Differential Ranging Method of Locating Satellite Communication System Earth Stations using Repeater on an Unmanned Aerial Vehicle

Abstract

The article presents the differential ranging method of locating modern earth stations with narrow radiation patterns. Earth station position data is proposed to be calculated using maximum-likelihood procedure system solution from three differential equations using one of numerical methods. In this case supplementary assessment parameter of location, calculated by measuring a mutual signal delay of an earth station, relayed through a spacecraft on geostationary orbit and a mobile repeater on the unmanned aerial vehicle, can improve the accuracy of coordinate estimation earth station.
 For the developed method the analytical expressions of potential accuracy of calculation of coordinates of the earth station on the basis of the Cramer–Rao lower bound are developed.
 To measure the positioning accuracy of located emitters it is suggested to use the errors ellipsoid corresponding to the provision of a source of a radio emission in space.
 The analysis of standard routes of the movement of a repeater on the unmanned aerial vehicle is carried out and the conclusion is drawn that the best accuracy and the shortest route simultaneously are achieved, if the unmanned aerial vehicle follows a circular trajectory along the control area.
 Calculation of potential accuracy of positioning of the terrestrial station for the area of 50 by 50 km is executed.It is shown that the error of the estimates, received as a result of statistical tests, doesn’t surpass the size of a big half shaft of the error ellipsoid calculated with application of analytical expressions.
 The application of the developed method is possible in the implementation of the software of electronic control systems to counteract illegitimate use of frequency resource of space vehicles-satellite repeaters communication system.

Difference-range method of estimating coordinates of radio emission sources based on artificial neural networks with bearing in the distant zone

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