RBFN 과 강화학습을 활용한 관성항법장치의 자이로 바이어스 추정 기법

Abstract

In this paper, a new gyro bias estimation method is proposed by using reinforcement learning and RBFN (Radial Basis Function Network). A set of lattices for better navigation performance is investigated using reinforcement learning. A function of estimating gyro bias is constructed by connecting the set lattices using RBFN. The performance of the proposed method is evaluated by comparing with various methods such as 3rd order function method, 3rd order function with a temperature rate method (TRM), classic RBFN method, and MLR (Multiple Linear Regression) method. The results of experiment show that the proposed gyro bias estimation method has better navigation performance than other methods.