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Небесная энциклопедия

Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Мониторинг СМИ

Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Применить Всего найдено 7. Отображено 7.
07-07-2023 дата публикации

Radar echo image target object processing method based on adaptive region growing method

Номер: CN116400351A
Автор: WANG DAZHI, LIU SHUAIWU, ZUO SHAOYAN, SUO LIUJIA, WANG XIAO, CAI FENG, LIU DEWANG, ZHAO YONGQING, YANG BO, YU KAIBO
Принадлежит:

The invention relates to the technical field of remote sensing, in particular to a radar echo image target object processing method based on an adaptive region growing method. The method comprises the following steps: selecting a sea wave parameter inversion area in a radar sea surface echo image and converting the sea wave parameter inversion area into Cartesian coordinates; determining the position of a target object in the image based on a self-adaptive region growth judgment algorithm; a radar echo image is processed by three steps of removing a target object and performing image filling based on a mean value filling transition algorithm. According to the adaptive region growing method provided by the invention, the target interference of the radar image can be removed, and the precision of subsequent information extraction is improved.

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Номер записи: 1
28-07-2023 дата публикации

Quality improvement method for radar echo image

Номер: CN116503268A
Автор: CAI FENG, WANG XIAO, WANG DAZHI, YANG BO, LIU SHUAIWU, ZUO SHAOYAN, SUO LIUJIA, LIU DEWANG, ZHAO YONGQING, YU KAIBO
Принадлежит:

The invention relates to the technical field of remote sensing, in particular to a quality improvement method for a radar echo image. The method comprises the following steps: selecting a sea wave parameter inversion area in a radar sea surface echo image and converting the sea wave parameter inversion area into Cartesian coordinates; on the basis of a two-layer judgment median filtering algorithm, same-frequency interference processing in the image is carried out, target object interference in the sea wave image is segmented on the basis of a self-adaptive region growth repairing method, and an original target object region is repaired. Through verification, the image processed by the algorithm can finally obtain a clear sea wave image, and the accuracy of information extraction is improved.

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Номер записи: 2
28-05-2014 дата публикации

Small substrate type fiber Bragg grating strain transducer

Номер: CN103822591A
Автор: LI HONGWEI, LI LING, SUO LIUJIA, CHEN TAO, LIU CIJUN
Принадлежит:

The invention discloses a small substrate type fiber Bragg grating strain transducer. The small substrate type fiber Bragg grating strain transducer comprises a packaging substrate, a hollow metal protecting body and an optical fiber, wherein the metal protecting body is connected to one surface of the packaging substrate, an optical fiber containing cavity is formed by an inner cavity of the metal protecting body, the optical fiber is located in the optical fiber containing cavity completely, the optical fiber is engraved with a first Bragg grating used for strain measurement and a second Bragg grating used for temperature compensation of the first Bragg grating, and the portions, located at the two ends of the first Bragg grating, of the optical fiber are connected with the inner wall of the metal protecting body after the optical fiber is pre-tensioned. The small substrate type fiber Bragg grating strain transducer has the advantages that the size is small, the weight is low, and the ...

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Номер записи: 3
28-07-2023 дата публикации

Radar image derivation and database expansion method

Номер: CN116503716A
Автор: WANG DAZHI, ZUO SHAOYAN, LIU SHUAIWU, SUO LIUJIA, WANG XIAO, CAI FENG, LIU DEWANG, ZHAO YONGQING, YANG BO, YU KAIBO
Принадлежит:

The invention provides a radar image derivation and database expansion method, and the method comprises the specific steps: firstly building a three-dimensional sea wave surface, adding modulation information and a simulation radar wave surface image into a three-dimensional numerical wave surface through a radar imaging principle, and forming a simulation radar image database; secondly, acquiring an actual measurement radar image, converting a polar coordinate radar image into a Cartesian coordinate, preprocessing the polar coordinate radar image, performing adaptive binaryzation on the preprocessed radar image, and performing closed operation and gray filling on the basis of the adaptive binaryzation to form an actual measurement radar wave surface image database; and finally, fusing the simulation radar image database and the processed actual measurement radar image database, and expanding the radar wave surface image database. The method effectively solves the problem that when an artificial ...

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Номер записи: 4
07-07-2023 дата публикации

Radar echo image sea wave texture detection method based on correlation analysis

Номер: CN116400352A
Автор: WANG DAZHI, ZUO SHAOYAN, LIU SHUAIWU, SUO LIUJIA, WANG XIAO, CAI FENG, LIU DEWANG, ZHAO YONGQING, YANG BO, YU KAIBO
Принадлежит:

The invention relates to the technical field of remote sensing, in particular to a radar echo image sea wave texture detection method based on correlation analysis. The method comprises the following steps: selecting a sea wave parameter inversion area in a radar sea surface echo image and converting the sea wave parameter inversion area into Cartesian coordinates; based on a self-adaptive layer-by-layer proofreading algorithm, gray anomaly self-adaptive detection of the sea wave texture is carried out; based on an improved mean correlation coefficient algorithm, calculating a mean correlation coefficient in the azimuth direction of the radar echo image; and comparing the mean correlation coefficient with a sea wave texture characteristic judgment threshold, and judging whether the selected region has sea wave texture characteristics or not. Experiments prove that the method can effectively screen out the images containing the sea wave textures for exploration experiments.

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Номер записи: 5
28-07-2023 дата публикации

Radar wave surface image sea wave parameter inversion method based on deep learning

Номер: CN116500611A
Автор: WANG DAZHI, ZUO SHAOYAN, LIU SHUAIWU, SUO LIUJIA, WANG XIAO, CAI FENG, LIU DEWANG, ZHAO YONGQING, YANG BO, YU KAIBO
Принадлежит:

The invention discloses a radar wave surface image sea wave parameter inversion method based on deep learning, and the method comprises the steps: employing an original radar wave surface image collected by a navigation radar, selecting a proper inversion region, carrying out the coordinate transformation, carrying out the preprocessing of the radar wave surface image, and building a radar wave surface image standard database; according to the method, the image data in the database is input into the convolutional neural network, feature extraction is carried out, finally, feature values of the wave height and the period are output, sea wave parameter calculation is carried out, and finally, through comparison with calculation results of a buoy and a traditional method, the inversion method improves the calculation precision of the sea wave parameters.

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Номер записи: 6
07-07-2023 дата публикации

Calibration method for radar sea wave parameter measurement

Номер: CN116400307A
Автор: WANG XIAO, CAI FENG, WANG DAZHI, YANG BO, ZUO SHAOYAN, LIU SHUAIWU, SUO LIUJIA, LIU DEWANG, ZHAO YONGQING, YU KAIBO
Принадлежит:

The invention belongs to the technical field of ocean remote sensing, and relates to a calibration method for radar ocean wave parameter measurement. The method comprises the steps of measuring radar signal data under different sea conditions through radar signals generated by radar antenna incidence to the sea surface and reflection, analyzing and processing radar image data and a buoy database, constructing a calibration model of a deep convolutional neural network, forming a calibration algorithm for sea wave parameter measurement, and calibrating the radar image data. According to the method, the error of the sea wave parameter inversion by adopting the radar wave surface image is reduced, and the accuracy and the reliability of the sea wave parameter inversion are improved.

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Номер записи: 7