Improved Orchard-Elliott pattern synthesis algorithm by pseudo-inverse technique and genetic algorithm

Reuven Shavit; Shuki Levy

Improved Orchard-Elliott pattern synthesis algorithm by pseudo-inverse technique and genetic algorithm

Reuven Shavit, Shuki Levy

Department of Electrical & Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

This paper describes a procedure to improve the Orchard-Elliott synthesis algorithm for shaped radiation patterns. By far this algorithm results in the best performance for shaping radiation patterns. However, its iterative procedure occasionally suffers from singularity problems throughout the matrix inversion embedded in the algorithm. This deficiency can be overcome by using a pseudo-inverse technique. Further improvement, which reduces the dynamic range of the array current distribution, is achieved using a genetic algorithm. The improved algorithm performance is demonstrated on the synthesis of a linear array with a symmetric flat-toped radiation pattern.

Original language	English
Title of host publication	IEEE Antennas and Propagation Society International Symposium
Subtitle of host publication	Transmitting Waves of Progress to the Next Millennium, Held in Conjunction with: USNC/URSI National Radio Science Meeting, AP-S/URSI 2000
Pages	1042-1045
Number of pages	4
State	Published - 1 Dec 2000

Publication series

Name	IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)
Volume	2
ISSN (Print)	0272-4693

ASJC Scopus subject areas

Electrical and Electronic Engineering

Cite this

Shavit, R., & Levy, S. (2000). Improved Orchard-Elliott pattern synthesis algorithm by pseudo-inverse technique and genetic algorithm. In IEEE Antennas and Propagation Society International Symposium: Transmitting Waves of Progress to the Next Millennium, Held in Conjunction with: USNC/URSI National Radio Science Meeting, AP-S/URSI 2000 (pp. 1042-1045). (IEEE Antennas and Propagation Society, AP-S International Symposium (Digest); Vol. 2).

Shavit, Reuven ; Levy, Shuki. / Improved Orchard-Elliott pattern synthesis algorithm by pseudo-inverse technique and genetic algorithm. IEEE Antennas and Propagation Society International Symposium: Transmitting Waves of Progress to the Next Millennium, Held in Conjunction with: USNC/URSI National Radio Science Meeting, AP-S/URSI 2000. 2000. pp. 1042-1045 (IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)).

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abstract = "This paper describes a procedure to improve the Orchard-Elliott synthesis algorithm for shaped radiation patterns. By far this algorithm results in the best performance for shaping radiation patterns. However, its iterative procedure occasionally suffers from singularity problems throughout the matrix inversion embedded in the algorithm. This deficiency can be overcome by using a pseudo-inverse technique. Further improvement, which reduces the dynamic range of the array current distribution, is achieved using a genetic algorithm. The improved algorithm performance is demonstrated on the synthesis of a linear array with a symmetric flat-toped radiation pattern.",

author = "Reuven Shavit and Shuki Levy",

year = "2000",

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Shavit, R & Levy, S 2000, Improved Orchard-Elliott pattern synthesis algorithm by pseudo-inverse technique and genetic algorithm. in IEEE Antennas and Propagation Society International Symposium: Transmitting Waves of Progress to the Next Millennium, Held in Conjunction with: USNC/URSI National Radio Science Meeting, AP-S/URSI 2000. IEEE Antennas and Propagation Society, AP-S International Symposium (Digest), vol. 2, pp. 1042-1045.

Improved Orchard-Elliott pattern synthesis algorithm by pseudo-inverse technique and genetic algorithm. / Shavit, Reuven; Levy, Shuki.
IEEE Antennas and Propagation Society International Symposium: Transmitting Waves of Progress to the Next Millennium, Held in Conjunction with: USNC/URSI National Radio Science Meeting, AP-S/URSI 2000. 2000. p. 1042-1045 (IEEE Antennas and Propagation Society, AP-S International Symposium (Digest); Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - This paper describes a procedure to improve the Orchard-Elliott synthesis algorithm for shaped radiation patterns. By far this algorithm results in the best performance for shaping radiation patterns. However, its iterative procedure occasionally suffers from singularity problems throughout the matrix inversion embedded in the algorithm. This deficiency can be overcome by using a pseudo-inverse technique. Further improvement, which reduces the dynamic range of the array current distribution, is achieved using a genetic algorithm. The improved algorithm performance is demonstrated on the synthesis of a linear array with a symmetric flat-toped radiation pattern.

AB - This paper describes a procedure to improve the Orchard-Elliott synthesis algorithm for shaped radiation patterns. By far this algorithm results in the best performance for shaping radiation patterns. However, its iterative procedure occasionally suffers from singularity problems throughout the matrix inversion embedded in the algorithm. This deficiency can be overcome by using a pseudo-inverse technique. Further improvement, which reduces the dynamic range of the array current distribution, is achieved using a genetic algorithm. The improved algorithm performance is demonstrated on the synthesis of a linear array with a symmetric flat-toped radiation pattern.

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Shavit R, Levy S. Improved Orchard-Elliott pattern synthesis algorithm by pseudo-inverse technique and genetic algorithm. In IEEE Antennas and Propagation Society International Symposium: Transmitting Waves of Progress to the Next Millennium, Held in Conjunction with: USNC/URSI National Radio Science Meeting, AP-S/URSI 2000. 2000. p. 1042-1045. (IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)).

Improved Orchard-Elliott pattern synthesis algorithm by pseudo-inverse technique and genetic algorithm

Abstract

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