To enhance the navigation precision of strapdown inertial navigation system, it is necessary to carry out a high accuracy calibration for the inertial measurement unit (IMU). In this paper, a novel network calibration method is proposed to satisfy the calibration for a number of IMUs, which is depending on multiple maneuvers of the test platform where IMUs are installed. With the specific maneuvers of the test platform, the uncalibrated parameters of gyros and accelerometers models can be excited. In order to obtain the optimal estimation of these parameters, the dual-loop filter algorithm based on Kalman filter is presented for the information fusion by tracking the velocity and position errors from the IMUs nearby. The simulation result shows that the parameters of gyros and accelerometers models can be well estimated in a short time. Comparing with the existing calibration methods, the proposed method has the following advantages: (1) it does not require special equipment such as a turntable to provide the angular rate and multi-position tests, (2) it is time efficient when compared with other time consuming methods, (3) it can calibrate a lot of IMUs simultaneously, but not one by one. Thus with the above advantages, the proposed calibration method will have a wide application prospect for the in-field calibration.


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    Title :

    A novel network calibration method for inertial measurement units


    Contributors:
    Xu, Yun (author) / Zhu, Xinhua (author) / Su, Yan (author)


    Publication date :

    2015-06-01


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English