Abstract
This paper introduces a new nonlinear filter for a discrete time, linear system which is observed in additive non-Gaussian measurement noise. The new filter is recursive, computationally efficient and has significantly improved performance over other linear and nonlinear schemes. The problem of narrowband interference suppression in additive noise is considered as an important example of non-Gaussian noise filtering. It is shown that the new filter outperforms currently used approaches and at the same time offers simplicity in the design.
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References
Candy, J. V.: Signal Processing: The Model-Based Approach, McGraw-Hill, New York, 1986.
Pitas, I. and Venetsanopoulos, A. N.: Nonlinear Digital Filters: Principles and Applications, Kluwer Academic Publishers, Norwell, MA, 1990.
Huber, P. J.: Robust estimation of a location parameter, Ann. Math. Statist. 35(1964), 73–101.
Middleton, D.:Man-made noise in urban environments and transportation systems, IEEE Trans. on Communications COM-21(1973), 1232–1241.
Middleton, D.: Canonical non-Gaussian noise models: Their implication for measurement and for prediction of receiver performance, IEEE Trans. Electromagn. Compat. EMC-21(1979), 209–219.
Achieser, N. I.: Theory of Approximation, translated by C. T. Hyman, Frederic Ungar, New York, 1956.
Namera, T. and Stubberud, A. L.: Gaussian sum approximation for nonlinear fixed-point prediction, Internat. J. Control 38(5) (1983), 1047–1053.
Vastola, K. S.: Threshold detection in narrowband non-Gaussian noise, IEEE Trans. on Communications COM-32(1984), 134–139.
Garth, L. M. and Poor, H. V.: Narrowband interference suppression in impulsive channels, IEEE Trans. on Aerospace and Electronic Systems AES-28(1992), 15–35.
Sorenson, H. and Alspach, D. L.: Recursive Bayesian estimation using Gaussian sum, Automatica 7(1971), 465–479.
Alspach, D. L. and Sorenson, H.: Nonlinear Bayesian estimation using Gaussian sum approximations, IEEE Trans. on Automatic Control AC-17(4) (1972), 439–448.
Masreliez, C. J.: Approximate non-Gaussian filtering with linear state and observation relations, IEEE Trans. on Automatic Control AC-20(1975), 107–110.
Masreliez, C. J. and Martin, R. D.: Robust Bayesian estimation for the linear model and robustifying the Kalman filter, IEEE Trans. on Automatic Control AC-22(1977), 361–371.
Wu, Weng-Rong and Yu, F. F.: New nonlinear algorithms for estimating and suppressing narrowband interference in DS spread spectrum systems, IEEE Trans. on Communications 44(4) (1996), 508–515.
Fukunaga, K.: Introduction to Statistical Pattern Recognition, Second Edition, Academic Press, London, 1990.
Vijayan, R. and Poor, H. V.: Nonlinear techniques for interference suppression in spreadspectrum systems, IEEE Trans. on Communications COM-38(1990), 1060–1065.
Plataniotis, K. N.: Distributed parallel processing state estimation algorithms, PhD Dissertation, Florida Institute of Technology, Melbourne, Florida, 1994.
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Plataniotis, K.N., Androutsos, D. & Venetsanopoulos, A.N. Nonlinear Filtering of Non-Gaussian Noise. Journal of Intelligent and Robotic Systems 19, 207–231 (1997). https://doi.org/10.1023/A:1007974400149
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DOI: https://doi.org/10.1023/A:1007974400149