Comparison of ship detection algorithms using ALOS-PALSAR, ground-based maritime radar, and AIS

摘要

MLCC (Multi-Look Cross-Correlation) is a useful technique to extract the images of ships embedded in sea clutter from SAR (Synthetic Aperture Radar) data. However, the previous MLCC has a difficulty of detecting small ships since SNR (Signal-to-Noise Ratio) is not high enough. Therefore, we developed a new Improved MLCC (IMLCC) to increase SNR to extract small boats. Although the IMLCC method increased SNR, there still remained some highly correlated noises in the coherence images caused by strong radar backscatter from sea surface. In order to improve the IMLCC algorithm further, we propose a new method of applying Lognormal-CFAR (Constant False Alarm Rate) to IMLCC coherence images. The results using ALOS-PALSAR (Advanced Land Observing Satellite-Phased Array L-band SAR) data showed substantial improvement in SNR and detection rate.