2014
DOI: 10.1049/iet-map.2013.0718
|View full text |Cite
|
Sign up to set email alerts
|

Array pattern synthesis approach using a genetic algorithm

Abstract: In this study, a new array pattern synthesis approach using a genetic algorithm (GA) is proposed. The proposed approach has a unique set of objectives to be achieved by exploiting the GA optimisation capabilities. These objectives are: (i) steering the pattern main lobe in the direction of the signal of interest, (ii) minimising the side lobes level, (iii) steering pattern nulls in the directions of jammers and interferers, (iv) forcing the pattern nulls to have prespecified values in order to insure sufficien… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
5

Citation Types

0
23
0

Year Published

2015
2015
2023
2023

Publication Types

Select...
9
1

Relationship

0
10

Authors

Journals

citations
Cited by 20 publications
(23 citation statements)
references
References 11 publications
(11 reference statements)
0
23
0
Order By: Relevance
“…The key is to calculate the excitation amplitudes and phase delays of each element accurately in accord with the system requirement [19]. A variety of solutions such as simulated annealing [20]- [22], genetic algorithm (GA) [23]- [25], particle swarm optimization (PSO) [26] and compressive sensing [27] have been suggested, but they often require more complicated hardware design and delicate error control. Moreover, they might be too slow for application in a real operational system.…”
Section: Introductionmentioning
confidence: 99%
“…The key is to calculate the excitation amplitudes and phase delays of each element accurately in accord with the system requirement [19]. A variety of solutions such as simulated annealing [20]- [22], genetic algorithm (GA) [23]- [25], particle swarm optimization (PSO) [26] and compressive sensing [27] have been suggested, but they often require more complicated hardware design and delicate error control. Moreover, they might be too slow for application in a real operational system.…”
Section: Introductionmentioning
confidence: 99%
“…Compared with equally spaced arrays, unequally spaced arrays with optimally spaced sensors have advantages including their capability of achieving higher spatial resolutions or lower sidelobe, or we can use fewer sensors to meet similar pattern specifications by carefully designing the locations of array sensors [4][5][6]. By changing the amplitudes and phases of the array elements' complex weights without any physical changes in the array, the method becomes suitable for adaptive processing applications in which the array pattern is dynamically adapted to the environments [7][8][9][10].…”
Section: Introductionmentioning
confidence: 99%
“…Aperiodic arrays with optimally spaced sensors have the advantage of achieving higher spatial resolutions or lower sidelobe. On the other hand, many techniques proposed in the literatures adjust the weight coefficients when deriving the solution to beam pattern synthesis [9]- [11]. Phase-only control widely used in phased arrays to provide beam scanning are less expensive to produce, and also, are more likely to minimize excitation errors and preserve coherence [10].…”
Section: Introductionmentioning
confidence: 99%