Performance Analysis of an Environmental Adaptive CFAR Detector

Sung Won Hong,Dong Seog Han

doi:10.1155/2014/615704

Abstract

The constant false alarm rate (CFAR) is a detection algorithm that is generally used in radar or sonar systems, but its performance depends greatly on the environment. This means that the detection performance cannot be satisfied with only a single CFAR detector. This paper evaluates mathematically a proposed environmental adaptive (EA) CFAR detector. The proposed CFAR detector selects an optimal CFAR detector depending on the environment. Computer simulations validate the mathematical analysis and robustness of the detector in homogeneous and nonhomogeneous backgrounds.

Highlights

The signal received in sonar or radar systems includes the target signal and noise and clutter signals
This means that the performance of the switching OS (SOS) constant false alarm rate (CFAR) detector in homogeneous environment can be worse than the cell averaging (CA) CFAR detector
To make a CFAR detector robust to range of background environments, this paper proposes a new CFAR detector called the environmental adaptive (EA) CFAR detector

Summary

Introduction

The signal received in sonar or radar systems includes the target signal and noise and clutter signals. In this case, the detection performance fluctuates according to the background environment [1,2,3]. The cell averaging (CA) CFAR detector shows the best performance in homogeneous environments. The excision CFAR detector was proposed to improve the detection performance in nonhomogeneous environments [5]. The SOS CFAR detector improves the detection performance but still has detection loss in homogeneous environment compared with that of the CA CFAR detector. This paper proposes an environmental adaptive (EA) CFAR detector to achieve the best performance regardless of the background environments. The proposed CFAR detector estimates the background conditions of the homogeneous and nonhomogeneous environments by comparing the power levels of the adjacent reference cells.

Conventional CFAR Detectors

Proposed Environmental Adaptive CFAR Detector

Simulation Results

Conclusions