SAR (Synthetic Aperture Radar) image target detection method based on visual attention model and constant false alarm rate

Abstract

The present invention discloses an SAR (Synthetic Aperture Radar) image target detection method based on a visual attention model and a constant false alarm rate, which mainly solves the problems of a low detection speed and a high clutter false alarm rate in the existing SAR image marine ship target detection technology. The implementation steps of the method are as follows: extracting a saliency map corresponding to an SAR image according to Fourier spectrum residual error information; calculating a saliency threshold, so as to select a potential target area on the saliency map; detecting the potential target area by adopting an adaptive sliding window constant false alarm rate method, and obtaining an initial detection result; and obtaining a final detection result after removing a false alarm from the initial detection result, and extracting a suspected ship target slice, so as to complete a target detection process. The SAR image target detection method based on the visual attention model and the constant false alarm rate provided by the present invention has the advantages of a high calculation speed, a high target detection rate and a low false alarm rate, and meanwhile the method has the advantages of simpleness and easy implementation and can be used for marine ship target detection.

Description

technical field [0001] The invention belongs to the technical field of radar, in particular to a synthetic aperture radar SAR image target detection method, which can be used for sea surface ship target detection. Background technique [0002] Ship detection is of great significance to fishery supervision and maritime safety management. Monitoring and identifying marine ships is an important task for every coastal country. Because SAR has the ability of long-distance, all-time and all-weather observation, using SAR images to detect ships at sea has always been one of the hot spots in the field of marine remote sensing. [0003] The main idea of ​​ship target detection is to use the feature difference between the ship target and the surrounding sea area on the SAR image, and set a threshold for the feature for detection. The target features currently used for detection include grayscale features, polarization features, phase features, and multi-resolution features. Due to t...

AI Technical Summary

Problems solved by technology

This pixel-level detection method needs to traverse the entire SAR image. Each time the sliding window needs to perform statistical modeling and parameter estimation on the background clutter, the computational complexity is high, and it does not meet the real-time requirements of target detection.

At the same time, if the window size is not set properly, the pixels of the ship target are likely to leak into the background window, resulting in a decrease in the accuracy of clutter statistical modeling, making it easy to miss the detection of the ship target at a close distance.

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