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Distributed diffusion multiple model state estimation based on inverse covariance intersection with guaranteed
Tao Cui1, Peng Dong1, Zhongliang Jing1
1Shanghai Jiao Tong University, Shanghai, China.
Abstract:
This paper presents a diffusion interacting multiple model (IMM) filter based on inverse covariance intersection (ICI) for linear jump Markov systems. We begin by presenting the calculation rule for the ICI fusion weights and provide an analysis showing that, under the given weights, the covariance obtained through ICI fusion is no greater than that obtained through covariance intersection (CI) fusion in the context of multiple estimate fusion. Building on this, the fusion rules in the classical IMM and the diffusion update step are replaced by ICI fusion. We then analyze the boundedness of the error covariance and the exponential stability of the estimation error. Simulations show that the proposed algorithm achieves good performance.
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