A GLRT based STAP for the range dependent problem

Biao Chen, Braham Himed

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

2 Scopus citations

Abstract

We consider in this paper a likelihood principle based approach for the range dependent problem in space time adaptive processing. The proposed generalized likelihood ratio test (GLRT) addresses the range dependent issue by directly applying the likelihood principle to the range dependent signal model. Using the knowledge of platform geometry, we develop maximum likelihood estimators that facilitate the GLRT. This differs from existing methods that rely on data transformations in dealing with the range dependence issue. Numerical examples show that the new GLRT approach exhibits significant performance gain over existing approaches.

Original languageEnglish (US)
Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
PagesII905-II908
DOIs
StatePublished - Aug 6 2007
Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
Duration: Apr 15 2007Apr 20 2007

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
ISSN (Print)1520-6149

Other

Other2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
CountryUnited States
CityHonolulu, HI
Period4/15/074/20/07

Keywords

  • General likelihood ratio test
  • Range dependent
  • Space time adaptive processing

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'A GLRT based STAP for the range dependent problem'. Together they form a unique fingerprint.

  • Cite this

    Chen, B., & Himed, B. (2007). A GLRT based STAP for the range dependent problem. In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 (pp. II905-II908). [4217556] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2). https://doi.org/10.1109/ICASSP.2007.366383