Article: Simulation of multilateration system based on Chan algorithm and conjugate gradient optimisation algorithm Journal: International Journal of Simulation and Process Modelling (IJSPM) 2019 Vol.14 No.5 pp.464 - 473 Abstract: In multilateration (MLAT) systems, the traditional Chan algorithm applies the theory of time-difference-of-arrival (TDOA) to solve the target position of the mathematical model. By introducing intermediate variables, the algorithm adopts a two-step weighted least-squares solution. The introduction of intermediate variables results in the target position equation producing a fuzzy solution, this reduces positioning accuracy. The conjugate gradient algorithm (CGA) is one of the most useful methods for solving large linear equations, it avoids solving the inverse of the matrix, whilst it 'speeds up' the solution of the target position. A four stations multi-point-positioning system mathematical model is established, and a new fusion algorithm Chan-CGA is applied to the MLAT system. Finally, the fusion algorithm is evaluated by simulation and compared with the Chan-Taylor algorithm. Inderscience Publishers - linking academia, business and industry through research

Title: Simulation of multilateration system based on Chan algorithm and conjugate gradient optimisation algorithm

Authors: Jianhua Zhang; Feng Gao; Yang Li; Xueli Wu

Addresses: Hebei Provincial Research Center for Technologies in Process Engineering Automation, Hebei University of Science and Technology, Shijiazhuang, Hebei, 050018, China ' Hebei University of Science and Technology, Shijiazhuang, Hebei, 050018, China ' Hebei Provincial Research Center for Technologies in Process Engineering Automation, Hebei University of Science and Technology, Shijiazhuang, Hebei, 050018, China ' Hebei Provincial Research Center for Technologies in Process Engineering Automation, Hebei University of Science and Technology, Shijiazhuang, Hebei, 050018, China

Abstract: In multilateration (MLAT) systems, the traditional Chan algorithm applies the theory of time-difference-of-arrival (TDOA) to solve the target position of the mathematical model. By introducing intermediate variables, the algorithm adopts a two-step weighted least-squares solution. The introduction of intermediate variables results in the target position equation producing a fuzzy solution, this reduces positioning accuracy. The conjugate gradient algorithm (CGA) is one of the most useful methods for solving large linear equations, it avoids solving the inverse of the matrix, whilst it 'speeds up' the solution of the target position. A four stations multi-point-positioning system mathematical model is established, and a new fusion algorithm Chan-CGA is applied to the MLAT system. Finally, the fusion algorithm is evaluated by simulation and compared with the Chan-Taylor algorithm.

Keywords: multilateration; time-difference-of-arrival; Chan algorithm; conjugate gradient optimisation algorithm.

DOI: 10.1504/IJSPM.2019.104117

International Journal of Simulation and Process Modelling, 2019 Vol.14 No.5, pp.464 - 473

Received: 01 Oct 2018
Accepted: 12 Jan 2019
Published online: 14 Dec 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article

Title: Simulation of multilateration system based on Chan algorithm and conjugate gradient optimisation algorithm

Keep up-to-date