Performance analysis of metaheuristic approaches for single-snapshot DOA estimation

Borja Errasti-Alcala; Raul Fernandez-Recio

doi:10.1109/LAWP.2013.2243694

Performance analysis of metaheuristic approaches for single-snapshot DOA estimation

Borja Errasti-Alcala
, Raul Fernandez-Recio

Instituto Nacional de Tecnica Aeroespacial

Research output: Contribution to journal › Article › peer-review

19 Citations (Scopus)

Abstract

This letter addresses the application of metaheuris-tics to the single-snapshot direction-of-arrival estimation. The performances of five of the most popular optimization algorithms-Particle Swarm Optimization, Ant Colony Optimization for Continuous Domains, Simulated Annealing, Genetic Algorithms, and Differential Evolution-are compared in terms of convergence, accuracy, resolution, and computational cost in order to find the most suitable one. Also, running parameters are suggested for all of them. The featured numerical simulations include both uniform and nonuniform arrays and different noise scenarios. Results show that all of the presented optimization algorithms are capable of solving the problem, but Ant Colony Optimization for Continuous Domains is the most recommendable.

Original language	English
Article number	6423777
Pages (from-to)	166-169
Number of pages	4
Journal	IEEE Antennas and Wireless Propagation Letters
Volume	12
DOIs	https://doi.org/10.1109/LAWP.2013.2243694
Publication status	Published - 2013
Externally published	Yes

Keywords

Ant colony optimization
Direction-of-arrival (DOA) estimation
Electronic warfare
Genetic algorithms
Particle swarm optimization

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10.1109/LAWP.2013.2243694

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abstract = "This letter addresses the application of metaheuris-tics to the single-snapshot direction-of-arrival estimation. The performances of five of the most popular optimization algorithms-Particle Swarm Optimization, Ant Colony Optimization for Continuous Domains, Simulated Annealing, Genetic Algorithms, and Differential Evolution-are compared in terms of convergence, accuracy, resolution, and computational cost in order to find the most suitable one. Also, running parameters are suggested for all of them. The featured numerical simulations include both uniform and nonuniform arrays and different noise scenarios. Results show that all of the presented optimization algorithms are capable of solving the problem, but Ant Colony Optimization for Continuous Domains is the most recommendable.",

keywords = "Ant colony optimization, Direction-of-arrival (DOA) estimation, Electronic warfare, Genetic algorithms, Particle swarm optimization",

author = "Borja Errasti-Alcala and Raul Fernandez-Recio",

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PY - 2013

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AB - This letter addresses the application of metaheuris-tics to the single-snapshot direction-of-arrival estimation. The performances of five of the most popular optimization algorithms-Particle Swarm Optimization, Ant Colony Optimization for Continuous Domains, Simulated Annealing, Genetic Algorithms, and Differential Evolution-are compared in terms of convergence, accuracy, resolution, and computational cost in order to find the most suitable one. Also, running parameters are suggested for all of them. The featured numerical simulations include both uniform and nonuniform arrays and different noise scenarios. Results show that all of the presented optimization algorithms are capable of solving the problem, but Ant Colony Optimization for Continuous Domains is the most recommendable.

KW - Ant colony optimization

KW - Direction-of-arrival (DOA) estimation

KW - Electronic warfare

KW - Genetic algorithms

KW - Particle swarm optimization

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JO - IEEE Antennas and Wireless Propagation Letters

JF - IEEE Antennas and Wireless Propagation Letters

M1 - 6423777

ER -

Performance analysis of metaheuristic approaches for single-snapshot DOA estimation

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Keywords

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