Knowledge-aided Bayesian detection for MIMO radar in compound-Gaussian clutter with inverse Gamma texture
Publication
, Conference
Li, N; Cui, G; Yang, H; Kong, L; Liu, QH
Published in: IEEE National Radar Conference - Proceedings
June 22, 2015
In this paper, we consider the adaptive detection with multiple-input multiple-output (MIMO) radar in compound-Gaussian clutter. The covariance matrices of the primary and the secondary data share a common structure but different power levels (textures). A Bayesian framework is exploited where both the textures and the structure are assumed to be random. Precisely, the textures follow inverse Gamma distribution and the structure is drawn from an inverse complex Wishart distribution. In this framework, the generalized likelihood ratio test (GLRT) is derived. Finally, we evaluate the capabilities of the proposed detector against compound-Gaussian clutter as well as their superiority with respect to some existing techniques.
Published In
IEEE National Radar Conference - Proceedings
DOI
ISSN
1097-5659
ISBN
9781479982325
Publication Date
June 22, 2015
Volume
2015-June
Issue
June
Start / End Page
777 / 782
Citation
APA
Chicago
ICMJE
MLA
NLM
Li, N., Cui, G., Yang, H., Kong, L., & Liu, Q. H. (2015). Knowledge-aided Bayesian detection for MIMO radar in compound-Gaussian clutter with inverse Gamma texture. In IEEE National Radar Conference - Proceedings (Vol. 2015-June, pp. 777–782). https://doi.org/10.1109/RADAR.2015.7131101
Li, N., G. Cui, H. Yang, L. Kong, and Q. H. Liu. “Knowledge-aided Bayesian detection for MIMO radar in compound-Gaussian clutter with inverse Gamma texture.” In IEEE National Radar Conference - Proceedings, 2015-June:777–82, 2015. https://doi.org/10.1109/RADAR.2015.7131101.
Li N, Cui G, Yang H, Kong L, Liu QH. Knowledge-aided Bayesian detection for MIMO radar in compound-Gaussian clutter with inverse Gamma texture. In: IEEE National Radar Conference - Proceedings. 2015. p. 777–82.
Li, N., et al. “Knowledge-aided Bayesian detection for MIMO radar in compound-Gaussian clutter with inverse Gamma texture.” IEEE National Radar Conference - Proceedings, vol. 2015-June, no. June, 2015, pp. 777–82. Scopus, doi:10.1109/RADAR.2015.7131101.
Li N, Cui G, Yang H, Kong L, Liu QH. Knowledge-aided Bayesian detection for MIMO radar in compound-Gaussian clutter with inverse Gamma texture. IEEE National Radar Conference - Proceedings. 2015. p. 777–782.
Published In
IEEE National Radar Conference - Proceedings
DOI
ISSN
1097-5659
ISBN
9781479982325
Publication Date
June 22, 2015
Volume
2015-June
Issue
June
Start / End Page
777 / 782