一种结合交互式多模型和自适应UKF的UWB/INS紧组合导航算法  

An UWB/INS tight integrated navigation algorithm combining interactive multi model and adaptive UKF

作　　者：李俊杰 任博华 王海钢 延春明 李灯熬 LI Junjie;REN Bohua;WANG Haigang;YAN Chunming;LI Dengao(Huayang New Material Technology Group Co.,Ltd.,Yangquan 045000,China;School of Information and Computer Science,Taiyuan University of Technology,Jinzhong 030600,China;Xinyuan Company,Lu’an Chemical Group,Shouyang 045400,China)

机构地区：[1]华阳新材料科技集团有限公司,山西阳泉045000 [2]太原理工大学信息与计算机学院,山西晋中030600 [3]潞安化工集团新元公司,山西寿阳045400

出　　处：《电子设计工程》2023年第8期32-36,41,共6页Electronic Design Engineering

基　　金：山西省重点研发计划重点项目(YM19017)。

摘　　要：超宽带技术在煤矿井下定位时,会受非视距、多径效应和电磁干扰等不利影响导致定位性能下降,该文提出了一种结合交互式多模型和自适应无迹卡尔曼滤波的超宽带/惯导紧组合导航算法。采用匀速与匀加速两个运动模型交叉耦合模拟井下目标的运动;采用无迹卡尔曼算法对两种传感器信息进行非线性滤波,得到较精确的定位信息;利用自适应模糊推理方法调整测量噪声协方差矩阵,提高定位精度和鲁棒性。仿真实验结果显示,提出的IMM-AUKF算法较传统算法跟踪精度提高了近10%。When ultra wideband technology is used in underground coal mine positioning,it will be adversely affected by non line of sight,multipath effect and electromagnetic interference,resulting in the decline of positioning performance.An UWB/INS tight integrated navigation algorithm combining interactive multi model and adaptive unscented Kalman filter is proposed.The cross coupling of uniform velocity and uniform acceleration is used to simulate the movement of downhole target;The unscented Kalman algorithm is used to nonlinear filter the two kinds of sensor information to obtain more accurate positioning information;The adaptive fuzzy inference method is used to adjust the measurement noise covariance matrix to improve the positioning accuracy and robustness.Simulation results show that the tracking accuracy of the proposed IMM-AUKF algorithm is nearly 10%higher than that of the traditional algorithm.

关 键 词：超宽带 惯性导航 交互式多模型 自适应无迹卡尔曼滤波 模糊推理 高精度 

分 类 号：TN961[电子电信—信号与信息处理]