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JOURNALS // Upravlenie Bol'shimi Sistemami // Archive

UBS, 2025 Issue 116, Pages 342–365 (Mi ubs1311)

Simulation Tools for Control Systems and Controlled Objects

Compensation of interference in airborne electromagnetic systems and modeling of the geological environment by the inversion method in the processing of airborne electrical survey data

L. Vlasov, D. Kaplun, E. A. Tretyakova, D. Khliustov

V.A. Trapeznikov Institute of Control Sciences of RAS, Moscow

Abstract: Various methods of induced interference compensation for the EQUATOR system and several modifications of the EM4H onboard electromagnetic system were compared. Two modifications of the EM4H were investigated: the system with a transmitter loop mounted on the fuselage of the An-3 aircraft and the system with a loop towed by the Eurocopter AS350B3 helicopter. Two methods of modeling transmitter signal interference are considered: in the form of a stationary systematic component of measurements and in the form of a stationary field vector rigidly connected to the transmitter. To implement the second approach, two additional dipoles are used in EM4N and EQUATOR to determine the relative positions of the transmitter and receiver. The analysis was performed for data obtained during the flights at high altitudes with no response from the ground. The following statistical parameters of signals remaining after interference compensation were analyzed: standard deviation and the difference between the minimum and maximum values. It is shown that the best compensation result is obtained by an approach that takes into account the movement of the receiver relative to the field source (transmitter). The next step was to provide interpretation of data with the objective of estimating important geophysical characteristics. For each of studied systems Kalman filter algorithm was applied providing resistivity maps, which have been compared with respect to resolution.

Keywords: compensation, transmitter, receiver, magnetic dipole, airborne electromagnetics, one dimensional model, Kalman filter.

UDC: 527.62+ 519.24
BBK: 30â6

Received: February 24, 2025
Published: July 31, 2025

DOI: 10.25728/ubs.2025.116.15



© Steklov Math. Inst. of RAS, 2025