Auto-weighted least squares based algorithm for direction finding in heavy-tailed noise

Author

He, Jin ; Liu, Zhong

Author_Institution

Dept. of Electron. Eng., Nanjing Univ. of Sci. & Technol., China

Volume

2B

fYear

2005

fDate

3-8 July 2005

Firstpage

88

Abstract

We present a novel direction finding algorithm based on least squares error in the presence of heavy-tailed noise. We develop the weighted least squares error using array data only, which we call auto-weighted least squares. We propose a unity snapshot infinite norm weighted scheme. The auto-weighted least squares is itself standard least squares. In simulations, we model the noise as an α-stable distribution, and the performance of the proposed algorithm is superior to related algorithms.

Keywords

array signal processing; direction-of-arrival estimation; least squares approximations; random noise; α-stable distribution; DOA estimation; alpha-stable distribution; array signal processing; auto-weighted least squares; direction finding; direction-of-arrival estimation; heavy-tailed noise; least squares error; unity snapshot infinite norm weighted scheme; Direction of arrival estimation; Least squares approximation; Least squares methods; Maximum likelihood estimation; Narrowband; Newton method; Recursive estimation; Sensor arrays; Signal processing algorithms; Working environment noise; direction finding; heavy-tailed noise; least squares error;

fLanguage

English

Publisher

ieee

Conference_Titel

Antennas and Propagation Society International Symposium, 2005 IEEE

Print_ISBN

0-7803-8883-6

Type

conf

DOI

10.1109/APS.2005.1551942

Filename

1551942