Discrete-time method for signal and noise measurement

Signal and noise measurement, especially the measurement of signal to noise power ratio (SNR) is of fundamental importance in many areas of electrical engineering, such as communications, signal processing, test 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 underline 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 shows excellent performance. Simulation results indicate that the lour parameter method requires the input SNR to be at least 10 dS and the input signal frequency not exceeding one third of the sampling frequency. On the other hand, the second approach, the spectrum average 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 average method should prove to be very useful in a wide range of applications