Adaptive Beamforming Algorithm based on Generalized Opposition-based Simulated Kalman Filter
In this paper, a new population-based metaheuristic optimization algorithm named Generalized Opposition-based Simulated Kalman Filter (GOBSKF) is proposed as adaptive beamforming algorithm. GOBSKF is an improved version of Simulated Kalman Filter (SKF). Adaptive beamforming algorithm based on GOBS...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Universiti Malaysia Pahang
2016
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/14849/ http://umpir.ump.edu.my/id/eprint/14849/ http://umpir.ump.edu.my/id/eprint/14849/1/P001%20pg1-9.pdf |
| Summary: | In this paper, a new population-based metaheuristic optimization algorithm named Generalized Opposition-based
Simulated Kalman Filter (GOBSKF) is proposed as adaptive beamforming algorithm. GOBSKF is an improved version of
Simulated Kalman Filter (SKF). Adaptive beamforming algorithm based on GOBSKF is compared with previously published work
which is Adaptive Mutated Boolean PSO (AMBPSO) and Minimum Variance Distortionless Response (MVDR) for different noise
level. The results show that GOBSKF is proven to be better than AMBPSO and MVDR. |
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