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

Yulong Huang and Yonggang Zhang

International Journal of Systems Science, 2016, vol. 47, issue 13, 3206-3218

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.

Date: 2016
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DOI: 10.1080/00207721.2015.1110639

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