New log-t-based CFAR detectors for a non-homogeneous Weibull Background

Detouche, Nedjma; Laroussi, Toufik; Madjidi, Hicham

doi:10.1016/j.phycom.2023.102085

Cited by 4 publications

(2 citation statements)

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“…The following figure (Figure 12) illustrates the probability density function of the signal X(m) and shows that the radar echo at the output of the proposed detector follows an exponential distribution [23]. We clearly see that the histogram of the radar echo X(m) (see Figure 12) is exponential in shape independently of the clutter model at the input of the proposed detector.…”

Section: Doppler Filter Bankmentioning

confidence: 93%

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Clutter Map Constant False Alarm Rate Mixed with the Gabor Transform for Target Detection via Monte Carlo Simulation

Mbouombouo Mboungam,

Zhi,

Fonzeu Monguen

2024

Applied Sciences

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Radar detection is a technology frequently used to detect objects and measure the range, angle, or velocity of those objects. Several studies have been performed to improve the accuracy and performance of detection methods, but they encountered a strong challenge, which was the minimization of false alarms and the distinguishing of real targets from false alarms, especially in nonhomogeneous environments. We propose a new detection method that uses time-frequency analysis tools to improve detection performance and maintain a low constant false alarm rate. Different from existing works, this paper combines the clutter map constant false alarm rate technique with the Gabor transform for accurate target detection in cluttered environments. We suggest the combination of a CFAR detector with a time-frequency method that enables us to tackle challenging scenarios involving near targets. The proposed method allows for locating the exact position of the target by reducing the impact of clutter and maintaining a low rate of false alarms, while the Gabor transform facilitates the extraction of pertinent target characteristics and improves differentiation from clutter. Through experiments and simulations in different scenarios and clutter models, we demonstrate that the method is efficient in measurements and performs well in cluttered environments. This research has a major impact on signal processing and significantly improves target detection in cluttered environments, allowing this method to be deeply developed and implemented.

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Section: Doppler Filter Bankmentioning

confidence: 93%

Section: Doppler Filter Bankmentioning

confidence: 99%