Modified Bayesian Cramér-Rao lower bound for nonlinear tracking

Onur Ozdemir, Ruixin Niu, Pramod Kumar Varshney, Andrew L. Drozd

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

5 Scopus citations

Abstract

We propose a modified Bayesian Cramér-Rao lower bound (BCRLB) for nonlinear tracking applications where the prediction distribution conditioned on past measurements is used as the prior. The novelty of the proposed modified BCRLB comes from the fact that it utilizes past measurements, therefore it is specific to the current realization of the track which makes it a useful online tool that can be used for real-time sensor management. The computation of our proposed modified BCRLB is not analytically tractable except under very restricted conditions. Therefore, we also develop a particle based numerical computation method for our modified BCRLB so that this new bound can be easily calculated in real-time using the particles already available from the underlying particle filter which is used to track the target. We show by simulations that our developed numerical computation method approaches to its true analytical value as the number of particles in the particle filter increases.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages3972-3975
Number of pages4
DOIs
StatePublished - 2011
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
Duration: May 22 2011May 27 2011

Other

Other36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
CountryCzech Republic
CityPrague
Period5/22/115/27/11

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Keywords

  • Bayesian Cramér-Rao lower bound
  • nonlinear tracking
  • sensor management

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

Cite this

Ozdemir, O., Niu, R., Varshney, P. K., & Drozd, A. L. (2011). Modified Bayesian Cramér-Rao lower bound for nonlinear tracking. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 3972-3975). [5947222] https://doi.org/10.1109/ICASSP.2011.5947222