An online self-calibration method of single-axis laser gyro strapdown inertial navigation system for shipboard radar

Abstract

The error coefficients calibration of inertial measurement units (IMUs) is an essential step for strapdown inertial navigation systems (SINSs), and the system-level calibration is the most prevalent method. To satisfy the need for high-precision attitude measurement in large-scale shipboard radar, single axis laser gyro SINSs can be directly fitted on radar and spins with it, feeding back attitude information in real time to determine the radar’s direction. The radar's pitch and roll axes can only rotate from -45° to +45°, however the radar heading axis may revolve at any angle by rotating the radar base. For single axis laser gyros SINS with rotation angle constraints, this paper proposes an on-line self-calibration solution. The error model of IMU is established in the study, and the 33-dimensional Kalman filter is applied to estimate the error parameters including the bias, scale factor errors, installation errors, inner-arm errors and quadratic errors. In order to solve the online self-calibration problem of IMU with limited rotation angle, we proposed a 17-step rotation scheme based on the errors transmission characteristics to excite and separate the parameters. The feasibility of calibration scheme is demonstrated by simulation, and results show that this online-calibration method can accurately calibrate the remaining 24 error parameters, except for the accelerometer’s z-axis bias, z-axis scale factor, and z-axis quadratic error. We conducted another simulation without considering the accelerometer’s z-axis quadratic error. Results show that all the calibration results of error parameters can meet the accuracy requirements by using the 17-step rotation scheme.