The YOLO network has been extensively employed in the field of ship detection in optical
images. However, the YOLO model rarely considers the global and local relationships in the …

In marine radar target detection, sea clutter will cause a large number of missed alarms and
false alarms, which will affect the accuracy of target detection. In order to suppress sea …

The traditional constant false alarm rate (CFAR) method, with fixed parameter settings and
single noise background calculation, is unable to intelligently catch the current detection …

In this letter, we provide a general cell-averaging constant false alarm rate (CA-CFAR)
performance analysis considering homogeneous Weibull-distributed clutter environments …

As one of the main sensors for continuous maritime measurements of sea state parameters,
high-frequency surface wave radar (HFSWR) also plays an important role in ship detection …

Ship detection for SAR imagery plays a crucial rule in the field of remote-sensing image
processing. Superpixel methods have attracted enormous interest in the recent years …

The primary objective of radar digital signal processing is to detect and identify targets in
complicated situations, such as those involving clutter or several closely positioned targets …

Compact High frequency surface wave radar (HFSWR) has been widely used in remote
sensing of oceanic dynamics and ship targets due to their convenient deployment and low …

A compact high-frequency (HF) radar is a promising tool for maritime surveillance owing to
its over-the-horizon and all-weather ability. However, it typically suffers from low tracking …

This article presents a deep neural network‐based constant false alarm rate (NNB‐CFAR)
detector for simulated high‐frequency surface wave radar (HFSWR) data. A deep neural …