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A Novel Statistical Similarity Measure-Based Outlier-Robust Cubature Kalman Filtering Framework Applied for Underwater Vehicle
- Citation Author(s):
- Submitted by:
- Haoqian Huang
- Last updated:
- Fri, 01/13/2023 - 03:24
- DOI:
- 10.21227/taed-gy08
- Data Format:
- License:
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- Keywords:
Abstract
These data is state estimation accuracy of the proposed algorithm.
These data includes the position estimation accuracy and velocity estimation accuracy of the algorithm.
The data are explained below:
rmse_ckf_1 and rmse_ckf_2 are the position accuracy and speed accuracy of CKF，respectively.
rmse_ukf_1 and rmse_ukf_2 are the position accuracy and speed accuracy of UKF，respectively.
rmse_ssmckf1_2 and rmse_ssmckf1_2 are the position accuracy and speed accuracy of SSM-RCKF when the similarity function is selected as exponentiac function, respectively.
rmse_ssmckf2_2 and rmse_ssmckf2_2 are the position accuracy and speed accuracy of SSM-RCKF when the similarity function is selected as logarithmic function, respectively.
rmse_ssmckf3_2 and rmse_ssmckf3_2 are the position accuracy and speed accuracy of SSM-RCKF when the similarity function is selected as square-roots function, respectively.
