Papers
Topics
Authors
Recent
Search
2000 character limit reached

Correlation and Spectral Density Functions in Mode-Stirred Reverberation -- II. Spectral Moments, Sampling, Noise, EMI and Understirring

Published 4 Apr 2024 in physics.class-ph, cs.SD, and eess.AS | (2404.03520v1)

Abstract: In part I, spectral moments and kurtosis were established as parameters in analytic models of correlation and spectral density functions for dynamic reverberation fields. In this part II, several practical limitations affecting the accuracy of estimating these parameters from measured stir sweep data are investigated. For sampled fields, the contributions of finite differencing and aliasing are evaluated. Finite differencing results in a negative bias that depends, to leading order, quadratically on the product of the sampling time interval and the stir bandwidth. Numerical estimates of moments extracted directly from sampled stir sweeps show good agreement with values obtained by an autocovariance method. The effects of data decimation and noise-to-stir ratios of RMS amplitudes are determined and experimentally verified. In addition, the dependencies on the noise-to-stir-bandwidth ratio, EMI, and unstirred energy are characterized.

Authors (2)
Definition Search Book Streamline Icon: https://streamlinehq.com
References (21)
  1. L. R. Arnaut, “Correlation and spectral density functions in mode-stirred reverberation – I. Theory,” IEEE Trans. Electromagn. Compat., 2024, doi 10.1109/TEMC.2024.3355801.
  2. L. R. Arnaut and J. M. Ladbury, “Correlation and spectral density functions in mode-stirred reverberation – III. Measurements,” IEEE Trans. Electromagn. Compat., 2024, doi 10.1109/TEMC.2024.3371418.
  3. L. R. Arnaut, “Measurement uncertainty in reverberation chambers – I. Sample statistics,” NPL Rep., TQE 2, 2nd. ed., pp. 1–136, Dec. 2008.
  4. J. C. West, C. F. Bunting, and V. Rajamani, “Accurate and efficient numerical simulation of the random environment within an ideal reverberation chamber,” IEEE Trans. Electromagn. Compat., vol. 54, no. 1, pp. 167–173, Feb. 2012.
  5. D. E. Cartwright and M. S. Longuet–Higgins, “The statistical distribution of the maxima of a random function,” Proc. Roy. Soc. Lond., Ser. A, vol. 237, no. 1208, pp. 212–232, Oct. 1956.
  6. P. A. Bello, “Some techniques for the instantaneous real-time measurement of multipath and Doppler spread,” IEEE Trans. Comm. Techn., vol. 13, no. 3, pp. 285–292, Sep. 1965.
  7. E. H. Vanmarcke, “Properties of spectral moments with applications to random vibration,” J. Eng. Mech. Div., vol. 98, no. 2, pp. 425–446, Apr. 1972.
  8. K. S. Miller and M. M. Rochwarger, “On estimating spectral moments in the presence of colored noise,” IEEE Trans. Inf. Theo., vol. 16, no. 3, pp. 303–309, May 1970.
  9. K. S. Miller and M. M. Rochwarger, “A covariance approach to spectral moment estimation,” IEEE Trans. Inf. Theo., vol. 18, no. 5, pp. 588–596, Sep. 1972.
  10. D. S. Zrnić, “Spectral moment estimates from correlated pulse pairs,” IEEE Trans. Aerospace Electron. Syst., vol. 13, no. 4, pp. 344–354, Jul. 1977.
  11. D. S. Zrnić, “Estimation of spectral moments for weather echoes,” IEEE Trans. Geosci. Electron., vol. 17, no. 4, pp. 113–128, Oct. 1979.
  12. R. E. Passarelli (Jr.) and A. D. Siggia, “The autocorrelation function and Doppler spectral moments: geometric and asymptotic interpretations,” J. Clim. Appl. Meteo., vol. 22, pp. 1776–1787, Oct. 1983.
  13. A. A. Monakov and D. V. Blagoveshchensky, “A method of spectral moment estimation,” IEEE Trans. Geosci. Remote Sens., vol. 37, no. 2, pp. 805–810, Mar. 1999.
  14. V. M. Melnikov and D. S. Zrnić, “Estimates of large spectrum width from autocovariances,” J. Atm. Ocean. Techn., vol. 11, pp. 969–974, Jun. 2004.
  15. L. R. Arnaut, “Effect of local stir and spatial averaging on the measurement and testing in mode-tuned and mode-stirred reverberation chambers,” IEEE Trans. Electromagn. Compat., vol. 43, no. 3, pp. 305–325, Aug. 2001.
  16. L. R. Arnaut, “On the maximum rate of fluctuation in mode-stirred reverberation,” IEEE Trans. Electromagn. Compat., vol. 47, no. 4, pp. 781–804, Nov. 2005.
  17. Q. Xu, Y. Huang, L. Xing, and Z. Tian, “Extract the decay constant of a reverberation chamber without satisfying Nyquist criterion,” IEEE Microw. Wirel. Compon. Lett., vol. 26, no. 3, pp. 153-155, Mar. 2016.
  18. A. C. Marvin and S. Bale, “Thermal noise measurements in a reverberation chamber,” IEEE Trans. Electromagn. Compat., vol. 64, no. 3, pp. 893–896, Feb. 2022.
  19. L. R. Arnaut and J. M. Ladbury, “Interference and noise effects on spectral moments of mode-stirred reverberation fields,” presented at Proc. 4th URSI AT-RASC, Gran Canaria, Spain, 19–24 May 2024.
  20. D. Warde and S. M. Torres, “The autocorrelation spectral density for Doppler weather radar signal analysis,” IEEE Trans. Geosci. Remote Sens., vol. 52, no. 1, pp. 508–518, Jan. 2014.
  21. L. R. Arnaut, “Threshold level crossings, excursions, and extrema in immunity and fading testing using multistirred reverberation chambers,” IEEE Trans. Electromagn. Compat., vol. 62, no. 5, pp. 1638–1650, Oct. 2020.
Citations (2)
View on Semantic Scholar

Summary

No one has generated a summary of this paper yet.

Sign Up to Summarize

Paper to Video (Beta)

No one has generated a video about this paper yet.

Sign Up to Generate All Videos Subscribe on YouTube

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Sign Up to Generate

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Generate Now

Continue Learning

We haven't generated follow-up questions for this paper yet.

Generate Now

Collections

Sign up for free to add this paper to one or more collections.

Sign Up