摘要
由于加速度计输出动态噪声的存在,无陀螺惯性测量组合(NG IMU)导航误差随时间迅速累积.采用传统卡尔曼滤波方法进行NG IMU/GPS组合导航系统设计时,又由于观测噪声的复杂性,造成滤波结果不明显.针对上述噪声统计特性不易确定的特点,基于NG IMU九加速度计配置方案,提出利用模糊逻辑自适应卡尔曼滤波方法进行NG IMU/GPS组合导航系统设计.模糊逻辑自适应卡尔曼滤波器(FLAKF)通过对噪声方差进行修正,将卡尔曼滤波器调整到最优状态.同时进行了系统位移、速度、角速度仿真,仿真结果验证了模糊逻辑自适应卡尔曼滤波方法的可行性.
In a non-gyro inertial measurement unit （NGIMU） system, an inevitable accumulation error of navigation parameters is produced due to the existence of the dynamic noise of the accelerometer output. When designing an integrated navigation system, which is based on a nine-configuration NGIMU and a single antenna Global Positioning System （GPS） by using the conventional Kalman filter （CKF）, the filtering results are divergent because of the complicity of the system measurement noise. So a fuzzy logic adaptive Kalman filter （FLAKF） is applied in the design of NGIMU/GPS. The FLAKF optimizes the Kalman filter by modifying the noise＇s covariance. A simulation case for estimating the position, velocity and angle rate is investigated by this approach. Results verify the feasibility of the FLAKF.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2006年第12期2044-2048,共5页
Journal of Harbin Institute of Technology
基金
黑龙江省博士后基金资助项目
哈尔滨工业大学优秀青年教师培养计划资助项目(HITQNJS.2006.009)
