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参数辨识法与卡尔曼滤波法精对准实验研究 被引量:2

Experimental Research on Parameter Identification and Kalman Filtering Alignment Methods
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摘要 为了比较静基座下参数辨识法精对准和卡尔曼滤波法精对准的对准精度,利用导航计算机采集惯性测量组件输出的比力和角增量信号,分别采用参数辨识法和卡尔曼滤波法完成精对准,台架实验结果表明,在粗对准方法相同、精对准时间相等的情况下,卡尔曼滤波法比参数辨识法能够获得更好的对准精度。参数辨识法精对准具有算法简单、运算量小等优点,但是其对准精度不高,适合在要求计算量小但对精度要求不高的条件下使用。卡尔曼滤波法具有较高的对准精度,但是要求系统的模型准确,适合在基座静止、失准角为小角度的条件下使用。 In order to compare the alignment accuracy of parameter identification alignment method with Kalman filtering alignment method,the navigation computer was used to collect the force and angle increment signals output from the inertial measurement unit,and complete the accurate alignment missions by use of the parameter identification method and the Kalman filtering method respectively.The platform experimental results showed that the Kalman filtering accurate alignment algorithm can obtain the better alignment accuracy than the parameter identification accurate alignment algorithm under the premise of using the same coarse alignment method and the same accurate alignment time.The parameter identification alignment algorithm is simple and has a small amount of calculation,but its alignment accuracy is not very high.So it is suitable for using in the conditions that needs small amount of calculation with low requirement of alignment accuracy.The Kalman filtering alignment algorithm can obtain the better alignment accuracy in case of a accurate system model,so it is suitable for using in the conditions that the misalignment angle is small and the base is stationary.
出处 《火炮发射与控制学报》 北大核心 2010年第3期50-55,共6页 Journal of Gun Launch & Control
关键词 计算数学 捷联式惯性导航系统 参数辨识 卡尔曼滤波 numerical mathematics SINS parameter identification Kalman filter
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参考文献5

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