When detecting targets of interest in satellite synthetic aperture radar (SAR) images, clustering is often required to construct the candidate pixels of an object. In this paper, we propose a new feature using principal component analysis to address the problem of dense targets that cause performance degradation when using the density-based spatial clustering of noise algorithm, which is suitable for the clustering process. Further, simulations are used to analyze the proposed features for different target and clutter clusters extracted from real TerraSAR-X (TSX) images, and the proposed dense target discrimination technique is applied to the TSX images. The simulation results reveal that the proposed feature is effective in distinguishing clusters composed of dense targets, and the target detection performance can be improved by re-separating dense target clusters from actual SAR images.
Low-altitude and high-speed targets that fly close to the sea level are generally detected using a single-band moving target indicator (MTI) technique. The MTI technique detects a moving target by filtering out the sea-clutter Doppler spectrum. However, when detecting a low-altitude, high-speed target flying close to the sea, blind speed problems can occur because of the fast maneuvering characteristics of the target. Moreover, multipath phenomena and false alarm may occur due to the influence of the sea. Such problems make detection difficult. In this paper, we propose a detector suitable for high-speed targets in sea conditions using dual-band radar. Low-altitude and high-speed targets were modeled by considering the maritime situation, and robust detection against blind speed and multipath phenomena was confirmed by applying the proposed technique to the average Doppler power of the received signal in each band. Finally, simulations for various speeds and distances of the target confirmed that the proposed method showed improved target detection performance than the existing single-band method when detecting low-altitude, high-speed targets in sea conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.