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A new conditional posterior Cramér-Rao lower bound for a class of nonlinear systems

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  • Yulong Huang
  • Yonggang Zhang

Abstract

In this paper, a new conditional posterior Cramér-Rao lower bound (CPCRLB) is proposed for a class of nonlinear systems, in which current measurement is dependent on current state as well as one step previous state. In order to compute the proposed CPCRLB recursively, a new particle filter for such class of nonlinear systems is designed, based on which a general formulation of the proposed CPCRLB can be derived. To facilitate practical engineering applications, CPCRLBs for special cases of such class of nonlinear systems, including nonlinear systems with coloured measurement noises and nonlinear systems with correlated noises at one epoch apart, are developed, respectively. Simulation results show the efficiency and superiority of the proposed CPCRLB as compared with existing CPCRLB.

Suggested Citation

  • Yulong Huang & Yonggang Zhang, 2016. "A new conditional posterior Cramér-Rao lower bound for a class of nonlinear systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(13), pages 3206-3218, October.
    • Handle: RePEc:taf:tsysxx:v:47:y:2016:i:13:p:3206-3218
    DOI: 10.1080/00207721.2015.1110639
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