By Topic

Timing estimation for a filtered Poisson process in Gaussian noise

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Hero, A.O. ; Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA

The problem of estimation of time shift of an inhomogeneous casually filtered Poisson process in the presence of additive Gaussian noise is discussed. Approximate expressions for the likelihood function, the MAP estimator, and the MMSE estimator that becomes increasingly accurate as the per-unit-time density of superimposed filter responses becomes small are obtained. The optimal MAP estimator takes the form of a cascade of linear and memoryless nonlinear components. For smooth point process intensities, the performance of the MAP estimator is studied via local bias and local variance. A rate distortion type lower bound on the MSE of any estimator of time delay is then derived by identification of a communications channel that accounts for the mapping from time delay to observation process. Results of numerical studies of estimator performance are presented. Based on the examples considered it is concluded: (1) the small-error MSE of the nonlinear MAP estimator can be significantly better than the small-error MSE of the optimal linear estimator: (2) the rate distortion lower bound can be significantly tighter than the Poisson limited bounds determined in previous studies

Published in:

Information Theory, IEEE Transactions on  (Volume:37 ,  Issue: 1 )