Spinning Missile Attitude Estimation System Based on the Sun Vector and MEMS

In this paper, a new method of estimating the attitude to spinning missile was proposed. The author designed the method of using sun vector to correct the gyro bias of MEMS sensor and using the Kalman filter algorithm to estimate the spinning missile attitude. According to the nature of spinning missile, this paper designed a special sun sensor that is used to measure the sun vector replaced the commonly used in MEMS sensor of accelerometer and magnetometer to correct the gyro bias of MEMS sensor. The sun vector measuring device comprises the transparent shell, the photocell array, the real-time clock and the controller. When the sun shines through the transparent shell illuminates the photocell array, the photocell array can convert the solar energy into the electric potential signal. According to the size of the solar energy and the angle of the photocell laying, combining with the accurate time provided by the real time clock, the sun vector of this time is obtained through the main controller processes data. The Kalman filer state equation and observation equation established by the quaternion differential equation is used to estimate the spinning missile attitude. The simulation results show that this method can obtain the higher accuracy attitude angle of spinning missile.