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.
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Yulong Huang
Yulong Huang received his BS degree from the Department of Automation, Harbin Engineering University, Harbin, China, in 2012, and is currently working towards a PhD degree in control science and engineering. His current research interests include state estimation, system identification and information fusion.
Yonggang Zhang
Yonggang Zhang received his BS and MS degrees from the Department of Automation, Harbin Engineering University, Harbin, China, in 2002 and 2004, respectively. He received his PhD degree in Electronic Engineering from Cardiff University, UK in 2007 and worked as a post-doctoral fellow at Loughborough University, UK from 2007 to 2008 in the area of adaptive signal processing. Currently, he is a professor of navigation, guidance, and control in Harbin Engineering University (HEU) in China. His current research interests include signal processing, information fusion and their applications in navigation technology, such as fiber optical gyroscope, inertial navigation and integrated navigation.