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

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.