Unconditional maximum likelihood approach for localization of near-field sources in 3-D space

Loading...
Thumbnail Image

Date

2004

Authors

Kabaoğlu, Nihat
Çırpan, Hakan Ali
Paker, Selçuk

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE

Research Projects

Organizational Units

Journal Issue

Abstract

Since maximum likelihood (ML) approaches have better resolution performance than the conventional localization methods in the presence of less number and highly correlated source signal samples and low signal to noise ratios we propose unconditional ML (UML) method for estimating azimuth elevation and range parameters of near-field sources in 3-D space in this paper Besides these superiorities stability asymptotic unbiasedness asymptotic minimum variance properties are motivated the application of ML approach. Despite these advantages ML estimator has computational complexity. Fortunately this problem can be tackled by the application of Expectation/Maximization (EM) iterative algorithm which converts the multidimensional search problem to one dimensional parallel search problems in order to prevent computational complexity.

Description

Keywords

Turkish CoHE Thesis Center URL

Citation

9

WoS Q

N/A

Scopus Q

N/A

Source

Volume

Issue

Start Page

233

End Page

237