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

In: Liss 2014

Author

Listed:
  • Lei Wang

    (Southeast University
    Southeast University)

  • Xianghong Cheng

    (Southeast University
    Southeast University)

  • Yixian Zhu

    (Southeast University
    Southeast University)

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.

Suggested Citation

  • Lei Wang & Xianghong Cheng & Yixian Zhu, 2015. "A Federated Filter Based on Innovation Filtering Interacting Multiple Model Filter for Multi-sensor Navigation System," Springer Books, in: Zhenji Zhang & Zuojun Max Shen & Juliang Zhang & Runtong Zhang (ed.), Liss 2014, edition 127, pages 1703-1709, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-43871-8_245
    DOI: 10.1007/978-3-662-43871-8_245
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