SAR ship target classification method based on deep dense connection and metric learning

Abstract

The invention discloses an SAR ship target classification method based on deep dense connection and metric learning, and mainly solves the problems of inaccurate feature extraction and poor classification effect in the prior art. According to the scheme, the method comprises the following steps: 1) acquiring ship target SAR image training data, and expanding the ship target SAR image training data; 2) establishing a network model composed of a deep dense connection layer and an embedded conversion layer; 3) sending the expanded training data into the network constructed in the step 2), and using cross entropy loss with L2 norm regular terms to perform preliminary training on the network; 4) adding the triple loss and a Fisher discrimination criterion-based regular term into the loss function in the step 3), and sending training data to continue to train the network model to obtain a finally trained network model; and 5) sending the test data to the trained network model to obtain a ship classification result. According to the method, deep feature extraction can be better completed, the classification performance is improved, and the method can be used for sea area ship monitoring and target classification.

Description

technical field [0001] The invention belongs to the technical field of radar target recognition, and mainly relates to a method for classifying ship targets in SAR images, which can be used for ship monitoring and target classification in sea areas. Background technique [0002] Synthetic aperture radar is an active imaging sensor with all-weather, all-time, high-resolution data acquisition capabilities. In order to realize continuous, real-time and long-term monitoring of vast sea areas, the SAR system has developed rapidly with its high resolution and wide coverage. At present, the use of spaceborne SAR systems to monitor ships in sea areas has become an important means, and has been widely used in national defense intelligence, fishery monitoring and law enforcement, search and rescue support, and shipping. In the past few decades, various satellite SAR systems have been successfully launched, such as Canadian RADARSAT-1 / 2, German TerraSAR-X, Italian Cosmo-SkyMed, Europe...

AI Technical Summary

Problems solved by technology

These changes are difficult to accurately describe with traditional geometric and radiation features, which increases the difficulty of identification

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