Cold starting temperature time-related compensation model of inertial sensors based on particle swarm optimization algorithm

Abstract

With the miniaturization of inertial instruments, sensors mounted inside are vulnerable to interference. In a complex thermal transmission environment, temperature drift is the main factor restricting the precision of high-performance inertial sensors. To solve this problem, a new method for compensating the time-related cold starting temperature drift of the inertial sensors is introduced in this paper. Based on the perspective that temperature drift can be regarded as the response curve of the sensor system to temperature and temperature gradient, temperature compensation models of first-order, second-order, and higher-order are proposed. Meanwhile, the particle swarm optimization algorithm is used to solve the model parameters. Under various practical circumstances, the method can be used to flexibly compensate the temperature drift and reduce the standard deviation of the output signal by about four times. Compared to other models or algorithms, the simulation and experimental results indicate that the proposed model is superior in adaptability, stability, and reliability.