Abstract
The paper investigates the relation between the sample number and the perormances of signal detection and parameter estimation in color Gaussian noise in fixed timeT. It points out that if the autocorrelation coefficient between the neighbour samples is in the range of 0.1–0.2 the GSNRS 2[T(XL)] will approach to the GSNR limitS 2(T). The paper also points out that the sample sequence of the solution of a second-order differential equation is not an AR(2) model. But when the sample interval Δ approaches zero, the sample sequence can be described by AR(2). Therefore we can calculateS 2(T) easily. At the end of the paper, the relation between the likelihood ratio detection and the maximum likelihood estimation is discussed.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
H.L. Van Trees, Detection, Estimation and Modulation Theory, Part I, New York: Wiley, 1968.
A.D. Whalen, Detectio of Signals in Noise, New York: Aoademic Press, 1971.
W.D. Wood, J.B. Thomas,Information Sciences 20(1981), 13–33.
S. Cambanis, E. Masry, IEEE on IT,IT-29(1983), 83–104.
A. Papoulis, Probability, Random Variables and Stochastic Processes, New York: McGraw-Hill Inc., 1965, pp. 528–537
A. Gelb, Applied Optimal Estimation, The M.I.T. Press, 1974, pp. 43–45.
I.S. Meditch, Stochastic Optimal Linear Estimation and Control, 1969.
Author information
Authors and Affiliations
About this article
Cite this article
Yu, L. The performance analysis of discrete-time detection and estimation in color gaussian noise. J. of Electron.(China) 5, 87–95 (1988). https://doi.org/10.1007/BF02778813
Issue Date:
DOI: https://doi.org/10.1007/BF02778813