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Memetic Algorithms for Multiple Interference Cancellations of Linear Array Based on Phase-Amplitude Perturbations

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Abstract

A novel method based on the memetic algorithm for the design of multiple interference cancellations of a linear array antenna by phase-amplitude perturbations is proposed. The adaptive array antenna is capable of sensing the presence of interference sources and suppressing the interferences in the interfering directions. This technique can increase the signal-to-interference ratio. The memetic algorithm is applied to find the weighting vector which makes the pattern nulling optimization of the proposed adaptive antenna. This technique is also able to do the cancellation of multiple interferences for different incident directions.

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References

  1. Ismail, T.H., Dawoud, M.M.: Null steering in phased arrays by controlling the element positions. IEEE Trans. Antennas Propag. 39, 1561–1566 (1991)

    Article  Google Scholar 

  2. Tennant, A., Dawoud, M.M., Anderson, A.P.: Array pattern nulling by element position perturbations using a genetic algorithm. Electron. Lett. 30, 174–176 (1994)

    Article  Google Scholar 

  3. Dawoud, M.M.: Null steering in scanned linear arrays by element position perturbations. Int. J. Electron. 78, 743–757 (1995)

    Article  Google Scholar 

  4. Er, M.H.: Quadratic optimization problems in robust beamforming. J. Optim. Theory Appl. 66(3), 431–442 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  5. Ng, T.S., Cheah, J.Y., Paoloni, F.J.: Optimization with controlled null placement in antenna array pattern synthesis. IEEE Trans. Antennas Propag. 33, 215–217 (1985)

    Article  Google Scholar 

  6. Chung, Y.C., Haupt, R.L.: Amplitude and phase adaptive nulling with a genetic algorithm. J. Electromagn. Waves Appl. 14, 631–649 (2000)

    Article  Google Scholar 

  7. Rao, S.S.: Optimization: Theory and Applications. Wiley, New York (1979)

    MATH  Google Scholar 

  8. Goldberg, D.E.: Genetic Algorithms in Search Optimization and Machine Learning. Addison-Wesley, Reading (1989)

    MATH  Google Scholar 

  9. Spall, J.C.: Introduction to Stochastic Search and Optimization Estimation Simulation and Control. Wiley, New York (2003)

    Book  MATH  Google Scholar 

  10. Yu, C.X., Chen, Y.M., Mu, Y.F.: Study on adaptive numerical analysis method for elastic problem. Int. J. Innov. Comput. Inf. Control 1(2), 227–235 (2005)

    Google Scholar 

  11. Holland, J.H.: Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor (1975)

    Google Scholar 

  12. Hsu, C.H., Babij, T.M.: Pattern nulling of adaptive antenna by phase and amplitude perturbations using genetic algorithm. In: Proc. KES-2001 Fifth Int. Conf. on Knowledge-Based Intelligent Information Engineering Systems and Allied Technologies, vol. 2, pp. 1047–1051 (2001)

  13. Sacchi, C., De Natale, F., Donelli, M., Lommi, A., Massa, A.: Adaptive antenna array control in the presence of interfering signals with stochastic arrivals: assessment on GA-based procedure. IEEE Trans. Wirel. Commun. 3(4), 1031–1036 (2004)

    Article  Google Scholar 

  14. Lohn, J.D., Hornby, G.S., Linden, D.S.: An Evolved Antenna for Deployment on NASA’s Space Technology 5 Mission, Genetic Programming Theory and Practice II. Springer, New York (2004)

    Google Scholar 

  15. Yang, R., Douglas, I.: Simple genetic algorithm with local tuning: efficient global optimizing technique. J. Optim. Theory Appl. 98(2), 449–465 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  16. Moscato, P., Norman, M.G.: A memetic approach for the travelling salesman problem-implementation of a computational ecology for combinatorial optimization on message-passing systems. In: Proc. Int. Conf. on Parallel Computing and Computer Applications. IOS Press (1992)

  17. Radcliffe, N.J., Surry, P.D.: Formal Memetic Algorithms. Lecture Notes in Computer Science. Springer, Berlin (1995)

    Google Scholar 

  18. Shyr, W.J.: The hybrid genetic algorithm for blind signal separation. In: Lecture Notes in Computer Science, vol. 4234, pp. 954–963. Springer, Berlin (2006)

    Google Scholar 

  19. Freisleben, B., Merz, P.: A genetic local search algorithm for solving symmetric and asymmetric travelling salesman problems. In: Proc. IEEE Int. Conf. on Evolutionary Computation, pp. 616–621. IEEE Press, New York (1996)

    Chapter  Google Scholar 

  20. Merz, P., Freisleben, B.: Fitness Landscapes and Memetic Algorithm Design in New Ideas in Optimization. McGraw-Hill, London (1999)

    Google Scholar 

  21. Knowles, J.D., Corne, D.W.: M-PAES: A memetic algorithm for multiobjective optimization. In: Proc. IEEE Int. Conf. on Evolutionary Computation, vol. 1, pp. 325–332 (2000)

  22. Burke, E.K., Smith, A.J.: Hybrid evolutionary techniques for the maintenance scheduling problem. IEEE Trans. Power Syst. 15(1), 122–128 (2000)

    Article  Google Scholar 

  23. Hsu, C.H., Shyr, W.J., Chen, C.H.: Adaptive pattern nulling design of linear array antenna by phase-only perturbations using memetic algorithms. In: Proc. Inter. Conf. of Innovative Computing Information and Control, vol. 3, pp. 308–311. IEEE Comput. Soc., Los Alamitos (2006)

    Google Scholar 

  24. Hsu, C.H., Shyr, W.J.: Memetic algorithms for optimizing adaptive linear array pattern by phase-position perturbations. Circuits Syst. Signal Process. 24(4), 327–341 (2005)

    Article  MATH  Google Scholar 

  25. Monzingo, R.A., Miller, T.W.: Introduction to Adaptive Arrays. Wiley, New York (1986)

    Google Scholar 

  26. Dawkins, R.: The Selfish Gene. Oxford University Press, London (1976)

    Google Scholar 

  27. Ishibuchi, H., Murata, T.: Multi-objective genetic local search algorithm. In: Proc. IEEE Int. Conf. on Evolutionary Computation, pp. 119–124. IEEE Press, New York (1996)

    Chapter  Google Scholar 

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Authors and Affiliations

  1. Department of Electronic Engineering, Chienkuo Technology University, Changhua, 500, Taiwan

    C. H. Hsu & K. H. Kuo

  2. Department of Industrial Education and Technology, National Changhua University of Education, Changhua, 500, Taiwan

    W. J. Shyr

  3. Department of Mechatronics Engineering, National Changhua University of Education, Changhua, 500, Taiwan

    P. H. Chou & M. J. Wu

Authors
  1. C. H. Hsu
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  2. W. J. Shyr
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  3. K. H. Kuo
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  4. P. H. Chou
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  5. M. J. Wu
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Corresponding author

Correspondence to C. H. Hsu.

Additional information

Communicated by P.L. Yu.

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Hsu, C.H., Shyr, W.J., Kuo, K.H. et al. Memetic Algorithms for Multiple Interference Cancellations of Linear Array Based on Phase-Amplitude Perturbations. J Optim Theory Appl 144, 629–642 (2010). https://doi.org/10.1007/s10957-009-9577-5

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  • DOI: https://doi.org/10.1007/s10957-009-9577-5

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