Orthogonal Simplex Chebyshev-Laguerre Cubature Kalman Filter Applied in Nonlinear Estimation Systems
Source abstract
Abstract
To further improve the filtering accuracy in nonlinear estimation systems, a nonlinear filter, called the orthogonal simplex Chebyshev-Laguerre cubature Kalman filter (OSCL-CKF), is proposed. The filter is built within the cubature Kalman filter framework, which transforms the multidimensional, Gaussian weighted integral into a spherical-radial coordinate system. In the spherical integral, an orthogonal method is introduced to the third-degree spherical simplex rule, and then the nonlocal sampling effects can be reduced by tuning the high order interference terms. In the radial integral, the quadrature points and corresponding weights are determined according to the Chebyshev-Laguerre (CL) equation, which enables the nonlinear filter to improve the precision by the order of the CL polynomial. Numerical results show that the proposed filter outperforms the conventional algorithms.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Target Tracking and Data Fusion in Sensor Networks · GNSS positioning and interference · Inertial Sensor and Navigation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Information and Navigation College, Air Force Engineering University, Xi’an 710077, China
Funding
the National Natural Science Foundation of China
References (31)
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