›› 2014, Vol. 23 ›› Issue (7): 78402-078402.doi: 10.1088/1674-1056/23/7/078402

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇    下一篇

Four-dimensional parameter estimation of plane waves using swarming intelligence

Fawad Zamana, Ijaz Mansoor Qureshib, Fahad Munira, Zafar Ullah Khana   

  1. a Department of Electronic Engineering, Faculty of Engineering and Technology International Islamic University Sector H-10, Islamabad, Pakistan;
    b Department of Electrical Engineering, Air University, Islamabad, Pakistan
  • 收稿日期:2013-09-04 修回日期:2014-01-16 出版日期:2014-07-15 发布日期:2014-07-15

Four-dimensional parameter estimation of plane waves using swarming intelligence

Fawad Zamana, Ijaz Mansoor Qureshib, Fahad Munira, Zafar Ullah Khana   

  1. a Department of Electronic Engineering, Faculty of Engineering and Technology International Islamic University Sector H-10, Islamabad, Pakistan;
    b Department of Electrical Engineering, Air University, Islamabad, Pakistan
  • Received:2013-09-04 Revised:2014-01-16 Online:2014-07-15 Published:2014-07-15
  • Contact: Fawad Zaman, Ijaz Mansoor Qureshi, Fahad Munir, Zafar Ullah Khan E-mail:fawad.phdee31@iiu.edu.pk;imqureshi@mail.au.edu.pk;fahad.phdee57@iiu.edu.pk;zafarullah.phdee13@iiu.edu.pk
  • About author:84.40.Ba; 84.40.Xb; 07.05.Mh; 33.20.Bx

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摘要： This paper proposes an efficient approach for four-dimensional (4D) parameter estimation of plane waves impinging on a 2-L shape array. The 4D parameters include amplitude, frequency and the two-dimensional (2D) direction of arrival, namely, azimuth and elevation angles. The proposed approach is based on memetic computation, in which the global optimizer, particle swarm optimization is hybridized with a rapid local search technique, pattern search. For this purpose, a new multi-objective fitness function is used. This fitness function is the combination of mean square error and the correlation between the normalized desired and estimated vectors. The proposed hybrid scheme is not only compared with individual performances of particle swarm optimization and pattern search, but also with the performance of the hybrid genetic algorithm and that of the traditional approach. A large number of Monte-Carlo simulations are carried out to validate the performance of the proposed scheme. It gives promising results in terms of estimation accuracy, convergence rate, proximity effect and robustness against noise.

关键词: amplitude estimation, direction of arrival estimation, frequency estimation, genetic algorithm

Abstract: This paper proposes an efficient approach for four-dimensional (4D) parameter estimation of plane waves impinging on a 2-L shape array. The 4D parameters include amplitude, frequency and the two-dimensional (2D) direction of arrival, namely, azimuth and elevation angles. The proposed approach is based on memetic computation, in which the global optimizer, particle swarm optimization is hybridized with a rapid local search technique, pattern search. For this purpose, a new multi-objective fitness function is used. This fitness function is the combination of mean square error and the correlation between the normalized desired and estimated vectors. The proposed hybrid scheme is not only compared with individual performances of particle swarm optimization and pattern search, but also with the performance of the hybrid genetic algorithm and that of the traditional approach. A large number of Monte-Carlo simulations are carried out to validate the performance of the proposed scheme. It gives promising results in terms of estimation accuracy, convergence rate, proximity effect and robustness against noise.

Key words: amplitude estimation, direction of arrival estimation, frequency estimation, genetic algorithm

中图分类号:  (Antennas: theory, components and accessories)

  • 84.40.Ba
84.40.Xb (Telemetry: remote control, remote sensing; radar) 07.05.Mh (Neural networks, fuzzy logic, artificial intelligence) 33.20.Bx (Radio-frequency and microwave spectra)