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SAR 3D rotating ship target refocusing method based on cv-refocusnet

A three-dimensional rotation and refocusing technology, applied in neural learning methods, radio wave reflection/re-radiation, instruments, etc., can solve the problem of unrecognizable SAR ship target images, achieve good image processing effects, and ensure a large number of needs. Implement convenient effects

Active Publication Date: 2021-06-22
HARBIN INST OF TECH
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Problems solved by technology

[0004] Aiming at the problem in the prior art that blurred SAR ship target images cannot be recognized and obtained reliable results, the present invention provides a method for refocusing SAR three-dimensional rotating ship targets based on CV-RefocusNet

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  • SAR 3D rotating ship target refocusing method based on cv-refocusnet
  • SAR 3D rotating ship target refocusing method based on cv-refocusnet
  • SAR 3D rotating ship target refocusing method based on cv-refocusnet

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specific Embodiment approach 1

[0043] Specific implementation mode 1. Combination Figure 1 to Figure 4 Shown, the present invention provides a kind of SAR three-dimensional rotating ship target refocusing method based on CV-RefocusNet, comprising,

[0044]The SAR ship target image is obtained based on the 3D ship model and the ray tracing method simulation, and the SAR ship target image includes the SAR 3D rotating ship target image as a sample and the SAR stationary ship target image as a label; the SAR ship target image is The target image is grouped into a training sample library and a testing sample library;

[0045] Construct complex domain convolutional neural network CV-RefocusNet framework, described CV-RefocusNet framework comprises an input layer, four convolution layers and four deconvolution layers, wherein the 4th deconvolution layer is as output layer; CV- The input, output, activation function and weight of the RefocusNet architecture all belong to the complex field;

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Abstract

A CV‑RefocusNet-based SAR three-dimensional rotating ship target refocusing method belongs to the field of SAR image processing. Including: SAR sample generation, network architecture design, and refocusing implementation; the SAR sample generation part is responsible for generating SAR three-dimensional rotating ship target images to form a training sample library and a test sample library. The network architecture design part gives the CV‑RefocusNet network Architecture, clarification of network design details, refocusing implementation part based on CV‑RefocusNet, training and testing the SAR 3D rotating ship target sample library, and realizing the refocusing function. The invention can realize the refocusing of the SAR three-dimensional rotating ship target and obtain a clear target image.

Description

technical field [0001] The invention relates to a CV-RefocusNet-based SAR three-dimensional rotating ship target refocusing method, belonging to the field of SAR image processing. Background technique [0002] The ship target sails on the sea, affected by the sea conditions and its own movement, there is a three-dimensional rotation. The imaging result of the same ship target is relatively clear in the static state, but in the three-dimensional rotating state, the imaging result is very blurred. This is because there is a three-dimensional rotation component of the ship target at sea, which makes the SAR (Synthetic Aperture Radar) imaging results blurred under high sea conditions, and the higher the sea conditions, the more serious the blur. The fuzzy SAR ship target image brings great difficulties to the subsequent information extraction and recognition process. [0003] Existing SAR information extraction and recognition algorithms can only achieve more accurate recognit...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08G01S13/90G01S13/937
CPCG06N3/08G01S13/9004G01S13/937G06V2201/07G06N3/045G06F18/214
Inventor 张云化青龙姜义成徐丹
Owner HARBIN INST OF TECH
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