A New Adaptive Linear Combined Cfar Detector in Presence of Interfering Targets

Abstract

Abstract-In this paper, a new radar constant false alarm rate detector to perform adaptive threshold target detection in presence of interfering targets is proposed. The proposed CFAR detector, referred to as Adaptive Linear Combined CFAR, ALC-CFAR, employs an adaptive composite approach based on the well-known cell averaging CFAR, CA-CFAR, and the ordered statistics, OS-CFAR, detectors. Data in the reference window is used to compute an adaptive weighting factor employed in the fusion scheme. Based on this factor, the ALC-CFAR tailors the background estimation algorithm. The conducted Monte Carlo simulation results demonstrate that the proposed detector provides low loss CFAR performance in an homogeneous environment and also performs robustly in presence of interfering targets. The performances of the ALC-CFAR detector have been evaluated and compared with that of the CA-CFAR and the OS-CFAR detectors. The obtained results are presented and discussed in this paper.

Performance analysis of ordered CFAR detectors for MIMO radars

“…In practice, the environment is usually non-homogeneous due to the presence of multiple targets and/or clutter edges in the reference window. Consequently, there is a significant decrease in performance when the assumption of homogeneous environment is not met [12]. For this, Rohling [13] proposed the Ordered Statistics (OS) CFAR detector.…”

Performance Analysis of an Environmental Adaptive CFAR Detector

“…Conventional CFAR detectors adopt only a single CFAR processor, as shown in Figure 1. In this case, however, 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.…”

A Homogenous Reference Cells Selector for Cfar Detector in Highly Heterogeneous Environment

“…Adaptive constant false alarm rate (CFAR) detectors are widely used in radar systems. In these schemes, the CFAR detectors are based on the assumption that the reference cells share the identical statistical characteristic with the cell under test (CUT) [1][2][3][4][5][6][7], i.e., the background is homogenous. Unfortunately, in many real-world scenes, the homogeneity assumption is not satisfied any more, e.g., from water to land.…”