Title :
Channel and intensity estimation for a class of point processes
Author :
Swami, Ananthram ; Sadler, Brian
Author_Institution :
AMSRL-IS-TA, Army Res. Lab., Adelphi, MD, USA
Abstract :
We show that the blind linear time invariant (LTI) channel estimation problem, when the input sequence is independent, but has time-varying statistics, mimics that for the i.i.d. case under appropriate persistence of excitation conditions. Hence, consistent parametric and non-parametric estimators based on a single realization are readily obtained. We establish an ergodicity theorem for the time-averages of non-stationary continuous time processes; we use this to establish blind identifiability of the LTI channel of a filtered inhomogeneous point process, with multiplicative marks. These results extend to a class of time-varying channels as well. The theoretical results are corroborated by simulations
Keywords :
continuous time systems; filtering theory; nonparametric statistics; parameter estimation; sequences; stochastic processes; time-varying channels; blind identifiability; blind linear time invariant channel; channel estimation; ergodicity theorem; excitation conditions; filtered inhomogeneous point process; i.i.d. case; independent identically distributed process; input sequence; intensity estimation; multiplicative marks; nonparametric estimators; nonstationary continuous time processes; parametric estimators; point processes; realization; time-averages; time-varying channels; time-varying statistics; Channel estimation; Milling machines; Phase estimation; Powders; Reflectivity; Statistics; Sufficient conditions; Time varying systems; Time-varying channels; Yield estimation;
Conference_Titel :
Statistical Signal and Array Processing, 1996. Proceedings., 8th IEEE Signal Processing Workshop on (Cat. No.96TB10004
Conference_Location :
Corfu
Print_ISBN :
0-8186-7576-4
DOI :
10.1109/SSAP.1996.534910