Hitoshi Maeno

Maritime space understanding using multiple radar systems by iterative image reconstuction algorithm

Understanding a space where autonomous robots work is an open problem. In case of maritime space, it is also very important. For this purpose, marine radar has been used to acquire images around the maritime vehicles. However, radar images are easily distorted by signal attenuation with distance, blurring due to antenna directivity, reflection by obstructs, etc. There are some conventional methods to improve the image quality. However, there is a limitation due to the acquisition mechanism of radar systems. To overcome the limitation, this study shows a novel approach, which uses multiple radar images to understand the maritime space. The method estimates radar cross section (RCS) from multiple radar images by iterative image reconstruction algorithm. Performance of the proposed method is validated using actual radar images taken by marine radar system equipped on a ship. The experimental results showed that the proposed method presents a maritime space map with high image quality and without distance attenuation, sidelobe diffusion.

Marine radar system of systems for radar image quality improvement using EM algorithm

It is important to improve the quality of marine radar images because marine radar systems play a principle role of sea surveillance. However, it is difficult to recover signal strength decay with increasing distance, signals of behind objects and of shaded area. This paper proposes a new approach to improve radar image quality with system of systems (SoS) technology. The SoS is based on a ship-to-ship communication in which ships send and receive radar images, and the SoS constructs the high quality radar images using EM algorithm. Performance was validated using a computer simulation and using radar images acquired from a single radar system at multiple locations. The experimental results showed that the proposed method constructed high quality radar images, and recovered signal decay and signals of behind objects and of shaded area.