A Systematization of the Unscented Kalman Filter Theory

• Published in: IEEE transactions on automatic control Vol. 60; no. 10; pp. 2583 - 2598
• Main Authors: Menegaz, Henrique M. T., Ishihara, Joao Y., Borges, Geovany A., Vargas, Alessandro N.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Additives; Automatic control; Computation; Construction equipment; Covariance; Covariance matrices; Equations; Estimation; Kalman filters; Noise; State of the art; Symmetry; Transformations; Vectors; Unscented Transformation (UT); Unscented Kalman Filter (UKF)
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2015.2404511

In this paper, we propose a systematization of the (discrete-time) Unscented Kalman Filter (UKF) theory. We gather all available UKF variants in the literature, present corrections to theoretical inconsistencies, and provide a tool for the construction of new UKF's in a consistent way. This systematization is done, mainly, by revisiting the concepts of Sigma-Representation, Unscented Transformation (UT), Scaled Unscented Transformation (SUT), UKF, and Square-Root Unscented Kalman Filter (SRUKF). Inconsistencies are related to 1) matching the order of the transformed covariance and cross-covariance matrices of both the UT and the SUT; 2) multiple UKF definitions; 3) issue with some reduced sets of sigma points described in the literature; 4) the conservativeness of the SUT; 5) the scaling effect of the SUT on both its transformed covariance and cross-covariance matrices; and 6) possibly ill-conditioned results in SRUKF's. With the proposed systematization, the symmetric sets of sigma points in the literature are formally justified, and we are able to provide new consistent variations for UKF's, such as the Scaled SRUKF's and the UKF's composed by the minimum number of sigma points. Furthermore, our proposed SRUKF has improved computational properties when compared to state-of-the-art methods.