期刊
SIGNAL PROCESSING
卷 114, 期 -, 页码 112-116出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.sigpro.2015.02.022
关键词
Embedded cubature Kalman filter; Fifth-degree embedded cubature rule; Adaptive method; Maximum likelihood criterion; Gaussian filter
资金
- National Natural Science Foundation of China [61001154, 61201409, 61371173]
- China Postdoctoral Science Foundation [2013M530147, 2014T70309]
- Heilongjiang Postdoctoral Fund [LBH-Z13052, LBH-TZ0505]
- Fundamental Research Funds for the Central Universities of Harbin Engineering University [HEUCFX41307]
The choice of free parameter in embedded cubature Kalman filter (ECKF) is important, and it is difficult to choose an optimal value in practice. To solve this problem, an adaptive method is proposed to determine the value of free parameter of ECKF based on maximum likelihood criterion. By incorporating this method in the third-degree ECKF, a new third-degree adaptive ECKF (AECKF) algorithm is obtained. To further improve the accuracy of the third-degree AECKF, a new fifth-degree AECKF based on the fifth-degree embedded cubature rule is developed. Simulation results show that the proposed algorithms have higher estimation accuracy than existing methods. (C) 2015 Elsevier B.V. All rights reserved.
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