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

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 anal-
ysis 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.
... mehr
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.