• DocumentCode
    1736910
  • Title

    Improved determination of the best fitting sine wave in ADC testing

  • Author

    Kollár, István ; Blair, Jerome J.

  • Author_Institution
    Dept. of Meas. & Inf. Syst., Budapest Univ. of Technol. & Econ., Hungary
  • Volume
    2
  • fYear
    2004
  • Firstpage
    829
  • Abstract
    The sine wave test of an ADC means to excite the ADC with a pure sine wave, look for the sine wave is which best fits the output in least squares sense, and analyze the difference. This is described in the IEEE standards 1241-2000 and 1057-1994. Least squares is the ´best´ fitting method most of us can imagine. and it yields very good results indeed. Its known properties are achieved when the error (the deviation of the samples from the true sine wave) is random, white (the error samples are all independent), with zero mean Gaussian distribution. Then the LS fit coincides with the maximum likelihood estimate of the parameters. However, in sine wave testing of ADCs these assumptions are far from being true. The quantization error is partly deterministic, and the sample values are strongly interdependent. This makes the sine fit worse than expected, and since small changes in the sine wave affect the residuals significantly, especially close to the peaks, ADC error analysis may become misleading. Processing of the residuals (e.g. the calculation of the effective number of bits, ENOB) can exhibit serious errors. This paper describes this phenomenon, analyses its consequences, and suggests modified processing of samples and residuals to reduce the errors to negligible level.
  • Keywords
    IEEE standards; analogue-digital conversion; curve fitting; integrated circuit testing; least squares approximations; maximum likelihood estimation; quantisation (signal); signal sampling; waveform analysis; ADC error analysis; ADC testing; IEEE standard 1057-1994; IEEE standard 1241-2000; best fitting sine wave; effective number of bits; least squares method; maximum likelihood estimate; modified processing; quantization error; zero mean Gaussian distribution; Error analysis; Frequency; Gaussian processes; Information systems; Least squares methods; Parameter estimation; Performance analysis; Read only memory; System testing; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference, 2004. IMTC 04. Proceedings of the 21st IEEE
  • ISSN
    1091-5281
  • Print_ISBN
    0-7803-8248-X
  • Type

    conf

  • DOI
    10.1109/IMTC.2004.1351190
  • Filename
    1351190