Study of Improved Sorting Weighting CFAR Detectors for Gaussian Environment

Authors

Souad Chabbi, Frères Mentouri University, Constantine, AlgeriaFollow
khadidja belhi, Frères Mentouri University, Constantine, AlgeriaFollow
M'HAMED HAMADOUCHE, University of Boumerdes, Boumerdes, AlgeriaFollow

Date of Acceptance

October 2023

Date of Submission

August 2023

Abstract

The goal of this paper is to improve the detection performance and the false alarm regulation of the conventional order statistics Constant False Alarm Rate (OS-CFAR) detectors in a non-homogeneous Gaussian environment. To this end, we design and study the New Sorting Weighting (NSW-) and the Modified Sorting Weighting (MSW-) CFAR detectors. We find closed forms of the detection ( ) and the false alarm ( ) probabilities for both detectors. Moreover, we identify the optimum pairs of weights that maximize the and ensure a constant . Finally, we prove through Monte Carlo simulations that these detectors provide better detection performance and false alarm regulation than the order statistics conventional ones in various clutter situations with the NSW-CFAR detector being the best one.

Recommended Citation

Chabbi, Souad; belhi, khadidja; and HAMADOUCHE, M'HAMED (2023) "Study of Improved Sorting Weighting CFAR Detectors for Gaussian Environment," Emirates Journal for Engineering Research: Vol. 28: Iss. 3, Article 2.
Available at: https://scholarworks.uaeu.ac.ae/ejer/vol28/iss3/2