Difference Coarray Design based on Genetic Algorithm and Convex Optimization

Wang, Lening; Zhao, Hangfang

doi:10.1109/coa50123.2021.9520006

Cited by 4 publications

(7 citation statements)

References 12 publications

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“…Archimedean spiral curve provides a better idea to improve the original spiral search strategy, which avoids the reduced accuracy caused by long search steps. Each position dimension of a whale is generated by (11) instead of (10).…”

Section: Archimedean Spiral Strategymentioning

confidence: 99%

“…If p is less than 50%, encircling prey is chosen. Otherwise, the Archimedean spiral strategy is chosen, and the whale position is updated by (11). In encircling prey, the prey is selected to pass by A.…”

Section: Archimedean Spiral Strategymentioning

confidence: 99%

“…Input: Initial chaotic sequences S, maximum iterations t Max , and the minimum spacing d c Output: Optimal individual whale position Determine the new search aperture L * using position decomposition; Initialize X according to search aperture L * using chaotic sequence S; Find the individual position corresponding to the optimal fitness value X * ; while t < t Max or PSLL does not meet demand do Set the parameters a, r, l, p, and calculate A, C.; Update X(t). if p < 0.5 then if |A| < 1 then Enforcing shrinking encircling mechanism and updating position according to (4) and ( 5) ; else Random search using ( 8) and ( 9); else Archimedes spiral strategy using (11); end Set k and n and use refraction learning to find the inverse solution X * (t); If PSLL( X) < PSLL( X * ), choose X as a new population; Otherwise, choose X * as a new population; t = t + 1 end…”

Section: Off-grid Arrays Design Based On Gewoamentioning

confidence: 99%

“…The existing methods to solve the first problem are mainly divided into two categories: deterministic optimization methods and stochastic optimization methods. Deterministic optimization methods, including minimum redundancy array [9], coprime array [10], and difference coarray [11], are easy to implement; however, the designed arrays are generally suboptimal. Stochastic optimization methods use intelligent algorithms to find the element positions that satisfy the design requirements.…”

Section: Introductionmentioning

confidence: 99%

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Underwater Sparse Acoustic Sensor Array Design under Spacing Constraints Based on a Global Enhancement Whale Optimization Algorithm

2022

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Sparse arrays with low cost and engineering complexity are widely applied in many fields. However, the high peak sidelobe level (PSLL) of a sparse array causes the degradation of weak target detection performance. Particularly for the large size of underwater low-frequency sensors, the design problem requires a minimum spacing constraint, which further increases the difficulty of PSLL suppression. In this paper, a novel swarm-intelligence-based approach for sparse sensor array design is proposed to reduce PSLL under spacing constrains. First, a global enhancement whale optimization algorithm (GEWOA) is introduced to improve the global search capability for optimal arrays. A three-step enhanced strategy is used to enhance the ergodicity of element positions over the aperture. In order to solve the adaptation problem for discrete array design, a position decomposition method and a V-shaped transfer function are introduced into off-grid and on-grid arrays, respectively. The effectiveness and superiority of the proposed approach is validated using experiments for designing large-scale low-frequency arrays in the marine environment. The PSLL of the off-grid array obtained by GEWOA was nearly 3.8 dB lower than that of WOA. In addition, compared with other intelligent algorithms, the on-grid array designed using GEWOA had the lowest PSLL.

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Section: Archimedean Spiral Strategymentioning

confidence: 99%

Section: Archimedean Spiral Strategymentioning

confidence: 99%

Section: Off-grid Arrays Design Based On Gewoamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Underwater Sparse Acoustic Sensor Array Design under Spacing Constraints Based on a Global Enhancement Whale Optimization Algorithm

2022

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“…The lowest PSLL is expected to be obtained with a fixed array aperture and a given number of elements. This kind of methods usually uses stochastic search algorithms to perform array design for practical engineering tasks, such as genetic algorithm [8], particle swarm optimisation [9], whale optimisation algorithm [10]. However, the convergence speed of this kind of methods is slow due to the dependency on various constraint factors.…”

Section: Introductionmentioning

confidence: 99%

Sparse hydrophone array synthesis for frequency‐invariant and multi‐angle beampatterns using block‐structured Bayesian compressive sensing

Wang

Zhao

2023

IET Radar Sonar & Navi

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To solve the synthesised accuracy degradation of traditional Bayesian compressive sensing (BCS) in wideband multi‐beam hydrophone array synthesis, a novel sparse array synthesis method based on block‐structure Bayesian compressive sensing (BS‐BCS) is proposed for frequency‐invariant and multi‐angle beampatterns. The multi‐angle beampatterns at different frequencies are synthesised in block structure using the shared position strategy which effectively reduces the number of array elements. In order to meet the minimum spacing requirement of adjacent array elements in practical engineering, the constraint converted off‐grid method is proposed to improve the array synthesis accuracy. The grid scaling is introduced to obtain the possible array element positions. The array positions and weights can be solved by the BCS solver and corrected by Taylor perturbation. To validate the effectiveness and feasibility of the proposed method, simulations and actual experiments are carried out. The synthesised errors and peak sidelobe levels (PSLLs) of multi‐angle beampatterns obtained by the constraint converted off‐grid method outperforms those of other methods. The beamforming results of actual experiments in marine environment show that the PSLLs of the beampatterns obtained by BS‐BCS is lower at least 6.3 dB than that of uniform array, which demonstrates the effectiveness of the proposed method.

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Optimization Design of Landscape Spatial Environment Based on Interactive Genetic Algorithm

Song,

Guo,

Wang

2023

2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE)

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Difference Coarray Design based on Genetic Algorithm and Convex Optimization

Cited by 4 publications

References 12 publications

Underwater Sparse Acoustic Sensor Array Design under Spacing Constraints Based on a Global Enhancement Whale Optimization Algorithm

Underwater Sparse Acoustic Sensor Array Design under Spacing Constraints Based on a Global Enhancement Whale Optimization Algorithm

Sparse hydrophone array synthesis for frequency‐invariant and multi‐angle beampatterns using block‐structured Bayesian compressive sensing

Optimization Design of Landscape Spatial Environment Based on Interactive Genetic Algorithm

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