Control of sensing by navigation on information gradients

Sofia Suvorova, Bill Moran, Stephen D. Howard, Douglas Cochran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In estimation of parameters residing in a smooth manifold from sensor data, the Fisher information induces a Riemannian metric on the parameter manifold. If the collection of sensors is reconfigured, this metric changes. In this way, sensor configurations are identified with Riemannian metrics on the parameter manifold. The collection of all Riemannian metrics on a manifold forms a (weak) Riemannian manifold, and a smooth trajectory of sensor configurations manifests as a smooth curve in this space. This paper develops the idea of sensor management by following trajectories in the space of sensor configurations that are defined locally by gradients of the metric this space inherits from the abstract space of all Riemannian metrics on the parameter manifold. Theory is developed and computational examples that illustrate sensor configuration trajectories arising from this scheme are presented.

Original languageEnglish (US)
Title of host publication2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
Pages197-200
Number of pages4
DOIs
StatePublished - Dec 1 2013
Event2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Austin, TX, United States
Duration: Dec 3 2013Dec 5 2013

Publication series

Name2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings

Other

Other2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013
CountryUnited States
CityAustin, TX
Period12/3/1312/5/13

Keywords

  • Information geometry
  • Sensor management

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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    Suvorova, S., Moran, B., Howard, S. D., & Cochran, D. (2013). Control of sensing by navigation on information gradients. In 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings (pp. 197-200). [6736849] (2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings). https://doi.org/10.1109/GlobalSIP.2013.6736849