Research on Adaptive Beamforming of Shape Maintenance Algorithm for the Mainlobe

Authors

  • Yan Ji Institute of energy engineering, Yulin University, Yulin, China
  • Feng Zhang School of Information, Yulin University, Yulin 719000, China

DOI:

https://doi.org/10.3991/ijoe.v9iS4.2643

Keywords:

adaptive beamforming, shape maintenance, beam, low sidelobe

Abstract


To improve the transmitting adaptive beamforming efficiency and performance of the shape maintenance for the mainlobe, analyzed existing adaptive pattern for beamforming.In this paper, the question that the main lobe of adaptive pattern will be distorted significantly, an approach is proposed to maintain the mainlobe shape based on a main-lobe subspace, and the high peak side-lobe problem is resolved recurring to the orthonormal projection algorithms available. The new approach can be used to the transmitting adaptive beamforming, adaptive sum and sub beam forming. The trace driven simulation shows its performance.

Author Biographies

Yan Ji, Institute of energy engineering, Yulin University, Yulin, China

Ji Yan received the MS degree in Computer science from Xidian University in 2008. Now he is an associate professor in Yulin University. His research interests are in the areas of modeling of complex systems, the Internet of Things applications.

Feng Zhang, School of Information, Yulin University, Yulin 719000, China

Feng Zhang received the MS degree in Computer science from Xidian University in 2009. Now he is a PhD of Northwestern Polytechnical University. He is currently a associate professor in Yulin University. His research interests are in the areas of Cloud integrated manufacturing technology, the modeling of complex systems, the Internet of Things applications.

Downloads

Published

2013-05-01

How to Cite

Ji, Y., & Zhang, F. (2013). Research on Adaptive Beamforming of Shape Maintenance Algorithm for the Mainlobe. International Journal of Online and Biomedical Engineering (iJOE), 9(S4), pp. 40–44. https://doi.org/10.3991/ijoe.v9iS4.2643

Issue

Vol. 9 (2013): Special Issue: MEAMS2012 Conference

Section

Special Focus Papers