A Robust Framework for Cancellation of MSK Interference in TEM Data

Abstract

Summary Data from surveys using the transient electromagnetic method (TEM) are inevitably corrupted by random noise. This noise, originating from both man-made and natural sources, is a limiting factor in the interpretation of the data. Radio signals in the VLF frequency range with encoded digital data make up a significant part of the noise power in the frequency range relevant to TEM. The topic of this work is cancellation of the noise contribution from VLF radio signals using the Minimum Shift Keying (MSK) modulation type. We present a framework for modeling and canceling MSK signals in TEM data, based on high-performance decoding methods from literature, combined with a tailored solution to make these methods work in the presence of powerful TEM signals. In contrast with a previously published method, this framework does not rely on assumptions regarding the signal, which do not always hold true. The effectiveness of the proposed framework is demonstrated using synthetic signals and compared with a reference framework similar to what has previously been published. In the experiments conducted, the proposed framework shows significant improvement compared to the reference framework.