摘要
为消除奇异点对大飞艇的姿态解算带来的困扰,提出了一种基于卡尔曼滤波的奇异点消除算法.在构造出的卡尔曼滤波模型基础上,将当前状态变量作为先验估计代入滤波器的时间更新方程中,以便及时投射到测量更新方程,并得到测量更新方程所需的数据;此后,通过测量更新方程来校正先验估计,从而获得此状态的后验估计值,并用该估计值来代替加速度计传感数据中的奇异点,从而达到消除传感数据中奇异点的目的.Matlab实验验证了算法的有效性.结果表明,该算法在没有引入延迟的同时,有效消除了系统中传感器信号的毛刺点.
To eliminate singularities which disturb the solution to high altitude airship＇s attitude,an algorithm based on the Kalman filter was proposed for excluding singularities.Based on the developed Kalman filtering model,the current state variables as priori estimates were substituted into the time-updating equations of the filter in order to be mapped onto the measurement-updating equations in time and get the data required in the measurement-updating equations.And then,the priori estimates were corrected by the measurement-updating equations so as to obtain the posterior estimates.The obtained posterior estimates were further substituted for the singularities from accelerometer sensors so as to eliminate the singularities.The Matlab experiments verify the effectiveness of the proposed algorithm,and the experimental results show that the algorithm eliminates signal burrs from the system＇s sensors effectively,with no delay introduced.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2013年第2期191-194,共4页
Journal of Northeastern University(Natural Science)
基金
高等学校科技创新工程重大项目培育资金资助项目(708026)
关键词
奇异点消除
卡尔曼滤波
捷联惯导系统
大飞艇
singularity eliminating
Kalman filter
strapdown inertial navigation system（SINS）
high altitude airship
