Real-Valued 2-D Direction of Arrival Estimation via Sparse Representation (original) (raw)
Related papers
Journal of telecommunications and information technology, 2021
Regular fully filled antenna arrays have been widely used in direction of arrival (DOA) estimation. However, practical implementation of these arrays is rather complex and their resolutions are limited to the beamwidth of the array pattern. Therefore, higher resolution and simpler methods are desirable. In this paper, the compressed sensing method is first applied to an initial fully filled array to randomly select the most prominent and effective elements which are used to form the sparse array. To keep the dimension of the sparse array equal to that of the fully filled array, the first and the last elements were excluded from the sparseness process. In addition, some constraints on the sparse spectrum are applied to increase estimation accuracy. The optimization problem is then solved iteratively using the iterative reweighted l 1 l 1 l 1 norm. Finally, a simple searching algorithm is used to detect peaks in the spectrum solution that correspond to the directions of the arriving signals. Compared with the existing scanned beam methods, such as the minimum variance distortionless response (MVDR) technique, and with subspace approaches, such as multiple signal classification (MUSIC) and ESPIRT algorithms, the proposed sparse array method offers better performance even with a lower number of array elements and in severely noisy environments. Effectiveness of the proposed sparse array method is verified via computer simulations.
Covariance-Based Direction-of-Arrival Estimation With Real Structures
IEEE Signal Processing Letters, 2000
Parametric methods for direction-of-arrival (DoA) estimation have become very popular due to their low computational complexity and good accuracy. Among parametric DoA algorithms, ESPRIT is one of the most widely used, since it presents low computational complexity in comparison to other parametric methods. Covariance-based DoA (CB-DoA) estimation algorithm provides an even lower complexity alternative to ESPRIT, while imposing the same constraints on the geometry of the receiving array. This letter presents a new algorithm, based on the CB-DoA approach, comprising only real operations. The constraints on the algorithm are the same imposed to the unitary ESPRIT algorithm, allowing a reduction of about 67% on the required computational effort, for equivalent error measure.
Two-Dimensional Direction-of-Arrival Estimation for More Sources Than Sensors
2022
In this paper, we investigate the issue of twodimensional (2-D) direction-of-arrival (DOA) estimation of multiple signals in co-prime planar arrays, where phase ambiguity problem arises due to the large distance between adjacent elements for each subarray. According to the co-prime characteristic, the ambiguity problem can be eliminated by searching for the common peaks of the spatial spectrum of each subarray, where the spectrum search involves a tremendous computation burden. In this paper, we exploit the property that all the ambiguous peaks for each DOA are uniformly distributed in a new transformed domain. Relying on the linear relations, we propose a partial spectral search (PSS) based estimation method, where it involves a limited search over only a small sector. Therefore, the proposed PSS method is very computationally efficient. Numerical results are provided to verify the effectiveness of the proposed method over the state-of-the-art methods, in terms of both computational complexity and estimation accuracy.
IEEE Transactions on Antennas and Propagation, 2000
A new hybrid algorithm that combines the uniform circular array-RAnk REduction (UCA-RARE) and Root-MUSIC algorithm for 2-D direction-of-arrival (DOA) estimation of azimuth and elevation angle is presented for uniform circular arrays in the presence of mutual coupling. To describe mutual coupling and platform effects we rely on the circular symmetry and expand the open-circuit voltages into a limited number of phase modes. This number of phase modes only depends on the electromagnetic dimensions of the UCA and is independent of the severity of mutual coupling in the UCA. The UCA-RARE algorithm is then applied to estimate the azimuth angle independent from the elevation angle. Next, for each azimuth angle we perform a new search-free rooting algorithm based on the expansion of the array manifold into a double Fourier series. By considering several examples, it is shown that even in the presence of severe mutual coupling the proposed combined technique yields very robust DOA estimations for azimuth angle as well as for elevation angle.
2-L-Shape Two-Dimensional Arrival Angle Estimation with a Classical Subspace Algorithm
2006 IEEE International Symposium on Industrial Electronics, 2006
This paper proposes a computationally efficient method for a two-dimensional direction of arrival estimation of multiple narrowband sources. We apply the MUSIC method which requires eigenvalues decomposition to the cross spectral matrix. This paper will employ two L-shape arrays that showed better performances than the one L-shape and the parallel shape arrays. In spite of its computational complexity, simulation results verify that the proposed subspace technique gives much better performance than the propagator method.
Direction-of-Arrival Estimation using a Low-Complexity Covariance-Based Approach
IEEE Transactions on Aerospace and Electronic Systems, 2000
This article presents a new algorithm for performing direction-of-arrival (DOA) estimation using manipulations on covariance matrices. The proposed algorithm combines a new formulation for data projection on real subspaces, together with beamspace decompositions, reducing the sizes of all data structures and computational complexity of the resulting estimation process. Theoretical analyses as well as computer simulations indicate that the proposed algorithm reduces its ESPRIT equivalent computational complexity by a minimum of 20%, while presenting similar mean-square error (MSE) performance.
Sparse direction-of-arrival estimation for two sources with constrained antenna arrays
2017 10th International Conference on Electrical and Electronics Engineering (ELECO), 2017
Compressive sensing (CS), multiple signal classification (MUSIC), and estimation of signal parameter via rotational invariance techniques (ESPRIT) are among the main used estimation techniques for direction of arrival (DOA). Though, the practical implementation of DOA techniques in handheld wireless devices is limited by the number of antennas and the spacing between them. A robust DOA estimation technique is needed to overcome the different impairments in the communication channel. This paper mainly focuses on DOA estimation of two sources in the presence of practical limitations. A comparison between important DOA estimation algorithms is presented including: Beamforming, Capon, MUSIC, and First-norm singular value decomposition (l1-SVD).
2005
A new algorithm for 2-D direction-ofarrival estimation of azimuth and elevation angle is presented for uniform circular arrays by combining UCA-RARE and MUSIC in the presence of the mutual coupling. To describe mutual coupling in a uniform circular array we make use of the symmetry of the array and expand the open-circuit voltages into a limited number of spherical modes. The UCA-RARE technique is then applied to estimate the azimuth angle independent from the elevation angle. Next for each azimuth angle we estimate the corresponding elevation angles. Some illustrative examples are given to validate our approach.
Computationally efficient 2D beamspace matrix pencil method for direction of arrival estimation
Digital Signal Processing, 2010
In this paper, we propose a new 2-dimensional beamspace matrix pencil (2D BMP) method for direction of arrival (DOA) estimation of plane wave signals using a uniform rectangular array (URA). Based on some a priori information about DOA, the proposed method transforms the complex signal subspace in 2D matrix pencil (2D MP) method [Y. Hua, Estimating two-dimensional frequencies by matrix enhancement and matrix pencil, IEEE Trans. Signal Process. 40 (9) (1992) 2267-2280] into a real and reduced dimensional beamspace using the discrete Fourier transform (DFT) matrix transformation. Consequently, the computational complexity is reduced (several times) in comparison with 2D MP method. Computer simulations are provided to show that 2D BMP method gives comparable performance in terms of average mean square error of the estimated DOA with lesser floating point operations as compared to the existing (MP) methods.
One-and two-dimensional direction-of-arrival estimation: An overview of search-free techniques
2010
One of major challenges in applying traditional subspace-based direction finding techniques to real-time practical problems is in that they normally require an exhaustive spectral search over the angular parameter(s). Therefore, methods avoiding such a computationally demanding spectral search step are of great interest. In this paper, an overview of one-and two-dimensional search-free direction-of-arrival (DOA) estimation methods is presented. Both cases of uniform and non-uniform sensor arrays are addressed.