在以太阳作为 目标源的天文测速导航中，多普勒速度量测量存在较多野值误差，严重影响导航精度。对此，提出一种基于高斯过程回归与无迹卡尔曼滤波(Gaussian process regression and unscented Kalman filte-ring，GPR-UKF)的野值检测修复方法，建立速度量测量的动态预测模型。此外，还针对不同参数对模型精度的影响进行研究。经仿真验证，所提方法效果显著优于传统野值处理方法。
Navigation method using angle/velocity measurement based on GPR-UKF
In astronomical velocity measurement navigation with the Sun as the target source,there are many outliers in Doppler velocity measurement,which seriously affects the accuracy of navigation.Thus,a outlier detection and repair method based on Gaussian process regression and unscented Kalman filtering(GPR-UKF)is proposed to establish a dynamic prediction model for velocity measurement.In addition,the impact of different parameters on the accuracy of the model is researched.Simulation verification test demonstrates that the proposed method has better performance than traditional outlier processing methods.
万方数据
维普
