A quadratic interpolation-based variational Bayesian algorithm for measurement information lost in underwater navigation
DOI10.1155/2020/6666411zbMath1459.93184OpenAlexW3114655573MaRDI QIDQ2217835
Yuan Yang, Jiacheng Tang, Yujin Kuang, Haoqian Huang, Xiaoguo Zhang, Ting-Ting Zhang
Publication date: 14 January 2021
Published in: Mathematical Problems in Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2020/6666411
Bayesian inference (62F15) Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Measures of information, entropy (94A17)
Cites Work
- Dynamic analysis of multilayers based MEMS resonators
- Observer Kalman filter identification of Suspen-Dome
- Huber's M-estimation-based cubature Kalman filter for an INS/DVL integrated system
- State-space measurement update for GNSS/INS integrated navigation
- Bayesian semiparametric double autoregressive modeling
- Variational Bayesian Adaptive Cubature Information Filter Based on Wishart Distribution
- Multiple-model estimation with variable structure
- A Novel Algorithm for Optimal Placement of Multiple Inertial Sensors to Improve the Sensing Accuracy
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