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Wednesday, November 15 • 11:00 - 11:20
Multi-Parameter Estimation of Multiple Sinusoidal Signals in the Presence of Additive White Gaussian Noise

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A new algorithm for estimating the multiple parameters (amplitude, phase and frequency) of a sinusoidal signal composed of the sum of multiple sinusoids and corrupted by additive white Gaussian noise is presented. This algorithm uses adaptive notch filters (ANFs) and a linear model. For the case where the frequencies of the sinusoids are among the unknown parameters, the ANFs first provide an accurate estimate of the frequency for each sinusoid. The linear model then uses the estimated frequencies to jointly estimate the corresponding amplitude and phase. For the case where the frequencies of the sinusoids are known but the amplitudes and phases are unknown, the linear model is used to obtain joint estimates of the amplitude and phase. Simulation examples are carried out to show the effectiveness of this algorithm. It is shown that the Cramer-Rao lower bound is asymptotically attained in most cases. The sensitivity of the linear model to the estimates of the ANF is also discussed.


Wednesday November 15, 2017 11:00 - 11:20
Salon A/B 180 Portugal Cove Rd, St. John's, NL A1B 2N4, Canada