Constructions of particular random processes

This paper reviews how to construct sets of random numbers with particular amplitude distributions and correlations among values. These constructions support both high-fidelity Monte Carlo simulation and analytic design studies. A variety of constructions is presented to free engineering models from "white or normal" limitations embodied in many current simulations. The methods support constructions of conventional stationary and normally distributed processes, nonstationary, nonnormal signal and interference waveforms, nonhomogeneous random scenes, nonhomogeneous volumetric clutter realizations, and snapshots of randomly evolving, nonhomogeneous scenes. Each case will have specified amplitude statistics, e.g., normal, log-normal, uniform, Weibull, or discrete amplitude statistics; and selected correlation, e.g., white, pink, or patchy statistics, clouds. or speckles. Sets of random numbers with correlation, nonstationarities, various tails for the amplitude distributions, and multimodal distributions can be constructed. The paper emphasizes aspects of probability theory necessary to engineering modeling. >

[1]  B. Melamed,et al.  The transition and autocorrelation structure of tes processes , 1992 .

[2]  Julius T. Tou,et al.  Pattern Recognition Principles , 1974 .

[3]  Peter F. Swaszek,et al.  Locally optimal detection in multivariate non-Gaussian noise , 1984, IEEE Trans. Inf. Theory.

[4]  G. Jona-Lasinio Probabilistic Approach to Critical Behavior , 1977 .

[5]  P. Lewis,et al.  A new Laplace second-order autoregressive time-series model - NLAR(2) , 1985, IEEE Trans. Inf. Theory.

[6]  W. Szajnowski The Generation of Correlated Weibull Clutter for Signal Detection Problems , 1977, IEEE Transactions on Aerospace and Electronic Systems.

[7]  L. Isserlis ON A FORMULA FOR THE PRODUCT-MOMENT COEFFICIENT OF ANY ORDER OF A NORMAL FREQUENCY DISTRIBUTION IN ANY NUMBER OF VARIABLES , 1918 .

[8]  T. Kailath The innovations approach to detection and estimation theory , 1970 .

[9]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[10]  D. Middleton An Introduction to Statistical Communication Theory , 1960 .

[11]  B. Melamed,et al.  The transition and autocorrelation structure of tes processes: Part II: Special Cases , 1992 .

[12]  J. Shohat,et al.  The problem of moments , 1943 .

[13]  K. Symanzik Euclidean Quantum field theory , 1969 .

[14]  J.M. Geist Computer generation of correlated Gaussian random variables , 1979, Proceedings of the IEEE.

[15]  William A. Gardner,et al.  Characterization of cyclostationary random signal processes , 1975, IEEE Trans. Inf. Theory.

[16]  William H. Press,et al.  Numerical recipes , 1990 .

[17]  Paul Bratley,et al.  A guide to simulation , 1983 .

[18]  Ronald W. Schafer,et al.  A fast method of generating digital random numbers , 1970, Bell Syst. Tech. J..

[19]  Bruce W. Schmeiser Random Process Generation. , 1980 .

[20]  Bede Liu,et al.  Generation of a random sequence having a jointly specified marginal distribution and autocovariance , 1982 .

[21]  Donald Ervin Knuth,et al.  The Art of Computer Programming , 1968 .

[22]  David Middleton Canonically optimum threshold detection , 1966, IEEE Trans. Inf. Theory.

[23]  G. Picci Stochastic realization of Gaussian processes , 1976, Proceedings of the IEEE.

[24]  W. Rudin Real and complex analysis , 1968 .

[25]  Reuven Y. Rubinstein,et al.  Simulation and the Monte Carlo method , 1981, Wiley series in probability and mathematical statistics.

[26]  George M. Dillard Generating random numbers having probability distributions occurring in signal detection problems (Corresp.) , 1967, IEEE Trans. Inf. Theory.

[27]  Andreas M. Maras,et al.  Locally optimum detection in moving average non-Gaussian noise , 1988, IEEE Trans. Commun..

[28]  Joseph L. Hammond,et al.  Generation of Pseudorandom Numbers with Specified Univariate Distributions and Correlation Coefficients , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[29]  R. A. Fox,et al.  Introduction to Mathematical Statistics , 1947 .

[30]  Michel Loève,et al.  Probability Theory I , 1977 .

[31]  G. C. Wick The Evaluation of the Collision Matrix , 1950 .