Space, objects, and motor actions

2006 ◽  
Author(s):  
Michael E. J. Masson ◽  
Daniel N. Bub
Keyword(s):  
Space Objects ◽  
Motor Actions

Hazard of collisions of artificial space objects in geosynchronous orbits

2004 ◽  
Vol 10 (5-6) ◽  
pp. 159-162
Author(s):  
V.P. Epishev ◽  
◽  
I.I. Motrunich ◽  
V.U. Klimyk ◽  
◽  
...  
Keyword(s):  
Space Objects ◽  
Geosynchronous Orbits

TESTING OF GNSS RECEIVERS OF SPACE OBJECTS IN EARTH CONDITIONS AND THE IMPLEMENTATION OF SPOOFING USING SIMULATOR OF GNSS SIGNALS

2020 ◽  
Vol 79 (20) ◽  
pp. 1773-1783
Author(s):  
N. X. Ahn ◽  
A. G. Laush ◽  
Yu. Khomenko ◽  
V. I. Lutsenko ◽  
I. V. Lutsenko ◽  
...  
Keyword(s):  
Space Objects ◽  
Gnss Receivers

Research of dynamics of movement of space objects on geostationary orbits

1998 ◽  
Vol 3 (0) ◽  
pp. 17-23
Author(s):  
А. Г. Кириченко ◽  
В. У. Клімик ◽  
К. А. Кудак ◽  
Г. М. Мацо ◽  
М. І. Демчик
Keyword(s):  
Space Objects

Nanosecond Time-Tagging of Space Objects Images

2006 ◽  
Author(s):  
Martin Němec ◽  
Prof. I. Procházka ◽  
Prof. K. Hamal ◽  
Dr. Georg Kirchner ◽  
Franz Koidl ◽  
...  
Keyword(s):  
Space Objects

MODELING OF SPECTROERERGETIC CHARACTERISTICS OF SPACE OBJECTS IN THE OPTICAL RANGE

2018 ◽  
Vol 19 (2) ◽  
pp. 200-211
Author(s):  
A. I. Bogoyavlenskiy ◽  
◽  
A. A. Kamenev ◽  
M. M. Poluyan ◽  
A.A. Soluyanov ◽  
...  
Keyword(s):  
Optical Range ◽  
Space Objects

SPACE SURVEILLANCE SYSTEM’S SAR SIGNAL DETECTION RESULTS

2018 ◽  
pp. 63-68 ◽  
Author(s):  
A. V. Ksendzuk ◽  
A. A. Kanatchikov ◽  
P. A. Gerasimov
Keyword(s):  
Signal Detection ◽  
Surveillance System ◽  
Observation Interval ◽  
Pulse Repetition Frequency ◽  
Storage Device ◽  
Periodic Signal ◽  
Unknown Parameters ◽  
Software Optimization ◽  
Space Objects ◽  
Field Programmable

Special aspects of space objects radiotechnical surveillance system used for filling the space tracking and surveillance system (STSS) satellite catalogue described and analyzed. Special emphasis placed on spaceborne synthetic aperture radar signals detection. Parameters of the SAR signals estimated with the proposed radiotechnical surveillance system described. Two processing methods for unknown and partially known signals proposed and analyzed. Signal detection with incompletely known parameters performs with cumulative second-order statistic. Signal detection with unknown parameters performs for periodic signal in assumption that observation interval exceed pulse repetition frequency. Proposed methods implemented in hardware demonstrator of radiotechnical surveillance system. This demonstrator works in real-time on Field Programmable Gate Array or save data on storage device for post-processing. L-band Palsar2 signal detection results presented and analyzed. Further work for hardware and software optimization described.

METHOD FOR ESTIMATING PARAMETERS OF GENERALIZED MODEL OF LUMINOSITY OF SPACE OBJECTS BASED ON DATA FROM DIFFERENT RANGES

2018 ◽  
pp. 57-62
Author(s):  
E. I. Gundrova ◽  
A. P. Lukyanov ◽  
A. V. Pruglo ◽  
S. S. Ravdin
Keyword(s):  
Phase Angle ◽  
Real Data ◽  
Model Data ◽  
Space Object ◽  
Distribution Law ◽  
Generalized Model ◽  
Measurement Results ◽  
Space Objects ◽  
Reference Distance

Previously, the authors have proposed a generalized model for estimating the distribution law parameters of luminosity of space objects, assuming that not only successful but also unsuccessful measurement results are taken into account. Estimation was done on the data of observations under similar conditions: phase angle, range, sensibility of the telescope. The algorithm under such limitations was tested on model data and real measurements. Therefore, obtained results showed that algorithm did not fit for cases of changing range of space objects. In this work, the new algorithm, that allows to merge information from different ranges to the observed space object, is proposed. In this case, luminosity values are reduced to the ones at a reference distance of 1000 km considering sensibility of the telescope. To obtain estimates of the parameters the Cramer-Mises-Smirnov criterion is used. This algorithm was tested on model data and results of its work on real data were obtained. The data showed correct work of the algorithm and also confirmed the practicability of organization the registration of unsuccessful measurements.

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