Use is made of five sets of multibeam observations of the lower atmosphere made by the Indian mesosphere-stratosphere-troposphere (MST) radar. Two aspects of signal processing which can lead to serious underestimates of the signal-to-noise ratio are considered. First, a comparison is made of the effects of different data weighting windows applied to the inphase and quadrature components of the radar return samples prior to Fourier transformation. The relatively high degree of spectral leakage associated with the rectangular and Hamming windows can give rise to overestimates of the noise levels by up to 28 dB for the strongest signals. Use of the Hanning window is found to be the most appropriate for these particular data. Second, a technique for removing systematic dc biases from the data in the time domain is compared with the more well-known practice of correction in the frequency domain. The latter technique, which is often used to remove the effects of ground clutter, is shown to be particularly inappropriate for the characteristically narrow spectral width signals observed by the Indian MST radar. For cases of near-zero Doppler shift it can remove up to 30 dB of signal information. The consequences of noise and signal level discrepancies for studies of refractivity structures are discussed. It is shown that neither problem has a significant effect on Doppler shift or spectral width estimates.