2014•Acta ArmamentariiRequires access

Data Fusion Algorithm for Target Trajectory Determination Based on Spline Function Representation

Gong Zhi-hu

Open publisher page 2 citations

Abstract

A data fusion algorithm for target trajectory determination based on spline function representation is presented. Under least squares criterion,a nonlinear optimization strategy is applied to search the optimal spline nodes according to different trajectory characteristics. The truncation error can be eliminated and the estimated parameters in the fusion model can be reduced greatly. Therefore,the computational efficiency and estimation accuracy for the trajectory parameters will be enhanced. Finally,the calculation show the validity of the proposed algorithm,and the system errors for each measuring data can be compensated accurately.

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What this paper is about

A data fusion algorithm for target trajectory determination based on spline function representation is presented. Under least squares criterion,a nonlinear optimization strategy is applied to search the optimal spline nodes according to different trajectory characteristics. The truncation error can be eliminated and the estimated parameters in the fusion model can be reduced greatly. Therefore,the computational efficiency and estimation accuracy for the trajectory parameters will be enhanced. Finally,the calculation show the validity of the proposed algorithm,and the system errors for each measuring data can be compensated accurately.

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Available abstract

A data fusion algorithm for target trajectory determination based on spline function representation is presented. Under least squares criterion,a nonlinear optimization strategy is applied to search the optimal spline nodes according to different trajectory characteristics. The truncation error can be eliminated and the estimated parameters in the fusion model can be reduced greatly. Therefore,the computational efficiency and estimation accuracy for the trajectory parameters will be enhanced. Finally,the calculation show the validity of the proposed algorithm,and the system errors for each measuring data can be compensated accurately.

Key concepts: Spline (mechanical), Trajectory, Algorithm, Fusion, Sensor fusion, Representation (politics), Computer science, Truncation (statistics)

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