduli of eigenvalues of the DOA matrix. Afterwards, the contributions of uncorrelated sources and the interference of noise are eliminated completely by exploiting the improved spatial differencing technique and only the coherent components remain in the spatial differencing matrix. Finally, the remaining coherent sources can be resolved by performing the improved spatial smoothing scheme on the spatial differencing matrix. The presented method can resolve more number of sources than that of the array elements and distinguish the uncorrelated and coherent sources that come from the same direction as well as improving the estimation performance. Simulation results demonstrate the effectiveness and efficiency of the proposed method.

scholarly journals Multiple Sparse Measurement Gradient Reconstruction Algorithm for DOA Estimation in Compressed Sensing

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Weijian Si ◽  
Xinggen Qu ◽  
Yilin Jiang ◽  
Tao Chen
Keyword(s):  
Convex Optimization ◽  
Compressed Sensing ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Reconstruction Algorithm ◽  
Doa Estimation ◽  
Superior Performance ◽  
Multiple Measurement Vectors ◽  
Gradient Reconstruction ◽  
Quadratically Constrained

A novel direction of arrival (DOA) estimation method in compressed sensing (CS) is proposed, in which the DOA estimation problem is cast as the joint sparse reconstruction from multiple measurement vectors (MMV). The proposed method is derived through transforming quadratically constrained linear programming (QCLP) into unconstrained convex optimization which overcomes the drawback thatl1-norm is nondifferentiable when sparse sources are reconstructed by minimizingl1-norm. The convergence rate and estimation performance of the proposed method can be significantly improved, since the steepest descent step and Barzilai-Borwein step are alternately used as the search step in the unconstrained convex optimization. The proposed method can obtain satisfactory performance especially in these scenarios with low signal to noise ratio (SNR), small number of snapshots, or coherent sources. Simulation results show the superior performance of the proposed method as compared with existing methods.

scholarly journals Reduced-Dimension Noncircular-Capon Algorithm for DOA Estimation of Noncircular Signals

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Weihua Lv ◽  
Huapu Sun ◽  
Xiaofei Zhang ◽  
Dazhuan Xu
Keyword(s):  
Computational Cost ◽  
Doa Estimation ◽  
Two Dimensional ◽  
Angle Estimation ◽  
One Dimensional ◽  
Reduced Dimension ◽  
Noncircular Signals ◽  
Simulation Results ◽  
High Computational Cost ◽  
Better Than

The problem of the direction of arrival (DOA) estimation for the noncircular (NC) signals, which have been widely used in communications, is investigated. A reduced-dimension NC-Capon algorithm is proposed hereby for the DOA estimation of noncircular signals. The proposed algorithm, which only requires one-dimensional search, can avoid the high computational cost within the two-dimensional NC-Capon algorithm. The angle estimation performance of the proposed algorithm is much better than that of the conventional Capon algorithm and very close to that of the two-dimensional NC-Capon algorithm, which has a much higher complexity than the proposed algorithm. Furthermore, the proposed algorithm can be applied to arbitrary arrays and works well without estimating the noncircular phases. The simulation results verify the effectiveness and improvement of the proposed algorithm.

scholarly journals An Enhanced Smoothed L0-Norm Direction of Arrival Estimation Method Using Covariance Matrix

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4403
Author(s):  
Ji Woong Paik ◽  
Joon-Ho Lee ◽  
Wooyoung Hong
Keyword(s):  
Covariance Matrix ◽  
Phased Array ◽  
Null Space ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Improve Performance ◽  
Space Projection

An enhanced smoothed l0-norm algorithm for the passive phased array system, which uses the covariance matrix of the received signal, is proposed in this paper. The SL0 (smoothed l0-norm) algorithm is a fast compressive-sensing-based DOA (direction-of-arrival) estimation algorithm that uses a single snapshot from the received signal. In the conventional SL0 algorithm, there are limitations in the resolution and the DOA estimation performance, since a single sample is used. If multiple snapshots are used, the conventional SL0 algorithm can improve performance in terms of the DOA estimation. In this paper, a covariance-fitting-based SL0 algorithm is proposed to further reduce the number of optimization variables when using multiple snapshots of the received signal. A cost function and a new null-space projection term of the sparse recovery for the proposed scheme are presented. In order to verify the performance of the proposed algorithm, we present the simulation results and the experimental results based on the measured data.

scholarly journals Compressed Sensing-Based DOA Estimation with Unknown Mutual Coupling Effect

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 424 ◽  
Author(s):  
Peng Chen ◽  
Zhenxin Cao ◽  
Zhimin Chen ◽  
Linxi Liu ◽  
Man Feng
Keyword(s):  
Compressed Sensing ◽  
Mutual Coupling ◽  
Linear Array ◽  
State Of The Art ◽  
Coupling Effect ◽  
Estimation Method ◽  
Doa Estimation ◽  
System Model ◽  
Reconstruction Problem ◽  
Uniform Linear Array

The performance of a direction-finding system is significantly degraded by the imperfection of an array. In this paper, the direction-of-arrival (DOA) estimation problem is investigated in the uniform linear array (ULA) system with the unknown mutual coupling (MC) effect. The system model with MC effect is formulated. Then, by exploiting the signal sparsity in the spatial domain, a compressed-sensing (CS)-based system model is proposed with the MC coefficients, and the problem of DOA estimation is converted into that of a sparse reconstruction. To solve the reconstruction problem efficiently, a novel DOA estimation method, named sparse-based DOA estimation with unknown MC effect (SDMC), is proposed, where both the sparse signal and the MC coefficients are estimated iteratively. Simulation results show that the proposed method can achieve better performance of DOA estimation in the scenario with MC effect than the state-of-the-art methods, and improve the DOA estimation performance about 31.64 % by reducing the MC effect by about 4 dB.

scholarly journals DOA Tracking of Two-Dimensional Coherent Distribution Source Based on Fast Approximated Power Iteration

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Tao Wu ◽  
Pengtao Zhang ◽  
Yiwen Li ◽  
Yangjun Gao ◽  
Chaoqi Fu ◽  
...  
Keyword(s):  
Estimation Method ◽  
Doa Estimation ◽  
Distribution Functions ◽  
Tracking Algorithm ◽  
Signal Subspace ◽  
Two Dimensional ◽  
Model Errors ◽  
Rectangular Array ◽  
Linear Arrays ◽  
Power Iteration

Aiming at two-dimensional (2D) coherent distributed (CD) sources, this paper has proposed a direction of arrival (DOA) tracking algorithm based on signal subspace updating under the uniform rectangular array (URA). First, based on the hypothesis of small angular spreads of distributed sources, the rotating invariant relations of the signal subspace of the receive vector of URA are derived. An ESPRIT-like method is constructed for DOA estimation using two adjacent parallel linear arrays of URA. Through the synthesis of estimation by multiple groups of parallel linear arrays within URA arrays, the DOA estimation method for 2D CD sources based on URA is obtained. Then, fast approximated power iteration (FAPI) subspace tracking algorithm is used to update the signal subspace. In this way, DOA tracking of 2D CD sources can be realized by DOA estimation through signal subspace updating. This algorithm has a low computational complexity and good real-time tracking performance. In addition, the algorithm can track multiple CD sources without knowing the angular signal distribution functions, which is robust to model errors.

scholarly journals Performance Evaluation of Acoustic Underwater Data Broadcasting Exploiting the Bandwidth-Distance Relationship

2011 ◽  
Vol 7 (4) ◽  
pp. 285-298 ◽  
Author(s):  
P. Nicopolitidis ◽  
K. Christidis ◽  
G. I. Papadimitriou ◽  
P. G. Sarigiannidis ◽  
A. S. Pomportsis
Keyword(s):  
Performance Evaluation ◽  
Superior Performance ◽  
Data Broadcasting ◽  
Improve Performance ◽  
Underwater Acoustic ◽  
Underwater Environment ◽  
Simulation Results ◽  
Distance Relationship ◽  
Characteristic Relationship ◽  
Receiver Distance

Despite being a fundamental networking primitive, data broadcasting has so far received little attention in the context of underwater networks. This paper proposes an adaptive push system for data broadcasting in underwater acoustic wireless networks with locality of client demands. The proposed system exploits the characteristic relationship between the bandwidth of an underwater acoustic link and the transmitter-receiver distance in order to improve performance in environments with locality of client demands. Simulation results show superior performance of the proposed approach in the underwater environment compared to existing systems.

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