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CLC number: TN929

On-line Access: 2018-11-11

Received: 2016-11-14

Revision Accepted: 2017-02-21

Crosschecked: 2018-09-17

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Shafqat Ullah Khan

https://orcid.org/0000-0003-1969-1289

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Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.9 P.1191-1202

http://doi.org/10.1631/FITEE.1601694


Correction of array failure using grey wolf optimizer hybridized with an interior point algorithm


Author(s):  Shafqat Ullah Khan, M. K. A. Rahim, Liaqat Ali

Affiliation(s):  Advanced RF & Microwave Research Group, Department of Communication Engineering Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai 81310, Malaysia; more

Corresponding email(s):   shafqatphy@yahoo.com

Key Words:  Failure correction, Grey wolf optimizer, Interior point algorithm, Sidelobes, Deeper null depth level


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Shafqat Ullah Khan, M. K. A. Rahim, Liaqat Ali. Correction of array failure using grey wolf optimizer hybridized with an interior point algorithm[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(9): 1191-1202.

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Abstract: 
We design a grey wolf optimizer hybridized with an interior point algorithm to correct a faulty antenna array. If a single sensor fails, the radiation power pattern of the entire array is disturbed in terms of sidelobe level (SLL) and null depth level (NDL), and nulls are damaged and shifted from their original locations. All these issues can be solved by designing a new fitness function to reduce the error between the preferred and expected radiation power patterns and the null limitations. The hybrid algorithm has been designed to control the array’s faulty radiation power pattern. Antenna arrays composed of 21 sensors are used in an example simulation scenario. The MATLAB simulation results confirm the good performance of the proposed method, compared with the existing methods in terms of SLL and NDL.

采用内点算法的灰狼优化程序阵列纠错

摘要:设计了一个采用内点算法的灰狼优化程序以纠错天线阵列。若单个传感器故障,整个阵列辐射功率图在旁瓣电平(side lobe level,SLL)和深零度电平(null depth level,NDL)方向受干扰,零点被破坏并发生偏离。可通过设计新的适应函数解决这些问题,并减小预期辐射功率图与零限值之间的偏差。该混合算法用于控制天线阵列的辐射功率图。仿真实验使用了由21个传感器组成的天线阵列。仿真结果表明,与现有的SLL和NDL方法相比,所提方法具有良好性能。

关键词:故障纠错;灰狼优化器;内点算法;旁瓣电平;深零度电平

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