Share This Article:

A Low Sample Size Estimator for K Distributed Noise

Full-Text HTML Download Download as PDF (Size:3155KB) PP. 293-307
DOI: 10.4236/jsip.2012.33039    3,409 Downloads   4,943 Views  

ABSTRACT

In this paper, we derive a new method for estimating the parameters of the K-distribution when a limited number of samples are available. The method is based on an approximation of the Bessel function of the second kind that reduces the complexity of the estimation formulas in comparison to those used by the maximum likelihood algorithm. The proposed method has better performance in comparison with existing methods of the same complexity giving a lower mean squared error when the number of samples used for the estimation is relatively low.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

E. Alban, M. Magaña and H. Skinner, "A Low Sample Size Estimator for K Distributed Noise," Journal of Signal and Information Processing, Vol. 3 No. 3, 2012, pp. 293-307. doi: 10.4236/jsip.2012.33039.

References

[1] M. K. Prior, “Estimation of K-Distribution Shape Parameter from Sonar Data: Sample Size limitations,” IEEE Journal of Oceanic Engineering, Vol. 34, No. 1, 2009, pp. 45-50. Hdoi:10.1109/JOE.2008.2008040
[2] C. J. Baker, “K-Distributed Coherent Sea Clutter,” IEEE Proceedings F Radar and Signal Processing, Vol. 138, No. 2, 1991, pp. 89-92. Hdoi:10.1049/ip-f-2.1991.0014
[3] E. Jakeman and P. Pusey, “A Model for Non-Rayleigh Sea Echo,” IEEE Transactions on Antennas and Propagation, Vol. 24, No. 6, 1976, pp. 806-814. Hdoi:10.1109/TAP.1976.1141451
[4] C. J. Oliver, “Optimum Texture Estimators for SAR Clutter,” Journal of Physics D: Applied Physics, Vol. 26, No. 11, 1993, p. 1824. http://stacks.iop.org/0022-3727/26/i=11/a=002=0pt
[5] D. A. Abraham and A. P. Lyons, “Novel Physical Interpretations of K-Distributed Reverberation,” IEEE Journal of Oceanic Engineering, Vol. 27, No. 4, 2002, pp. 800-813. Hdoi:10.1109/JOE.2002.804324
[6] S. Kay, “Representation and Generation of Non-Gaussian Wide-Sense Stationary Random Processes with Arbitrary PSDs and a Class of PDFs,” IEEE Transactions on Signal Processing, Vol. 58, No. 7, 2010, pp. 3448-3458. Hdoi:10.1109/TSP.2010.2046437
[7] D. R. Iskander, A. M. Zoubir and B. Boashash, “A Method for Estimating the Parameters of the K Distribution,” IEEE Transactions on Signal Processing, Vol. 47, No. 4, 1999, pp. 1147-1151. Hdoi:10.1109/78.752614
[8] M. Jahangir, D. Blacknell and R. G. White, “Accurate Approximation to the Optimum Parameter Estimate for K-Distributed Clutter,” IEEE Proceedings—Radar, Sonar and Navigation, Vol. 143, No. 6, 1996, pp. 383-390. Hdoi:10.1049/ip-rsn:19960842
[9] D. Blacknell and R. J. A. Tough, “Parameter Estimation for the K-Distribution Based on [z log(z)],” IEEE Proceedings—Radar, Sonar and Navigation, Vol. 148, No. 6, 2001, pp. 309-312. Hdoi:10.1049/ip-rsn:20010720
[10] R. S. Raghavan, “A Method for Estimating Parameters of K-Distributed Clutter,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 27, No. 2, 1991, pp. 238-246. Hdoi:10.1109/7.78298
[11] D. A. Abraham and A. P. Lyons, “Bootstrapped K-Distribution Parameter Estimation,” OCEANS 2006, Boston, 18-21 September 2006, pp. 1-6. Hdoi:10.1109/OCEANS.2006.306983
[12] D. A. Abraham and A. P. Lyons, “Reliable Methods for Estimating the K-Distribution Shape Parameter,” IEEE Journal of Oceanic Engineering, Vol. 35, No. 2, 2010, pp. 288-302. Hdoi:10.1109/JOE.2009.2025645
[13] D. P. Hruska and M. L. Oelze, “Improved Parameter Estimates Based on the Homodyned K Distribution,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 56, No. 11, 2009, pp. 2471-2481. Hdoi:10.1109/TUFFC.2009.1334
[14] D. R. Iskander and A. M. Zoubir, “Estimating the Parameters of the K-Distribution Using the ML/MOM Approach,” Proceedings of 1996 IEEE TENCON. Digital Signal Processing Applications, Perth, 26-29 November 1996, pp. 769-774.
[15] W. J. J. Roberts and S. Furui, “Maximum Likelihood Estimation of K-Distribution Parameters via the Expectation-Maximization Algorithm,” IEEE Transactions on Signal Processing, Vol. 48, No. 12, 2000, pp. 3303-3306. Hdoi:10.1109/78.886993
[16] P.-J. Chung, W. J. J. Roberts and J. F. Bohme, “Recursive K-Distribution Parameter Estimation,” IEEE Transactions on Signal Processing, Vol. 53, No. 2, 2005, pp. 397- 402. Hdoi:10.1109/TSP.2004.840811
[17] I. R. Joughin, D. B. Percival and D. P. Winebrenner, “Maximum Likelihood Estimation of K Distribution Parameters for SAR Data,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 31, No. 5, 1993, pp. 989-999. Hdoi:10.1109/36.263769
[18] A. Mezache and F. Soltani, “A New Approach for Estimating the Parameters of the K-Distribution Using Fuzzy- Neural Networks,” IEEE Transactions on Signal Processing, Vol. 56, No. 11, 2008, pp. 5724-5728. Hdoi:10.1109/TSP.2008.929653
[19] D. R. Iskander and A. M. Zoubir, “Estimation of the Parameters of the K-Distribution Using Higher Order and Fractional Moments [Radar Clutter],” IEEE Transactions on Aerospace and Electronic Systems, Vol. 35, No. 4, 1999, pp. 1453-1457. Hdoi:10.1109/7.805463
[20] M. P. Wachowiak, R. Smolikova, J. M. Zurada and A. S. Elmaghraby, “Estimation of K Distribution Parameters Using Neural Networks,” IEEE Transactions on Biomedical Engineering, Vol. 49, No. 6, 2002, pp. 617-620. Hdoi:10.1109/TBME.2002.1001977
[21] S. Kay and C. Xu, “CRLB via the Characteristic Function with Application to the K-Distribution,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 44, No. 3, 2008, pp. 1161-1168. Hdoi:10.1109/TAES.2008.4655371
[22] M. Abramowitz and I. A. Stegun, “Handbook of Mathematical Functions: With Formulas, Graphs, and Mathematical Tables,” In: M. Abramowitz and I. A. Stegun, Eds., Dover Books on Advanced Mathematics, Dover Publications, New York, 1965.
[23] S.-C. Zhang and J.-M. Jin, “Computation of Special Func- tions,” Wiley, New York, 1996. http://books.google.com/books?id=ASfvAAAAMAAJ =0pt

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.