中国科学院计算技术研究所机构知识库

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限定条件	资助项目：Key Research and Development Project from Hebei Province[19210404D]

已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择期刊影响因子升序期刊影响因子降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序WOS被引频次升序WOS被引频次降序题名升序题名降序
	Towards Predicting the Measurement Noise Covariance with a Transformer and Residual Denoising Autoencoder for GNSS/INS Tightly-Coupled Integrated Navigation 期刊论文 REMOTE SENSING, 2022, 卷号: 14, 期号: 7, 页码: 22 作者:  Xu, Hongfu;  Luo, Haiyong;  Wu, Zijian;  Wu, Fan;  Bao, Linfeng;  Zhao, Fang 收藏  |  浏览/下载：19/0  |  提交时间：2022/12/07 tightly coupled integrated navigation  measurement noise estimation  transformer  adaptive Kalman filtering
	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：36/0  |  提交时间：2021/12/01 Adaptive integrated navigation  deep learning  denoising autoencoder (DAE)  Kalman filter (KF)  measurement noise  process noise
	Adaptive Kalman filtering-based pedestrian navigation algorithm for smartphones 期刊论文 INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2020, 卷号: 17, 期号: 3, 页码: 14 作者:  Yu, Chen;  Luo, Haiyong;  Fang, Zhao;  Qu, Wang;  Shao, Wenhua 收藏  |  浏览/下载：46/0  |  提交时间：2020/12/10 Pedestrian navigation  error model system  inertial sensors integration  magnetic field  heading estimation