Segmentation compensation method for FOG temperature error based on particle swarm optimization algorithm

Aiming at the poor adaptability of single-model compensation method for fiber optic gyro (FOG) temperature error, a segmentation compensation method based on particle swarm optimization (PSO) algorithm is proposed. Based on the idea of piecewise modeling compensation, this method adds the influence factors of temperature and temperature change rate into the modeling, and introduces PSO algorithm to optimize the extreme value, so as to obtain the optimal compensation function. In order to verify the compensation effect of the proposed method, the FOG temperature experiment within-15℃ to 50℃ is designed, and the temperature error is compensated by the proposed method and traditional method, respectively. Experimental results show that the proposed method can greatly reduce temperature error is of real time compensation. Compared with the traditional algorithm, the zero offset average of FOG is reduced by an order of magnitude. © 2019, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.