Next Article in Journal
The Investigation of a SAW Oxygen Gas Sensor Operated at Room Temperature, Based on Nanostructured ZnxFeyO Films
Previous Article in Journal
Location Privacy Protection in Distributed IoT Environments Based on Dynamic Sensor Node Clustering
Previous Article in Special Issue
3D Tdoa Problem Solution with Four Receiving Nodes
Open AccessArticle

Accuracy Analysis in Sensor Networks for Asynchronous Positioning Methods

Positioning Department, Drotium, Universidad de León, 24071 León, Spain
Department of Mechanical, Computer and Aerospace Engineering, Universidad de León, 24071 León, Spain
Author to whom correspondence should be addressed.
Sensors 2019, 19(13), 3024;
Received: 6 June 2019 / Revised: 8 July 2019 / Accepted: 8 July 2019 / Published: 9 July 2019
The accuracy requirements for sensor network positioning have grown over the last few years due to the high precision demanded in activities related with vehicles and robots. Such systems involve a wide range of specifications which must be met through positioning devices based on time measurement. These systems have been traditionally designed with the synchronization of their sensors in order to compute the position estimation. However, this synchronization introduces an error in the time determination which can be avoided through the centralization of the measurements in a single clock in a coordinate sensor. This can be found in typical architectures such as Asynchronous Time Difference of Arrival (A-TDOA) and Difference-Time Difference of Arrival (D-TDOA) systems. In this paper, a study of the suitability of these new systems based on a Cramér-Rao Lower Bound (CRLB) evaluation was performed for the first time under different 3D real environments for multiple sensor locations. The analysis was carried out through a new heteroscedastic noise variance modelling with a distance-dependent Log-normal path loss propagation model. Results showed that A-TDOA provided less uncertainty in the root mean square error (RMSE) in the positioning, while D-TDOA reduced the standard deviation and increased stability all over the domain. View Full-Text
Keywords: sensor networks; TDOA; asynchronous; Cramér–Rao lower bound; heteroscedasticity sensor networks; TDOA; asynchronous; Cramér–Rao lower bound; heteroscedasticity
Show Figures

Figure 1

MDPI and ACS Style

Álvarez, R.; Díez-González, J.; Alonso, E.; Fernández-Robles, L.; Castejón-Limas, M.; Perez, H. Accuracy Analysis in Sensor Networks for Asynchronous Positioning Methods. Sensors 2019, 19, 3024.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

Back to TopTop