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Robust in‐field estimation and calibration approach for strapdown inertial navigation systems accelerometers bias acting on the vertical channel

This paper investigates an effective approach to estimate vertical channel accelerometer bias in strapdown inertial navigation system. At first, a novel inertial frame based mechanisation algorithm for strapdown inertial navigation system is introduced and its equations are derived. The difference between the outputs of the proposed mechanisation and a special type of the local-level frame mechanisation is considered as an error signal. Through this approach, the vertical accelerometer bias estimation procedure is converted to a control problem. By designing an appropriate optimal controller, the error signal is minimised and the vertical accelerometer bias is accurately estimated. The proposed approach attains a more robust and accurate estimation of the vertical accelerometer bias compared to the conventional Kalman filter based self-alignment and calibration method. Two different scenarios are conducted to assess the effectiveness of the proposed approach. In the first scenario, the IMU is stationary with respect to the Earth and the second scenario evaluates the condition where IMU experiences undesirable dynamic motions. The experimental test results illustrate that unlike the conventional Kalman filter based self-alignment and calibration method, the proposed approach obtains a robust estimation in the presence of undesirable dynamic motion as well as the static condition.