A Federated Filter Based on Innovation Filtering Interacting Multiple Model Filter for Multi-sensor Navigation System

Lei Wang (), Xianghong Cheng () and Yixian Zhu ()
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Lei Wang: Southeast University
Xianghong Cheng: Southeast University
Yixian Zhu: Southeast University

A chapter in LISS 2014, 2015, pp 1703-1709 from Springer

Abstract: Abstract A federated filter based on innovation filtering interacting multiple model (IFIMM) is developed in this paper. The proposed algorithm combines the innovation filtering interacting multiple model filtering and federated algorithm. The former implements dynamic interaction and dynamic changing of multiple modes based on the Markov chain process of the system models. Compare to the traditional interacting multiple model (IMM) algorithm, it decreases the sensitivity of probabilistic weightings to measurement noise. Experiment results show that the proposed federated IFIMM filter has significant improvement in navigation estimation accuracy and reliability as compared to the federated Kalman filter and federated IMM filter approaches.

Keywords: Interacting multiple model; Innovation filtering; Integrated navigation system; INS/GPS/Odometer (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-662-43871-8_245

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DOI: 10.1007/978-3-662-43871-8_245

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