强跟踪卡尔曼滤波器的研究与应用  

Research and Simulation of Strong Tracking Kalman Filter

作　　者：刘昱鑫 周鑫 曹玉波[1] LIU Yuxin;ZHOU Xin;CAO Yubo(School of Information and Control Engineering,Jilin Institute of Chemical Technology,Jilin City 132022,China;Key Project Engineering Department,Zhejiang SUPCON Technology Co.,Ltd,Wuxi 214026,China)

机构地区：[1]吉林化工学院信息与控制工程学院,吉林吉林132022 [2]浙江中控技术股份有限公司重点项目工程部,江苏无锡214026

出　　处：《吉林化工学院学报》2023年第9期55-58,共4页Journal of Jilin Institute of Chemical Technology

摘　　要：针对无人机速度信号估计存在噪声等问题,研究一种基于强跟踪滤波与卡尔曼滤波对未知信号进行估计的滤波算法。在预测先验误差协方差时引入渐消因子,减弱过去数据对滤波效果的影响,从而提升滤波器的响应速度与精度。对无人机自驾仪估计的速度信号进行滤波处理。结果表明,强跟踪卡尔曼滤波器信号响应更快,超调更小,精度更高。Aiming at the problem of noise in UAV speed signal estimation,a filter algorithm based on strong tracking filter and Kalman filter was proposed to estimate unknown signal.When predicting the prior error covariance,the fading factor was introduced to reduce the influence of the past data on the filtering effect,and thus improved the response speed and accuracy of the filter.The speed signal estimated by the UAV autopilot was filtered.The results showed that the signal response of strong tracking Kalman filter was faster,the overshoot was smaller and the precision was higher.

关 键 词：强跟踪卡尔曼滤波 无人机 状态估计 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]