Rapidly convergent “superresolving” direction finders of noise radiation sources in adaptive arrays

Author

Lekhovytskiy, David I. ; Shifrin, Y.S. ; Atamanskiy, Dmytro V.

Author_Institution

Kharkiv Nat. Univ. of Radio Electron., Kharkiv, Ukraine

fYear

2013

fDate

16-20 Sept. 2013

Firstpage

28

Lastpage

33

Abstract

For a number of known "superresolving" algorithms intended for direction-finding of point sources of noise radiation, we compare the requirements to the size of training sample in the estimates of input signals\´ covariance matrix. We discuss the reasons of the distinctions between the analyzed algorithms, and propose new kinds of methods with improved robustness to the finite sample size.

Keywords

adaptive antenna arrays; radio direction-finding; adaptive arrays; covariance matrix; direction-finding; finite sample size; noise radiation sources; point sources; rapidly convergent superresolving direction finders; superresolving algorithms; training sample; Algorithm design and analysis; Antenna theory; Signal resolution; Signal to noise ratio; Spatial resolution; Vectors; “ALF-bank”; adaptive lattice filter; combined direction finding; maximum likelihood estimate; sample size; spectral functions; statistical analysis; statistical and non-statistical resolution criteria; super resolution methods for DoA estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Antenna Theory and Techniques (ICATT), 2013 IX International Conference on

Conference_Location

Odessa

Print_ISBN

978-1-4799-2896-5

Type

conf

DOI

10.1109/ICATT.2013.6650679

Filename

6650679