Military antenna design using simple and competent genetic algorithms

Santarelli, Scott; Yu, Tian-Li; Goldberg, David E.; Altshuler, E.E.; O'Donnell, T.H.; Southall, H.L.; Mailloux, Robert J.

doi:10.1016/j.mcm.2005.05.024

Cited by 26 publications

(13 citation statements)

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“…SGAs are known for their robust optimization capabilities and have been successfully used in a variety of practical antenna problems [1]. A SGA, however, does not always address the issue of linkage (i.e., chromosomal encoding) adequately.…”

Section: Ga Design Theory and Competent Gasmentioning

confidence: 99%

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Application of evolutionary algorithms and neural network concepts to the design of low-cost, wideband antenna arrays

Santarelli

Mailloux²,

et al. 2007

SPIE Proceedings

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. (From -To) REPORT DATE (DD-MM-YYYY) 23-08-2007 REPORT TYPE: Conference Paper DATES COVERED SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES)Electromagnetics Technology Division Source Code: 437490 SPONSOR/MONITOR'S ACRONYM(S)Sensors Directorate AFRL-SN-HS Air Force Research Laboratory 80 Scott Drive Hanscom AFB MA 01731-2909 SPONSOR/MONITOR'S REPORT NUMBER(S) AFRL-SN-HS-TP-2007-0010 DISTRIBUTION / AVAILABILITY STATEMENTStatement A: Approved for Public Release; distribution unlimited. SUPPLEMENTARY NOTES This work is copyrighted. © [2007] Society of Photo-Optical Instrumentation Engineers (SPIE). Presented at 2007 SPIE Defense andSecurity Symposium, Orlando, FL, 9 -13 April 2007. One or more of the authors is a U.S. Government employee working within the scope of their Government job; therefore, the U.S. Government is joint owner of the work and has the right to copy, distribute, and use the work. This work is supported by AFOSR; ESC/PA clearance: ESC 07-0394 ABSTRACTThis paper describes the application of biologically-inspired algorithms and concepts to the design of wideband antenna arrays. In particular, we address two specific design problems. The first involves the design of a constrained-feed network for a Rotman-lens beamformer. We implemented two evolutionary optimization (EO) approaches, namely a simple genetic algorithm (SGA) and a competent genetic algorithm. We conducted simulations based on experimental data, which effectively demonstrate that the competent GA outperforms the SGA (i.e., finds a better design solution) as the objective function becomes less specific and more "general." The second design problem involves the implementation of polyomino-shaped subarrays for sidelobe suppression of large, wideband planar arrays. We use a modified screen-saver code to generate random polyomino tilings. A separate code assigns array values to each element of the tiling (i.e., amplitude, phase, time delay, etc.) and computes the corresponding far-field radiation pattern. In order to conduct a statistical analysis of pattern characteristics vs. tiling geometry, we needed a way to measure the "similari...

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Section: Ga Design Theory and Competent Gasmentioning

confidence: 99%

“…We restricted the amplitudes to lie in the interval [0 1] and the phases to lie in the interval [0° 360°]. It is also worth noting that we used an 8-bit gray code for both the amplitude and phase encoding schemes [1].…”

Section: Simple Genetic Algorithm (Sga)mentioning

confidence: 99%

Application of evolutionary algorithms and neural network concepts to the design of low-cost, wideband antenna arrays

Santarelli

Mailloux²,

et al. 2007

SPIE Proceedings

Self Cite

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“…As long as the horizontal segments have opposite phase currents the contribution to the radiated power can be The optimization problem involves a tradeoff between miniaturization along with a resonant total length i.e., a long wire, and loss minimization i.e., a short wire 4 . In this case, the size of each segment must be individually optimized and we propose as a solution, the use of the genetic algorithm, which has been proven to be an effective tool for antenna optimization 5,6,7 .…”

Section: Introductionmentioning

confidence: 99%

Optimization of meander line antennas for RFID applications by using genetic algorithm

et al. 2015

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“…Genetic algorithm is applied to select the optimal combination of the parameters of support vector machine. Genetic algorithm is inspired by evolution and has strong global search ability [4,5]. After the testing experiments, the evaluation accuracy of GA-SVC is 100%.…”

Section: Introductionmentioning

confidence: 99%

Synthesized evaluation method for network safety based on Ga-Svc

Song

2013

SPIE Proceedings

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In the study, support vector machine optimized by genetic algorithm is applied to evaluate network safety. As the parameters in the support vector machine have a great influence on its evaluation ability. Genetic algorithm is applied to select the optimal combination of the parameters of support vector machine. The evaluation accuracy of GA-SVC is 100% after the testing experiments. The experimental results indicate that SVM has high evaluation accuracy in the evaluation of network safety.

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Military antenna design using simple and competent genetic algorithms

Cited by 26 publications

References 9 publications

Application of evolutionary algorithms and neural network concepts to the design of low-cost, wideband antenna arrays

Application of evolutionary algorithms and neural network concepts to the design of low-cost, wideband antenna arrays

Optimization of meander line antennas for RFID applications by using genetic algorithm

Synthesized evaluation method for network safety based on Ga-Svc

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