Discrete-time method for signal-to-noise power ratio measurement

Abstract

The measurement of signal-to-noise power ratio (SNR) is of fundamental importance in many areas of electrical engineering, such as communications, signal processing, tests and measurements, circuits and systems, etc. In this paper, we propose two algorithms for estimating the signal-to-noise ratio of a noisy sinewave from discrete-time data obtained by sampling the input signal. One algorithm is based on the estimation of the four parameters of the input sinewave. The second algorithm is based on estimating the average noise power by averaging the squared magnitude of the FFT bins attributed to the noise. Both methods show excellent performance. Simulation results indicate that the four-parameter method requires the input SNR to be at least 10 dB and the input signal frequency not exceeding one-third of the sampling frequency. On the other hand, the second approach, the spectrum averaging method, shows a remarkable robustness over a very wide range of normalized frequencies (with respect to the Nyquist frequency) and SNRs (well over 100 dB). This spectrum averaging method should prove to be very useful in a wide range of applications.