Peak sidelobe level gumbel distribution for arrays of randomly placed antennas

Siddhartha Krishnamurthy, Daniel Bliss, Christ Richmond, Vahid Tarokh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Extreme Value Theory (EVT) is used to analyze the peak sidelobe level distribution for array element positions with arbitrary probability distributions. Computations are discussed in the context of linear antenna arrays using electromagnetic energy. The results also apply to planar arrays of random elements that can be transformed into linear arrays. For sparse arrays with small number of elements, Gaussian approximations to the beampattern distribution at a particular angle introduce inaccuracies to the probability calculations. EVT is applied without making these Gaussian approximations. It is shown that the peak sidelobe level distribution converges weakly to a Gumbel distribution in the limit of a large number of beampattern samples. This result is for both sparse and dense arrays of randomly placed antennas over a large aperture. The definition of a large aperture in this context is ambiguous, but a possible rule-of-thumb is that it is at least a wavelength.

Original languageEnglish (US)
Title of host publication2015 IEEE International Radar Conference, RadarCon 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1671-1676
Number of pages6
EditionJune
ISBN (Electronic)9781479982325
DOIs
StatePublished - Jun 22 2015
Event2015 IEEE International Radar Conference, RadarCon 2015 - Arlington, United States
Duration: May 10 2015May 15 2015

Publication series

NameIEEE National Radar Conference - Proceedings
NumberJune
Volume2015-June
ISSN (Print)1097-5659

Other

Other2015 IEEE International Radar Conference, RadarCon 2015
Country/TerritoryUnited States
CityArlington
Period5/10/155/15/15

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Peak sidelobe level gumbel distribution for arrays of randomly placed antennas'. Together they form a unique fingerprint.

Cite this