title: A reliability-based track fusion algorithm.
abstract: The common track fusion algorithms in multi-sensor systems have some defects, such as serious imbalances between accuracy and computational cost, the same treatment of all the sensor information regardless of their quality, high fusion errors at inflection points. To address these defects, a track fusion algorithm based on the reliability (TFR) is presented in multi-sensor and multi-target environments. To improve the information quality, outliers in the local tracks are eliminated at first. Then the reliability of local tracks is calculated, and the local tracks with high reliability are chosen for the state estimation fusion. In contrast to the existing methods, TFR reduces high fusion errors at the inflection points of system tracks, and obtains a high accuracy with less computational cost. Simulation results verify the effectiveness and the superiority of the algorithm in dense sensor environments.
authors.affiliation: College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, China.
authors.forename: Li
authors.initials: L
authors.lastname: Xu
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China.
authors.forename: Liqiang
authors.initials: L
authors.lastname: Pan
authors.affiliation: Department of Mathematics, Harbin Institute of Technology, Harbin, Heilongjiang, China.
authors.forename: Shuilin
authors.initials: S
authors.lastname: Jin
authors.affiliation: College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, China.
authors.forename: Haibo
authors.initials: H
authors.lastname: Liu
authors.affiliation: College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, China.
authors.forename: Guisheng
authors.initials: G
authors.lastname: Yin
mesh_terms: D000465:Algorithms; D015203:Reproducibility of Results