Our main objective is to enhance ship monitoring systems to ensure the safety and security of the maritime industry. Ships lacking detection system (AIS) transponders that are or in areas with limited radar vision will be targeted. Two object-oriented ship detectors based on faster R-CNNs are shown. These detectors function in the Doppler and temporal domain of airborne range compressed radar data and are trained on real data that includes ship signals. The proposed detectors are robust and perform admirably even when exposed to challenging inshore environments, like the Arctic Sea, and many targets. Because of these advancements, maritime security and safety are improved, and ship detection is now possible in near-real-time. Achieving accurate ship recognition in real-time while maintaining high recall performance is challenging for pixel-based algorithms, particularly in congested multimarket contexts. Avoid relying only on AIS and marine radars by supplementing ship monitoring systems with aerial radars.