Notification:
We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

Fast Consistent Chernoff Fusion of Gaussian Mixtures for Ad Hoc Sensor Networks

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

2 Author(s)
Ahmed, N.R. ; Autonomous Syst. Lab., Cornell Univ., Ithaca, NY, USA ; Campbell, M.

This correspondence examines the Chernoff rule for robust decentralized fusion of non-Gaussian pdfs in dynamic ad hoc sensor networks. Although theoretically appealing, the Chernoff rule is challenging to implement since it leads to fusion pdfs that cannot be obtained in closed-form and requires analytically intractable optimizations. Existing heuristic approximations to the Chernoff rule are generally inconsistent and do not accurately represent the fusion pdf. A fast new procedure based on Monte Carlo importance sampling, convex optimization and weighted expectation maximization is presented here to overcome these drawbacks and enable accurate online Chernoff fusion for ad hoc distributed sensor networks with Gaussian mixtures. Numerical experiments demonstrate the superiority of the proposed procedure.

Published in:

Signal Processing, IEEE Transactions on  (Volume:60 ,  Issue: 12 )