An improved robust initial alignment method under geographic latitude uncertainty and external vibration and shock scenarios

Abstract

Strap-down inertial navigation system (SINS) is an autonomous sensor that can be used for the initial alignment of the shearer. However, due to the lack of external auxiliary sensors in the underground coal mine, it is difficult to obtain the geographic latitude information that required by the initial alignment algorithm. Moreover, the poor working conditions in the underground coal mine will cause the SINS to be disturbed by external vibrations and shocks. Therefore, we propose a robust initial alignment method under geographic latitude uncertainty to overcome these challenges. In our proposed method, the geographic latitude is first estimated before performing initial alignment task. To estimate the geographical latitude, we project the gravity vector into the inertial coordinate frame to establish the geometric relationship between geographic latitude and gravity vector. Then, we derive the error equation of latitude self-estimation method and combine the sliding window and low-pass filter to improve the accuracy of the latitude self-estimation result. Finally, in order to reliably complete the initial alignment even if the SINS is under external vibration and shock environment, we introduce the M estimation theory into the initial alignment of the SINS, and construct the objective function that needs to be optimized based on Cauchy robust function. At the same time, the stochastic gradient descent method was used to solve the extreme value of the objective function and obtain the initial attitude quaternion. Simulation and experiments show that our proposed method has returned very satisfactory results in terms of accuracy and robust.