  Magnetogastrogram (MGG) signal frequency is about 0.05 Hz, the low-frequency
environmental noise interference is serious and can be several times stronger
in magnitude than the signals of interest and may severely impede the
extraction of relevant information. Wiener filter is one classic denoising
solution for biomagnetic applications. Since the reference channels are usually
placed not far enough from the biomagnetic sources under test, they will
inevitably detect the signals and the Wiener filters may produce
ill-conditioned solutions. Considering the solutions to improve the
signal-to-noise ratio (SNR) of Wiener filter output, there are few methods to
separate the signals from the noises of the reference signal at the filter
input. In this paper, a new signal processing framework called signal-noise
separation based Wiener filter (SNSWF) is proposed that it separates the main
noise as the input signal of the filter to improve the output SNR of Wiener
filter. The filter was successfully applied to the noise suppression for MGG
signal detection. Using the SNSWF, the filter SNR is 16.7 dB better than the
classic Wiener filter.
