Adaptive radar detection in the presence of Gaussian clutter with symmetric spectrum

Chengpeng Hao; Antonio De Maio; Danilo Orlando; Salvatore Iommelli; Chaohuan Hou

ICASSP 2016accepted0 citations

Adaptive radar detection in the presence of Gaussian clutter with symmetric spectrum

Chengpeng Hao, Antonio De Maio, Danilo Orlando, Salvatore Iommelli, Chaohuan Hou

Abstract

In this paper, we address the problem of detecting the signal of interest in the presence of Gaussian clutter with symmetric spectrum. To this end, we exploit the spectral properties of the clutter to transfer the binary hypothesis test problem from complex domain to real domain. Then, we devise and assess a detection strategy based on the so-called two-step Generalized Likelihood Ratio Test (GLRT) design procedure. Finally, a preliminary performance assessment, conducted by resorting to simulated data, has confirmed the effectiveness of the newly proposed detector compared with the traditional state-of-the-art counterparts which ignore the spectrum symmetry.

BibTeX

@inproceedings{icassp2016_adaptiveradardet,
  title = {Adaptive radar detection in the presence of Gaussian clutter with symmetric spectrum},
  author = {Chengpeng Hao and Antonio De Maio and Danilo Orlando and Salvatore Iommelli and Chaohuan Hou},
  booktitle = {ICASSP 2016},
  year = {2016}
}