High-Order Unscented Transformation Based on the Bayesian Learning for Nonlinear Systems with Non-Gaussian Noises. - Jiaxin Hou; Weidong Zhou 001; Wen-An Zhang 001; Cong Zhang; Chen Chen 098; Chenghao Shan (CIS, 2019)

A New Variational Bayesian-Based Kalman Filter with Unknown Time-Varying Measurement Loss Probability and Non-Stationary Heavy-Tailed Measurement Noise. - Chenghao Shan; Weidong Zhou 001; Yefeng Yang; Hanyu Shan (Entropy, 2021)

Multi-Fading Factor and Updated Monitoring Strategy Adaptive Kalman Filter-Based Variational Bayesian. - Chenghao Shan; Weidong Zhou 001; Yefeng Yang; Zihao Jiang 004 (Sensors, 2021)

A New Heavy-Tailed Robust Kalman Filter with Time-Varying Process Bias. - Zihao Jiang 004; Weidong Zhou 001; Guangle Jia; Chenghao Shan; Liang Hou (Circuits Syst. Signal Process., 2022)

A new Gaussian approximate filter with colored non-stationary heavy-tailed measurement noise. - Chenghao Shan; Weidong Zhou 001; Zihao Jiang 004; Hanyu Shan (Digit. Signal Process., 2022)

A new robust Kalman filter with measurement loss based on mixing distribution. - Chenghao Shan; Weidong Zhou 001; Yefeng Yang; Hanyu Shan (Trans. Inst. Meas. Control, 2022)

A GNSS Terrestrial Water Storage Inversion Method Based on GRACE Spatial Constraints. - Bin Liu 062; Chenghao Shan; Weilong Rao; Xueming Xing; Jianbo Tan; Yabo Luo (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)