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...

In many practical situations, however, the environment is presence of strong pulse jamming (PJ) with high intensity; the pulse jamming is with binomial distribution. In this case, the pulse jamming can cause drastic degradation in the performance of Constant False Alarm Rate (CFAR) processors. In this paper, CA CFAR and CA CFAR BI (binary integration) processors in binomial distributed pulse ja...

In this paper we investigate the performance of a combined Compressive Sensing (CS) Constant False Alarm Rate (CFAR) radar processor under different interference scenarios using both the Cell Averaging (CA) and Order Statistic (OS) CFAR detectors. Using the properties of the Complex Approximate Message Passing (CAMP) algorithm, we demonstrate that the behavior of the CFAR processor is independe...

We propose a new constant false alarm rate (CFAR) detection method from noncoherent radar echoes, considering heterogeneous sea clutter. It applies the Bayesian theory for adaptive estimation of the local clutter statistical distribution in the cell under test. The detection technique can be readily implemented in existing noncoherent marine radar systems, which makes it particularly attractive...

A constant false alarm rate in the presence of variable levels of noise is usually a requirement placed on any modern radar. The CAand OS-CFAR detectors are the most widely used ones in the CFAR world . The cell-averaging (CA) is the optimum CFAR detector in terms of detection probability in homogeneous background when the reference cells have identical, independent and exponentially distribute...

Traditional constant false alarm rate (CFAR) detectors only use the contrast information between ship targets and clutter, and they suffer probability of detection (PD) degradation in multiple target situations. This paper proposes a correlation-based joint CFAR detector using adaptively-truncated statistics (hereafter called TS-2DLNCFAR) in SAR images. The proposed joint CFAR detector exploits...

Constant False Alarm Rate (CFAR) algorithms are used in digital signal processing applications to extract targets from background in noisy environments. Some examples of applications are target detection in radar environments, image processing, medical engineering, power quality analysis, features detection in satellite images, Pseudo-Noise (PN) code detectors, among others. This paper presents...

The constant false alarm rate (CFAR) matched subspace detector (CFAR MSD) is the uniformly most-powerful-invariant test and the generalized likelihood ratio test (GLRT) for detecting a target signal in noise whose covariance structure is known but whose level is unknown. Recently, the CFAR adaptive subspace detector (CFAR ASD), or adaptive coherence estimator (ACE), was proposed for detecting a...

A different technique of CFAR detectors procedure for moving target detection in noise environment conditions with a Poisson distributed flow and Raleigh amplitude distribution is proposed in this paper . The expressions of the detection and false alarm probability are derived for a highly fluctuating Swerling II target. A comparative analysis of the performance of different radar detectors str...