A Differential Evolution Approach for Robust Adaptive Beamforming Based on Joint Estimation of Look Direction and Array Geometry

Mallipeddi, Rammohan; Lie, Joni Polili; Suganthan, Ponnuthurai Nagaratnam; Razul, Sirajudeen Gulam; See, Chong Meng Samson

doi:10.2528/pier11052205

Cited by 35 publications

(29 citation statements)

References 38 publications

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“…Unequally spaced linear array synthesis with side lobe suppression under constraints to beam width and null control using a design technique based on a comprehensive learning particle swarm optimizer (CLPSO) is presented in [6]. Differential evolution algorithm is used in the synthesis of antenna arrays in [8][9][10]. Planar antenna arrays have much more elements and the radiation patterns are more complex.…”

Section: Introductionmentioning

confidence: 99%

Pattern Synthesis of Concentric Circular Antenna Array by Nonlinear Least-Square Method

Guo¹,

Guo²,

Qu³

et al. 2013

PIER B

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Abstract-An improved nonlinear least-square method is presented in this paper. This method changes the traditional least-square method's shortness of being sensitive to its initial conditions. Pattern synthesis for concentric circular arrays using nonlinear least-square method is introduced. The excitation amplitudes and phases of the array elements are optimized. This method can make the design of the feeding network much easier because the excitation amplitudes of the elements placed on the same ring are equal. The number of parameters to be optimized is reduced which leads to a faster simulation speed and makes the simulation results much more accurate. Also, the cost of designing the feeding network is reduced. The simulation results show the good agreement between the synthesized and desired radiation pattern. Also, the peak side lobe level (PSLL) of the synthesized radiation pattern is quite low.

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Section: Introductionmentioning

confidence: 99%

Pattern Synthesis of Concentric Circular Antenna Array by Nonlinear Least-Square Method

Guo¹,

Guo²,

Qu³

et al. 2013

PIER B

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“…Therefore global optimization methods are a good option and can be used for auxiliary design. In recent years, many evolutionary algorithms have been proposed for solving design problems in electromagnetics such as differential evolution (DE) [16], particle swarm optimization (PSO) [12,[17][18][19] and genetic algorithm (GA) [20][21][22][23]. Among them, the PSO [12,17,18] and the GA [23] have already been used in power divider designs.…”

Section: Introductionmentioning

confidence: 99%

Design of an Ultra-Wideband Power Divider via the Coarse-Grained Parallel Micro-Genetic Algorithm

Chang¹,

Liao²,

Chen³

et al. 2012

PIER

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Abstract-An ultra-wideband (UWB) power divider is designed in this paper. The UWB performance of this power divider is obtained by using a tapered microstrip line that consists of exponential and elliptic sections. The coarse grained parallel micro-genetic algorithm (PMGA) and CST Microwave Studio are combined to achieve an automated parallel design process. The method is applied to optimize the UWB power divider. The optimized power divider is fabricated and measured. The measured results show relatively low insertion loss, good return loss, and high isolation between the output ports across the whole UWB (3.1-10.6 GHz).

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“…Many advanced methods [2,3] for the localization of point signals attain super-resolution by exploiting the presence of a small number of signals. The most well-known existing nonparametric methods include beamforming [4] and its relevant algorithms [5,6], Capon's method [7], and subspace based methods such as MUSIC [8]. Some additional methods (Root-MUSIC and ESPRIT) [9] are under the assumption that the array of sensors is linear.…”

Section: Introductionmentioning

confidence: 99%

An Improved L1-SVD Algorithm Based on Noise Subspace for Doa Estimation

Liu¹,

Lu²,

Wei³

et al. 2012

PIER C

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Abstract-In this paper, an improved L 1 -SVD algorithm based on noise subspace is presented for direction of arrival (DOA) estimation using reweighted L 1 norm constraint minimization. In the proposed method, the weighted vector is obtained by utilizing the orthogonality between noise subspace and signal subspace spanned by the array manifold matrix. The presented algorithm banishes the nonzero entries whose indices are inside of the row support of the jointly sparse signals by smaller weights and the other entries whose indices are more likely to be outside of the row support of the jointly sparse signals by larger weights. Therefore, the sparsity at the real signal locations can be enhanced by using the presented method. The proposed approach offers a good deal of merits over other DOA techniques. It not only increases robustness to noise, but also enhances resolution in DOA estimation. Furthermore, it is not very sensitive to the incorrect determination of the number of signals and can primely suppress spurious peak in DOA estimation. Simulation results are shown that the presented algorithm has better performance than the existing algorithms, such as MUSIC, L 1 -SVD algorithm.

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A Differential Evolution Approach for Robust Adaptive Beamforming Based on Joint Estimation of Look Direction and Array Geometry

Cited by 35 publications

References 38 publications

Pattern Synthesis of Concentric Circular Antenna Array by Nonlinear Least-Square Method

Pattern Synthesis of Concentric Circular Antenna Array by Nonlinear Least-Square Method

Design of an Ultra-Wideband Power Divider via the Coarse-Grained Parallel Micro-Genetic Algorithm

An Improved L1-SVD Algorithm Based on Noise Subspace for Doa Estimation

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