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Res-EMSA: Adaptive Adjustment of Innovation Based on Efficient Multihead Self-Attention in GNSS/INS Tightly Integrated Navigation System 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2024, 卷号: 21, 页码: 5
作者:  Xu, Hongfu;  Luo, Haiyong;  Wu, Zijian;  Zhao, Fang
收藏  |  浏览/下载:17/0  |  提交时间:2024/05/20
Technological innovation  Global navigation satellite system  Navigation  Feature extraction  Adaptation models  Measurement uncertainty  Kalman filters  Deep learning  extended Kalman filter (EKF)  innovation matrix  integrated navigation  
Predicting the Noise Covariance With a Multitask Learning Model for Kalman Filter-Based GNSS/INS Integrated Navigation 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 卷号: 70, 页码: 13
作者:  Wu, Fan;  Luo, Haiyong;  Jia, Hongwei;  Zhao, Fang;  Xiao, Yimin;  Gao, Xile
收藏  |  浏览/下载:51/0  |  提交时间:2021/12/01
Adaptive integrated navigation  deep learning  denoising autoencoder (DAE)  Kalman filter (KF)  measurement noise  process noise  
RL-AKF: An Adaptive Kalman Filter Navigation Algorithm Based on Reinforcement Learning for Ground Vehicles 期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 11, 页码: 25
作者:  Gao, Xile;  Luo, Haiyong;  Ning, Bokun;  Zhao, Fang;  Bao, Linfeng;  Gong, Yilin;  Xiao, Yimin;  Jiang, Jinguang
收藏  |  浏览/下载:69/0  |  提交时间:2020/12/10
integrated navigation  Kalman filter  process noise covariance estimation  reinforcement learning  deep deterministic policy gradient