Robust cancellation of minimum shift keying-encoded radio interference in data from the transient electromagnetic method

Abstract

Interference from radio signals in the very low frequency (VLF, 3–30 kHz) band constitutes a significant part of the noise in data, measured using the transient electromagnetic method (TEM). Most radio signals in this frequency band convey streams of binary data, encoded using minimum shift keying or variants thereof. We have developed a framework for cancellation of these signals by modeling and subtracting the interfering signals from the recorded data. The framework uses several techniques to ensure robust and accurate modeling of the radio signals in a typical airborne TEM environment. These include combination of signals from multiple receiver coils, tracking of time-varying parameters for each receiver coil, use of a priori knowledge pertaining to the TEM primary field, and use of a high-performance decoding algorithm. Examples using recorded noise data from the field combined with synthetic TEM signals indicate a significant reduction in noise power. This results in a reduction of the standard deviation of approximately 1.5–4 times in the early to intermediate-time response, after common processing steps have been applied. In the late-time part of the response, little to no improvement is seen. Although the attainable improvement in signal quality is highly case dependent, we expect that significant noise reduction can be achieved in most cases. Despite not being tested, our framework should be directly applicable in the low frequency (LF, 30–300 kHz) band, which has relevance for wide-band systems.