MVDR Algorithm Based Linear Antenna Array Performance Assessment For Adaptive Beamforming Application

The performance of Minimum Variance Distortionless Response (MVDR) beamformer is sensitive to errors such as the steering vector errors, the finite snapshots, and unsatisfactory null-forming level. In this paper, a combination of MVDR with linear antenna arrays (LAAs) for two scanning angles process...

Full description

Saved in:
Bibliographic Details
Main Authors: Shahab, Suhail Najm, Ayib Rosdi, Zainun, Ali, Hussein Ahmed, Hojabri, Mojgan, Nurul Hazlina, Noordin
Format: Article
Language:English
Published: Taylor's University 2017
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/18212/1/MVDR%20Algorithm%20Based%20Linear%20Antenna%20Array%20Performance%20Assessment%20For%20Adaptive%20Beamforming%20Application.pdf
http://umpir.ump.edu.my/id/eprint/18212/
http://jestec.taylors.edu.my/Vol%2012%20issue%205%20May%202017/12_5_17.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The performance of Minimum Variance Distortionless Response (MVDR) beamformer is sensitive to errors such as the steering vector errors, the finite snapshots, and unsatisfactory null-forming level. In this paper, a combination of MVDR with linear antenna arrays (LAAs) for two scanning angles process in the azimuth and elevation are used to illustrate the MVDR performance against error which results in acquiring the desired signal and suppressing the interference and noise. The impact of various parameters, such as the number of elements in the array, space separation between array elements, the number of interference sources, noise power level, and the number of snapshots on the MVDR are investigated. The MVDR performance is evaluated with two important metrics: beampattern of two scanning angles and Signal to Interference plus Noise Ratio (SINR). The results found that the MVDR performance improves as the number of array elements increases. The beampattern relies on the number of elements and the separation between array elements. The best interelement spacing obtained is 0.5λ that avoids grating lobes and mutual coupling effects. Besides, the SINR strongly depends on the noise power label and a number of snapshots. When the noise power label increased, the MVDR performance degraded as well the null width increases in the elevation direction as well as more accurate resolution occurred when the number of snapshots increased. Finally, it is found the proposed method achieves SINR better than existing techniques.