State Estimation for Linear Scalar Dynamic Systems with Additive Cauchy Noises: Characteristic Function Approach

Uncertainties in many practical systems, such as radar glint and sonar noise, have impulsive character and are better described by heavy-tailed non-Gaussian densities, for example, the Cauchy probability density function (pdf). The Cauchy pdf does not have a well defined mean and its second moment is infinite. Nonetheless, the conditional density of a Cauchy random variable, given a scalar linear measurement with an additive Cauchy noise, has a conditional mean and a finite conditional variance. In particular, for scalar discrete linear systems with additive process and measurement noises described by Cauchy pdfs, the unnormalized characteristic function of the conditional pdf is considered. It is expressed as a growing sum of terms that at each measurement update increases by one term, constructed from four new measurement-dependant parameters. The dynamics of these parameters is linear. These parameters are shown to decay, allowing an approximate finite dimensional recursion. From the first two differen...

[1]  Gonzalo R. Arce,et al.  Nonlinear Signal Processing - A Statistical Approach , 2004 .

[2]  N. L. Johnson,et al.  Continuous Univariate Distributions. , 1995 .

[3]  C. L. Nikias,et al.  Deviation from normality in statistical signal processing: parameter estimation with alpha-stable distributions , 1998 .

[4]  W. Linde STABLE NON‐GAUSSIAN RANDOM PROCESSES: STOCHASTIC MODELS WITH INFINITE VARIANCE , 1996 .

[5]  J. Meditch,et al.  Applied optimal control , 1972, IEEE Transactions on Automatic Control.

[6]  Paul Zarchan,et al.  Tactical and strategic missile guidance , 1990 .

[7]  Moshe Idan,et al.  Cauchy Estimation for Linear Scalar Systems , 2008, IEEE Transactions on Automatic Control.

[8]  G. Hewer,et al.  Robust Preprocessing for Kalman Filtering of Glint Noise , 1987, IEEE Transactions on Aerospace and Electronic Systems.

[9]  D. Kammler A First Course in Fourier Analysis , 2000 .

[10]  Peter J. W. Rayner,et al.  Near optimal detection of signals in impulsive noise modeled with a symmetric /spl alpha/-stable distribution , 1998, IEEE Communications Letters.

[11]  R. Martin,et al.  Robust bayesian estimation for the linear model and robustifying the Kalman filter , 1977 .

[12]  John P Nolan,et al.  Stable filters: A robust signal processing framework for heavy-tailed noise , 2010, 2010 IEEE Radar Conference.

[13]  Paul M Reeves A NON-GAUSSIAN TURBULENCE SIMULATION , 1969 .

[14]  George A. Tsihrintzis,et al.  Statistical modeling and receiver design for multi-user communication networks , 1998 .