基于最大熵卡尔曼滤波的机载SINS星敏感器辅助空中标定技术

Maximum Correntropy Kalman Filter Based Self Calibration of Airborne SINS Adopting Aided by Star Sensor

为增强机载捷联惯导系统(SINS)在自标定过程中的可观测性,提升陀螺仪漂移和加速度计零偏估计的速度和精度,引入星敏感器姿态信息和GPS速度信息,辅助完成捷联惯导系统的空中标定;同时,考虑在实际空中飞行条件下,受气流、电磁干扰等影响,姿态和速度的量测噪声呈非高斯分布且噪声统计特性不精确,导致经典卡尔曼滤波性能降低;为有效利用量测信号中的高阶矩信息,在卡尔曼滤波中采用最大熵准则代替最小均方误差准则,对星敏感器辅助下的机载捷联惯导系统的误差进行标定;仿真结果表明,经最大熵卡尔曼滤波后,惯性器件误差的标定精度明显提升;在采用星敏感器后,对陀螺仪漂移的标定速度和精度都得到了提升。

In order to strength the observability of velocity and attitude in the self-calibration process of airbrone strapdown inertial navigation system(SINS),and to improve the estimation accuracy of gyro draft and accelerometer zero bias,the attitude from star sensor and velocity from the GPS are introduced to calibrate in the strapdown inertial navigation system.Meanwhile the measurement noise of attitude and velocity becomes non-Gaussian distributed,and the statistical characteristics of noise is inaccurate,the attitude and velocity are affected by pulse noise and electromagnetic interference under the actual flight conditions,which leads to the degeneration of Kalman filter performance.In order to utilize the high-order moment information of measurement signals,the minimum mean square error criterion is replaced by maximum correntropy criterion in Kalman filter,which is used to calibrate the airbrone SINS aided by the star sensor and the GPS.The simulation results show that the accuracy of calibration is improved by the maximum correntropy Kalman filter.And the speed and accuracy in calibration are improved by the aide of the star sensor.