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The combination of a median filter and a neural network interpolation for terrestrial objectives motion trajectory estimation


A.V. Zhuravlev – Ph. D. (Eng.), Senior Research Scientist, Main Designer – Deputy General Director,
JSC «SPE «PROTEK» (Voronezh)
V.G. Markin – Leading Engineer, JSC SPE «PROTEK» (Voronezh)

One of the main mobile devices (MD) control problems is the issue of determination of their location. This problem can be solved by a number of various methods, including the measurement of the distances between MD and the base stations of a local terrestrial radio navigational system (LRNS) with the further processing in order to determine the location with the use of algorithms typical of the distance measuring systems.
The present article aims to develop a procedure of the MD motion trajectory estimation error reduction applying the filtration of the measured location data.
The author offers to reduce errors by an innovative approach, based on the joint use of a median filter and a neural network with a polynomial interpolation and the calculated location data prediction. The median filter successfully copes with impulse interference. The polynomial interpolation and prediction of the measurements with the use of the neural network allows to successfully cope with the both types of interference.
To enhance the mobile device motion trajectory estimation effectivity, the author offers using the median filter advanced by the chain processed by a regular median filter addition. This regular filter is interpolated and predicted by the measurements values, obtained as a result of the polynomial interpolation and prediction.
The numerical modelling results have showed the high effectivity of motion trajectory estimation in the conditions of Gaussian noise and impulse jam impact on the measurement of the distances between a mobile device and the base stations of LRNS.

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June 24, 2020
May 29, 2020

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