Abstract: An ARAIM subset selection method based on a BeiDou constellation includes: (a) deeming a current airspace as a two-dimensional plane and satellite distribution at some point as point distribution on the two-dimensional plane; (b) selecting coordinates of K satellites as original centroids, assigning each satellite to the closest original centroid by means of a K-Means algorithm to form K classification clusters, and recalculating a centroid of each classification cluster to obtain a centroid coordinate; (c) re-selecting the coordinates of the K satellites as the original centroids, repeating the calculation step (b) to calculate the sum of squared errors of the centroid obtained every time, and selecting the centroid with a minimum sum of squared errors as an output result; and (d) performing outlier detection on the output result of the step (c), and if an outlier appears, not performing fault assumption on a satellite at the outlier.

Abstract: The invention relates to a quick calibration method for an inertial measurement unit (IMU). According to the method, a user holds and rotates the IMU to move in all directions without any external equipment, so that twelve error coefficients including gyro biases, gyro scale factors, accelerometer biases and accelerometer scale factors can be accurately calibrated in a short time. The quick calibration method for the IMU is characterized by being free of hardware cost, high in efficiency and simple and easy to implement, and can ensure certain calibration precision. Thus, the quick calibration method is especially suitable for in-situ quick calibration for the medium- and low-grade IMUs, thereby effectively solving the problem of environmental sensitivity of the error coefficients of the mechanical IMU, and promoting popularization and application of MEMS (micro-electro mechanical systems) inertial devices.