基于自适应遗传算法的MEMS加速度计快速标定方法

MEMS inertial measurement unit (MIMU) calibration is one of an important research direction in low-precision inertial navigation. Traditional calibration method has complex operating procedures and depends most on turntable accuracy. In order to overcome the problem of MIMU calibration in batch production, this paper presents a rapid micro-electro-mechanical system (MEMS) accelerometer calibration method based on adaptive genetic algorithm (GA), which converts calibration task to parameter optimization. Firstly, the principle of norm observation is adopted to establish the objective optimization function. Secondly, the optimal calibration scheme is designed on the basis of system observability analysis. Finally, calibration parameters can be optimized through adaptive GA with global search capability. Experimental results demonstrate that, compared with Newton's iteration, the proposed method can improve calibration accuracy by 1-3 orders of magnitude and increase operational speed by 61%. After the proposed calibration, the horizontal attitude error is less than 0.1° and its accuracy can reach the same order of magnitude as that in traditional method, which verifies its superiority and practicability.