Abstract Due to limitation of space in mine tunnel, only a 2m × 2m rectangle coil can be employed to collect the electromagnetic signals for the mine transient electromagnetic analysis. Hence, a small emission magnetic moment and weak detection signal strength will increase the electromagnetic analysis difficulty. Moreover, the transient electromagnetic response signal in mines exhibits exponential decay over time, with late-stage amplitudes being notably small, which makes these signals susceptible to noise interference. As a result, it is necessary to study effective noise removal methods to enhance the signal-to-noise ratio of the late-stage electromagnetic data. Addressing this challenge task, this study proposes a new method for frequency domain denoising of transient electromagnetic data. This new method utilizes the Fourier Transform to convert the original transient electromagnetic data from the time domain to the frequency domain, and then, the noise is identified and removed through the frequency characters. Lastly, the processed frequency domain information is transformed to the time domain by the Fourier Inverse Transform to restore the time domain signals. The effect of this frequency domain denoising method is demonstrated through numerical simulations and underground coal mine field data to show significant noise reduction performance on the abnormality detection in the underground coal mine.