Adaptive detection based on multiple a-priori spectral models for MIMO radar in compound-Gaussian clutter

Conference Paper

In this paper, we consider the adaptive detection with multiple-input multiple-output (MIMO) radar in the presence of compound-Gaussian clutter with a limited number of secondary data set. We assume that multiple a-priori spectral models for the clutter are available, and model the actual clutter inverse covariance structure as a combination of these available a-priori models. In this framework, a sequential optimization algorithm is first presented to estimate the unknown parameters. Then, an approximate generalized likelihood ratio test (GLRT) is developed by exploiting the obtained estimates. Finally, we evaluate the capabilities of the proposed detector against compound-Gaussian clutter as well as its superiority with respect to some existing techniques with few secondary data support.

Full Text

Duke Authors

Cited Authors

  • Li, N; Cui, G; Yang, H; Kong, L; Liu, QH

Published Date

  • June 22, 2015

Published In

Volume / Issue

  • 2015-June / June

Start / End Page

  • 870 - 875

International Standard Serial Number (ISSN)

  • 1097-5659

International Standard Book Number 13 (ISBN-13)

  • 9781479982325

Digital Object Identifier (DOI)

  • 10.1109/RADAR.2015.7131117

Citation Source

  • Scopus