Аннотация:Recovery of magnetic target parameters from magnetic sensor measurements has
attracted wide interests and found many practical applications. However, difficulties present
in identifying the magnetization due to the complications of magnetization distributions over
investigated object, errors and noises of measurement data, degrade the accuracy and quality
of the restored parameters. In this paper we consider a modern model for the mentioned
problem (magnetic inversion based on both total magnetic intensity data and full tensor
gradient magnetic data) and some method of its solving. This method involves taking into
account the round-off errors, accumulation of which could significantly influences the restored
solution in the case of using model with full tensor gradient magnetic data. Tikhonov regularization
has been applied in solving the inversion problem with the modified generalized
discrepancy principle (that include information about accumulated round-off errors) for the
choosing regularization parameter.