A constant false alarm rate (CFAR) target detector in non-homogenous backgrounds is proposed. Based on K-sample Anderson-Darling (AD) tests, the method re-arranges the reference cells by merging homogenous sub-blocks surrounding the cell under test (CUT) into a new reference window to estimate the background statistics. Double partition test, clutter edge refinement and outlier elimination are ...

Reliable radar constant false alarm rate (CFAR) detection is critical in dynamic clutter and jamming scenarios [2]. The existence of heterogeneities in practical operational environments renders the conventional cell averaging CFAR (CA-CFAR) ineffective. Heterogeneities arise due to the presence of multiple targets and clutter edges [3]. Alternative schemes have been developed to address this i...

Herein, a robust constant false alarm rate (CFAR) detector with ordered statistic of sub-reference cells (OSS-CFAR) is proposed in multiple target situations. This can improve background level estimation and reduce computational complexity using cells. The detection performance the OSS-CFAR conventional CFAR detectors situations are investigated compared computer simulations experimental data s...

ABSTRACT The performance characteristics of the cell averaging (CA), greatest of (GO), and smallest of (SO) constant false alarm rate (CFAR) processors in homogeneous environment are analyzed and compared when receiving antenna diversity is employed in the pseudonoise code acquisition of directsequence code division multiple access systems. From the simulation results, it is observed that the C...

The line spectrum estimation and detection problem are considered in this paper. We propose a CFAR-based Newtonized OMP (NOMP-CFAR) method which can maintain desired false alarm rate without the knowledge of noise variance. NOMP-CFAR consists two steps, namely, an initialization step step. In step, NOMP is employed to obtain candidate sinusoidal components. CFAR detector applied detect each fre...

A new detection algorithm based on constant false alarm rate (CFAR) algorithm, which is applicable to radar image with homogeneous background, is proposed in this paper. This algorithm firstly estimates the parameters of the probability model of background accurately. Then a conventional global CFAR is done using the results of estimation. In estimating the parameters of background, a novel ite...

This paper taught the performance of the proposed sensing models, namely, constant false alarm ratedynamic waveform detector (CFAR-DWD) are categorized as dynamic threshold (DT), two-stage (TS), and adaptive two-stage (ATS) detection for accurately detecting of the static-primary user (PU) signals, where the state of the PU signal not change during the sensing duration. Whereby it is carried ou...

The Hough detector is investigated with three types of Constant False Alarm Rate (CFAR) processors – an Adaptive censoring Post detection Integration (API CFAR) processor, a Binary Integration (BI CFAR) processor and an Excision with Binary Integration (EXC CFAR BI) processor in the presence of randomly arriving impulse interference. The detection probability and the average detection threshold...

1 Introduction Cell-Averaging Constant False Alarm Rate (CA CFAR) signal processing proposed by Finn and Johnson in [1] is often used for radar signal detection. The detection threshold is determined as a product of the noise level estimate in the reference window and a scale factor to achieve the design probability of false alarm. The presence of strong pulse jamming (PJ) in both, the test res...

In this paper we study the efficiency of CA CFAR BI, EXC CFAR BI and Adaptive CFAR PI detectors in strong pulse jamming. We achieve new results for the average decision threshold (ADT) using the minimum detectable signal (Pd=0.5). For comparison we use also the approach with Monte-Karlo simulation for estimation of the ADT of the studied CFAR detectors. Differently from other authors, we consid...