Nonlinear Decentralized Data Fusion with Generalized Inverse Covariance Intersection

2019-01-01
Noack, Benjamin
Orguner, Umut
Hanebeck, Uwe D.
Decentralized data fusion is a challenging task even for linear estimation problems. Nonlinear estimation renders data fusion even more difficult as dependencies among the nonlinear estimates require complicated parameterizations. It is nearly impossible to reconstruct or keep track of dependencies. Therefore, conservative approaches have become a popular solution to nonlinear data fusion. As a generalization of Covariance Intersection, exponential mixture densities have been widely applied for nonlinear fusion. However, this approach inherits the conservativeness of Covariance Intersection. For this reason, the less conservative fusion rule Inverse Covariance Intersection is studied in this paper and also generalized to nonlinear data fusion. This generalization employs a conservative approximation of the common information shared by the estimates to be fused. This bound of the common information is subtracted from the fusion result. In doing so, less conservative fusion results can be attained as an empirical analysis demonstrates.

Suggestions

Approximate Analytical Solutions for the Weight Optimization Problems of CI and ICI
Orguner, Umut (2017-10-12)
Approximate analytical formulae are proposed for the solutions of the weight optimization problems involved in Covariance Intersection (CI) and Inverse Covariance Intersection (ICI). The methodology used for obtaining the analytic approximations boils down to using just two Newton iterations with the initial weight value 1/2. The simulation results show that quite acceptable root-mean-square (RMS) error levels are achievable with the proposed approximate analytical weights with less computations compared to...
Basis reduction and the complexity of branch-and-bound
Pataki, Gábor; Tural, Mustafa Kemal; Wong, Erick B. (2010-05-06)
The classical branch-and-bound algorithm for the integer feasibility problem [GRAPHICS] has exponential worst case complexity. We prove that, it. is surprisingly efficient on reformulations of (01), in which the columns of the constraint, matrix are short and near orthogonal, i e, a reduced basis of the generated lattice. when the entries of A ale from {1, ,M} for a large enough M, branch-and-bound solves almost all reformulated instances at the root. node For all A matrices we prove an upper bound on th...
Efficient adaptive regression spline algorithms based on mapping approach with a case study on finance
Koc, Elcin Kartal; İyigün, Cem; Batmaz, İnci; Weber, Gerhard-Wilhelm (2014-09-01)
Multivariate adaptive regression splines (MARS) has become a popular data mining (DM) tool due to its flexible model building strategy for high dimensional data. Compared to well-known others, it performs better in many areas such as finance, informatics, technology and science. Many studies have been conducted on improving its performance. For this purpose, an alternative backward stepwise algorithm is proposed through Conic-MARS (CMARS) method which uses a penalized residual sum of squares for MARS as a T...
Residual based Adaptive Unscented Kalman filter for satellite attitude estimation
Söken, Halil Ersin (2012-12-01)
Determining the process noise covariance matrix in Kalman filtering applications is a difficult task especially for estimation problems of the high-dimensional states where states like biases or system parameters are included. This study introduces a simplistic residual based adaptation method for the Unscented Kalman Filter (UKF), which is used for small satellite attitude estimation. For a satellite with gyros and magnetometers onboard, the proposed adaptive UKF algorithm estimates the attitude as well as...
Stable controller design for the T-S fuzzy model of a flexible-joint robot arm based on lie algebra
Gurkan, E; Banks, SP; Erkmen, İsmet (2003-12-12)
In this paper, we develop a novel approach for the stability of T-S fuzzy systems using the Lie algebra generated by the linear subsystems used in the T-S model. The theory is illustrated on the T-S fuzzy model of a flexible joint robot arm. We use our approach to design a controller satisfying our Lie algebra based stability criteria and demonstrate its performance on the robotic system.
Citation Formats
B. Noack, U. Orguner, and U. D. Hanebeck, “Nonlinear Decentralized Data Fusion with Generalized Inverse Covariance Intersection,” 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52723.