SAR image ship target detection and recognition integrated method based on deep learning

Abstract

The invention belongs to the technical field of radar remote sensing application, and particularly relates to an SAR image ship target detection and recognition integrated method based on deep learning. An important part of SAR image ship target interpretation is detection and identification, but all detection and identification are independent at present, and a detection and identification integrated method is an important research direction of SAR image interpretation in the future. Existing traditional methods and deep learning methods for target detection and recognition cannot achieve detection and recognition integration of SAR image ship targets. The invention provides an SAR image ship target detection and identification integrated method. Through an existing deep learning networkframework, a network used for SAR image ship target detection and identification integration is provided. Detection and classification tasks of ship targets are carried out at the same time by mainlyutilizing a detection and classification sub-network at the tail end of a network, so that a detection and identification integrated target is realized. Compared with a traditional ATR technology, thedetection and recognition process of the method is simpler and more efficient.

Description

Technical field [0001] The invention belongs to the technical field of radar remote sensing application, and specifically relates to an integrated method for detecting and identifying ship targets in SAR images based on deep learning. Background technique [0002] Synthetic Aperture Radar (Synthetic Aperture Radar, hereinafter referred to as SAR) is an active sensor that uses microwave imaging. Compared with optical and infrared sensors, SAR can work around the clock and has a certain penetration capability. Therefore, SAR technology has been widely used in civil and military fields. With the development of SAR imaging technology, the field of SAR image target detection and recognition faces many opportunities and challenges. The detection and recognition of ship targets in SAR images is an important part of modern maritime intelligent monitoring systems, so the interpretation of ship targets in SAR images is a current research hotspot. [0003] The traditional SAR image automati...

AI Technical Summary

Problems solved by technology

However, slice-based classification methods are not ideal for practical scenarios

At present, the ship target automatic recognition method based on SAR images can integrate ship target detection and rough classification. Rough classification refers to dividing ships into large ships and small ships according to the size of the ship. Obviously, rough classification cannot meet the practical requirements.

Therefore, the ship target in SAR image based on deep learning cannot realize automatic identification in the true sense.

[0005] An important part of SAR image ship target interpretation is detection and recognition, but currently all detection and recognition are independent

The integrated method of detection and recognition is an important research direction of SAR image interpretation in the future. The existing traditional methods and deep learning methods of target detection and recognition cannot realize the integration of detection and recognition of ship targets in SAR images.

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