scholarly journals Adaptive Planning Method for Operations of a Multi-satellite Swarm for Earth Remote Sensing in Real Time

Author(s):  
Petr Skobelev ◽  
Elena Simonova ◽  
Vladimir Galuzin ◽  
Anastasiya Galitskaya ◽  
Vitaly Travin
2018 ◽  
Vol 51 (32) ◽  
pp. 451-455 ◽  
Author(s):  
Vasiliy Sazonov ◽  
Sofia Sazonova ◽  
Ivan Samylovskiy ◽  
Arseniy Sapelkin ◽  
Stanislav Budzinskiy ◽  
...  

2019 ◽  
Vol 75 ◽  
pp. 01005 ◽  
Author(s):  
Mikhail V. Saramud ◽  
Igor V. Kovalev ◽  
Vasiliy V. Losev ◽  
Mariam O. Petrosyan ◽  
Dmitriy I. Kovalev

The article describes the use of a multi-version approach to improve the accuracy of the classification of images when solving the problem of image analysis for Earth remote sensing. The implementation of this approach makes it possible to reduce the classification error and, consequently, to increase the reliability of processing remote sensing data. A practical study was carried out in a multi-version real-time execution environment, which makes it possible to organize image processing on board of an unmanned vehicle. The results confirm the effectiveness of the proposed approach.


Author(s):  
Aleksandr P. DANYLKIN ◽  
Vladimir N. VORONKOV ◽  
Oleg Yu. KAZANTSEV ◽  
Vyacheslav A. KETOV ◽  
Yury N. KOPTEV ◽  
...  

The paper presents basic results of exploratory design studies into a space system for real-time monitoring of the Earth surface based on small spacecraft* for Earth remote sensing, which provides acquisition in real time of highly detailed Earth surface images with resolution of 0.7–1.0 m, a swath of 20 km and 15m in-plane georeferencing accuracy from a ~300 km orbit with a mass of spacecraft ~200 kgf repeating with high frequency (at least every 1.0–1.5h). The said parameters are in line with the current state of the art and are quite feasible for our country’s industry. _________________________________________ * — for the purposes of this paper ‘small spacecraft’ is a 150-220 kg spacecraft. Key words: small spacecraft, space system, Earth remote sensing, satellite bus, payload module, electro-optical equipment, multipurpose ground facility, combined ground station, services of space monitoring of the Earth surface.


Author(s):  
Aleksandr P. DANYLKIN ◽  
Vladimir N. VORONKOV ◽  
Oleg Yu. KAZANTSEV ◽  
Vyacheslav A. KETOV ◽  
Yury N. KOPTEV ◽  
...  

The paper presents basic results of exploratory design studies into a space system for real-time monitoring of the Earth surface based on small spacecraft* for Earth remote sensing, which provides acquisition in real time of highly detailed Earth surface images with resolution of 0.7–1.0 m, a swath of 20 km and 15m in-plane georeferencing accuracy from a ~300 km orbit with a mass of spacecraft ~200 kgf repeating with high frequency (at least every 1.0–1.5h). The said parameters are in line with the current state of the art and are quite feasible for our country’s industry. _________________________________________ * — for the purposes of this paper ‘small spacecraft’ is a 150-220 kg spacecraft. Key words: small spacecraft, space system, Earth remote sensing, satellite bus, payload module, electro-optical equipment, multipurpose ground facility, combined ground station, services of space monitoring of the Earth surface.


Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.


2007 ◽  
Vol 13 (2) ◽  
pp. 39-42
Author(s):  
A.I. Kirillov ◽  
◽  
Ye.I. Kapustin ◽  
N.A. Kirillova ◽  
E.I. Makhonin ◽  
...  

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