Title: A theoretical investigation on moving average filtering solution for fixed-path map matching of noisy position data

Authors: Baris Baykant Alagoz; Metin Erturkler; Celaleddin Yeroglu

Addresses: Department of Computer Engineering, Inonu University, Malatya, 44280, Turkey ' Department of Computer Engineering, Inonu University, Malatya, 44280, Turkey ' Department of Computer Engineering, Inonu University, Malatya, 44280, Turkey

Abstract: Precisely estimation of moving object locations from position sensors promises useful implications for many fields of engineering. The mapping of a moving object on a predefined path is an important process for object tracking and remote control applications. Owing to measurement noises of sensors and uncertainties, the measured object location may not precisely match to paths or roads in a map. This study presents a numerical method for a low computational-complexity solution of point to arc type mapping problems. This method has two main tasks: a noise reduction task by short-time moving average filtering of noisy two-dimensional position data, and a map matching task to estimate exact position of an object on a map. To evaluate performance of the investigated method, the algorithm is applied for bus route tracking simulations and results are discussed for several road scenarios and various levels of noise.

Keywords: map matching; noisy position data; short-time moving average filtering; point to arc mapping; object tracking.

DOI: 10.1504/IJSNET.2019.098554

International Journal of Sensor Networks, 2019 Vol.29 No.4, pp.213 - 225

Received: 22 Mar 2018
Accepted: 08 Aug 2018
Published online: 27 Mar 2019 *

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