Using sine wave histograms to estimate analog-to-digital converter dynamicerror functions

This paper describes a new method for developing analog-to-digital converte r (ADC) error function models using modified sinewave histogram methods, Th e error models may be used to digitally compensate for nonlinearities intro duced by the converter, The histogram modification involves sorting of conv erter output samples based upon an estimated associated input derivative si gnal, This error model is based upon a previously unpublished result which shows that sinewave histograms yield distinctly different expected errors f or each state based upon input signal slope associated with each output sam ple, This result thus provides a dynamic dependence for expected errors mea sured by means of histogram methods. Sorted sinewave histograms are used to estimate slope dependent expected errors at each ADC output state (code), The method provides improved error representation by providing error basis functions for every output code, Simulated results prove that this method r emoves all slope dependent errors for complex ADC architectures while exper imental results for an 8-bit 200 MSPS ADC yielded more than 10 db improveme nt in spurious-free-dynamic-range (SFDR) over the full Nyquist band. The ne w method is thus shown to possess wideband dynamic error character.