Statistical Efficiency of Sinewave Fitting When Using Non-Linear Quantizers
Antonio Moschitta, Paolo Carbone · 2006
In this paper, the Cramer-Rao lower bound on the estimation of the parameters of a noisy sinewave based on quantized data is discussed. The effects of overloading noise and integral non-linearity are considered and modeled, assuming both coherent and non-coherent signal sampling. It is shown that a simplified model can be derived, which describes the Cramer-Rao lower bound by considering only the most frequently excited ADC transition levels. Then the effects of quantization on the sinewave fitting statistical efficiency are investigated