Recursive least mean square algorithm for linear antenna array optimization for beamforming using genetic algorithm
01 Jan 2016-pp 343-348
TL;DR: Two Adaptive algorithm Least Mean Square and Recursive Le least Mean Square are implemented to revamp beam to make beam more optimize.
Abstract: A smart antenna is actually a fusion of an array that changes individual antenna elements patterns in response of a dedicated signal to improve performance. Moving one step beyond of beam forming is adaptive algorithm which allows for the computation of continuously amend weights. The process of adaptation must satisfy a specified optimization principle. In this project two Adaptive algorithm Least Mean Square and Recursive Least Mean Square are implemented to revamp beam. Added optimization of beam is accomplished with the help of genetic algorithm which makes beam more optimize. This optimization method is used for the synthesis of antenna array radiation pattern in adaptive beam forming. The optimum value of weights of each antenna element is determined which produces a radiation pattern with minimum side lobe level. Analysis is being carried out with varying different element and space in between element to obtain the minimum weight with the help of genetic algorithm. This improves the performance to achieve the maximum reduction in side lobe level (of the order −20dB) with minimum function calls.
Citations
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01 Dec 2020
TL;DR: In this paper, a new beamforming optimization method is proposed, which transforms the problem of beamforming as solving a nonlinear multivariable optimization problem with constrained fmincon function.
Abstract: The beamforming (BF) technique is very important for the phased array antenna, which includes beam pointing direction, sidelobe level suppression, and nulls. In this paper, a new beamforming optimization method is proposed. We transform the problem of beamforming as solving a nonlinear multivariable optimization problem with constrained. The fmincon function in the MATLAB optimization toolbox is introduced here to search the optimal solution. Several numerical examples are presented to prove the effectiveness of the method. In addition, compared with the stochastic optimization methods such as genetic algorithm (GA) and particle swarm optimization (PSO), the proposed method is outperforming on beamforming.
References
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Book•
01 Jan 1986
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Abstract: Background and Overview. 1. Stochastic Processes and Models. 2. Wiener Filters. 3. Linear Prediction. 4. Method of Steepest Descent. 5. Least-Mean-Square Adaptive Filters. 6. Normalized Least-Mean-Square Adaptive Filters. 7. Transform-Domain and Sub-Band Adaptive Filters. 8. Method of Least Squares. 9. Recursive Least-Square Adaptive Filters. 10. Kalman Filters as the Unifying Bases for RLS Filters. 11. Square-Root Adaptive Filters. 12. Order-Recursive Adaptive Filters. 13. Finite-Precision Effects. 14. Tracking of Time-Varying Systems. 15. Adaptive Filters Using Infinite-Duration Impulse Response Structures. 16. Blind Deconvolution. 17. Back-Propagation Learning. Epilogue. Appendix A. Complex Variables. Appendix B. Differentiation with Respect to a Vector. Appendix C. Method of Lagrange Multipliers. Appendix D. Estimation Theory. Appendix E. Eigenanalysis. Appendix F. Rotations and Reflections. Appendix G. Complex Wishart Distribution. Glossary. Abbreviations. Principal Symbols. Bibliography. Index.
16,062 citations
"Recursive least mean square algorit..." refers background in this paper
...[10] Simon Haykin: Adaptive Filter Theory, Prentice Hall, 2002, ISBN 0-13-048434-2....
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Book•
01 Nov 19968,608 citations
"Recursive least mean square algorit..." refers methods in this paper
...In the LMS algorithm the weight vector w changes along with the direction of the arrival estimated gradient based on the negative steepest descent method [6]....
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TL;DR: An overview of beamforming from a signal-processing perspective is provided, with an emphasis on recent research.
Abstract: An overview of beamforming from a signal-processing perspective is provided, with an emphasis on recent research. Data-independent, statistically optimum, adaptive, and partially adaptive beamforming are discussed. Basic notation, terminology, and concepts are included. Several beamformer implementations are briefly described. >
4,122 citations
"Recursive least mean square algorit..." refers methods in this paper
...In comparison to LMS which use a steepest descent method to amend the weight vector, whereas RLS use the wiener solution to amend the weight without any additional strain of approximating an optimization process [9]....
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01 Jan 1986
2,843 citations
"Recursive least mean square algorit..." refers background in this paper
...Functional diagram of an N-element adaptive array [12] III GENTIC ALGORITHM...
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Proceedings Article•
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TL;DR: The energy o f the observed signal may contain frequencies a l l t h e way from 1 h e r t z t o above 100 Mhz and the presence o f such atmospheric energy needs to be understood.
Abstract: I n t h e c o n t e x t o f t h i s "handbook" o f f e r i n g , a tmospher ics re fer to e lect romagnet ic s ignals that rad iate or are produced by l ightn ing and r e l a t e d e lec t r i ca l d ischarge phenomena. Sometimes these sign a l s a r e c a l l e d s f e r i c s and the i r ex i s tence was known s ince the ea r l y days o f r a d i o . The energy o f the observed signal may contain frequencies a l l t h e way from 1 h e r t z t o above 100 Mhz. Needless t o say, the presence o f such atmospheric energy i n .ou r env i ronment needs t o be understood. I n s p i t e o f observat ional research spanning hal f a century, we r e a l l y do n o t have a c l e a r p i c t u r e o f what i s going on n o t t o mention our lack o f t h e o r e t i c a l i n s i g h t . More recent ly , inves t iga tors have examined t h e s u b j e c t i n the contex t o f the e lec t romagnet ic s igna ls tha t can be produced ind i rect ly f rom the prompt gama radiat ion associated wi th nuc lear detonat ions.
660 citations