观测器/卡尔曼滤波在飞行数据处理中的应用  

Application of observer/Kalman filter in flight data processing

作　　者：朱菲菲[1] 高艳辉[2] 肖前贵[2] 胡寿松[2] 

机构地区：[1]南京航空航天大学自动化学院,江苏南京210016 [2]南京航空航天大学无人机院,江苏南京210016

出　　处：《电子设计工程》2016年第20期91-93,97,共4页Electronic Design Engineering

摘　　要：在无人机飞行参数测量中,受环境、干扰或自身稳定性等因素的影响,往往使测量数据中存在野值。为提高飞行数据处理精度,提出了一种基于观测器/卡尔曼滤波辨识(OKID)的新算法用于估计飞行参数。该算法直接利用输入输出数据与系统矩阵得到观测器增益,而观测器增益又收敛于稳定状态下的卡尔曼滤波增益,利用卡尔曼滤波增益即可估计飞行参数。Matlab仿真表明该方法能有效地消除飞行数据中的野值。Affected by the environment, interference or its stability, the outliers often exists in the flight data measurement. In order to improve the flight data processing accuracy, annew algorithm based on the observer/Kalman filter identification （OKID） is proposed to estimate the flight parameters. The algorithm directly uses the input and output data and the system matrix to obtain the observer gain, while the observer gain converges to the steady-state Kalman filter gain .This Kalman filter gain can be used for flight parameters estimation. Matlab simulations show this method can effectively eliminate the outliers in flight data.

关 键 词：数据处理 观测器/卡尔曼滤波 观测器增益 野值剔除 

分 类 号：TN957.51[电子电信—信号与信息处理]