Null Steering in Failed Antenna Arrays

Om Prakash Acharya,Amalendu Patnaik,Sachendra N Sinha

doi:10.1155/2011/692197

Abstract

Antenna array pattern nulling is desirable in order to suppress the interfering signals. But in large antenna arrays, there is always a possibility of failure of some elements, which may degrade the radiation pattern with an increase in side lobe level (SLL) and removal of the nulls from desired position. In this paper a correction procedure is introduced based on Particle Swarm Optimization (PSO) which maintains the nulling performance of the failed antenna array. Considering the faulty elements as nonradiating elements, PSO reoptimizes the weights of the remaining radiating elements to reshape the pattern. Simulation results for a Chebyshev array with imposed single, multiple, and broad nulls with failed antenna array are presented.

Highlights

In order to reduce the effect of interfering signals, it is desirable to place nulls in specified directions during antenna beamforming
The Particle Swarm Optimization (PSO) technique has been described in the literature in length, but for completeness of the paper, here we have briefly described the technique
In order to obtain desired nulling pattern with failed elements which has a good parity with the pattern as before, the excitations of the remaining working elements were adjusted by PSO

Summary

Introduction

In order to reduce the effect of interfering signals, it is desirable to place nulls in specified directions during antenna beamforming. Conventional [2,3,4,5,6] as well as evolutionary optimization techniques [7,8,9,10,11,12,13,14,15] have been used for placing nulls in antenna array patterns. In situations, where some of the radiating elements do not radiate due to some unforeseen reasons, the entire antenna pattern gets distorted It degrades the SLL and destroys the pattern null created to suppress the interference from particular directions. Hybrid optimization method [25, 26] has been applied to improve the array pattern in the presence of failed elements.

Problem Formulation

Particle Swarm Optimization

PSO Implementation and Results

Conclusion