– The federated filter created by Carlson has been widely used in multi-sensor integrated navigation. Compared with no-reset federated filter, the reset mode has greater sub-filters’ performance, but faults of any subsystem would affect other healthy subsystems via global fusion and the sub-optimality of sub-filters’ estimation has influence on fault detection sensitivity. It’s a challenge to design a robust reset federated filter.

    Design/methodology/approach

    – The time-varying observation noise is designed to reduce proportions of observation information in faulty sub-filters. A new dynamic information distribution algorithm based on optimal residual chi-square detection function is presented to reduce proportions of faulty sub-filters’ estimation in information fusion filter.

    Findings

    – The robust filtering algorithm represents a filtering strategy for reset federated filter. Compared with fault isolation, the navigation result is smoother by using this algorithm. It has significant benefits in avoiding faulty sensors’ contamination and the performance of federated filter is greatly improved.

    Research limitations/implications

    – The approach described in this paper provides a new method to deal with federated reset filter’s faulty problems. This new robust federated filter algorithm possesses a great potential for various applications.

    Practical implications

    – The approach described in this paper can be used in multi-sensor integrated navigation with no fewer than three sensors.

    Originality/value

    – Compared with conventional approach of fault isolation, the proposed algorithm does not destroy the continuity and integrity of the filtering process. It improves the performance of the federated filter by reducing proportions of faulty observation information. It also reduces the influence of sub-optimality on fault detection sensitivity.


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    Title :

    Robust filtering algorithm based on time-varying noise


    Contributors:
    Shao, Hui (author) / Xiong, Zhi (author) / Xu, Jianxin (author) / Hua, Bing (author) / Han, Song (author)


    Publication date :

    2016-01-04


    Size :

    8 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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