System-level calibration method of FOG-MEMS accelerometer SINS for unmanned aerial vehicle electro-optical pod

The electro-optical pod is an important optical payload of the drone, provides the operators with the required visual images, serves as a crucial basis for command decisions. The Strapdown Inertial Navigation System (SINS) in the electro-optical pod utilizes signals collected by the Inertial Measurement Unit (IMU) to provide the drone with precise positioning and navigation capabilities. The FOG (Fiber Optic Gyroscope)–MEMS (Micro-Electro-Mechanical Systems) accelerometer SINS combines the advantages of optical gyroscopes and MEMS accelerometers, with high performance, small size, and low power consumption characteristics. It has gradually become a optional choice for unmanned aerial vehicle electro-optical pod. As an important feedback component in the control loop of electro-optical pod, SINS needs to be periodically calibrated and compensated for its errors in order to ensure the stability of the electro-optical gimbals during actual stabilization processes. Taking into account the measurement and error characteristics of the SINS, a mathematical error model is established considering the asynchronous time between the gyroscope and accelerometer, inner lever arm error, outer lever arm error, and quadratic error of the FOG-MEMS accelerometer SINS. A 40-D Kalman filter is formed based on the velocity error observation and position error observation, and a reasonable calibration path is used to estimate the system error parameters. The effectiveness of the system-level calibration method is verified through semi-physical simulation experiment and real experiments.