In this paper, the Cramér-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 Cramér-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
Statistical Efficiency of Sinewave fitting When Using Non-Linear Quantizers
MOSCHITTA, Antonio;CARBONE, Paolo
2005
Abstract
In this paper, the Cramér-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 Cramér-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 investigatedFile in questo prodotto:
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