Publications
2019
1.
Díez-González, Javier; Álvarez, Rubén; Sánchez-González, Lidia; Fernández-Robles, Laura; Pérez, Hilde; Castejón-Limas, Manuel
3D Tdoa problem solution with four receiving nodes Artículo de revista
En: Sensors, vol. 19, no 13, pp. 2892, 2019, (Publisher: MDPI).
Resumen | Enlaces | BibTeX | Etiquetas: 3D, LPSs, positioning, TDOA
@article{diez-gonzalez_3d_2019,
title = {3D Tdoa problem solution with four receiving nodes},
author = {Javier Díez-González and Rubén Álvarez and Lidia Sánchez-González and Laura Fernández-Robles and Hilde Pérez and Manuel Castejón-Limas},
url = {https://www.mdpi.com/1424-8220/19/13/2892},
year = {2019},
date = {2019-01-01},
journal = {Sensors},
volume = {19},
number = {13},
pages = {2892},
abstract = {Time difference of arrival (TDOA) positioning methods have experienced growing importance over the last few years due to their multiple applications in local positioning systems (LPSs). While five sensors are needed to determine an unequivocal three-dimensional position, systems with four nodes present two different solutions that cannot be discarded according to mathematical standards. In this paper, a new methodology to solve the 3D TDOA problems in a sensor network with four beacons is proposed. A confidence interval, which is defined in this paper as a sphere, is defined to use positioning algorithms with four different nodes. It is proven that the separation between solutions in the four-beacon TDOA problem allows the transformation of the problem into an analogous one in which more receivers are implied due to the geometric properties of the intersection of hyperboloids. The achievement of the distance between solutions needs the application of genetic algorithms in order to find an optimized sensor distribution. Results show that positioning algorithms can be used 96.7% of the time with total security in cases where vehicles travel at less than 25 m/s.},
note = {Publisher: MDPI},
keywords = {3D, LPSs, positioning, TDOA},
pubstate = {published},
tppubtype = {article}
}
Time difference of arrival (TDOA) positioning methods have experienced growing importance over the last few years due to their multiple applications in local positioning systems (LPSs). While five sensors are needed to determine an unequivocal three-dimensional position, systems with four nodes present two different solutions that cannot be discarded according to mathematical standards. In this paper, a new methodology to solve the 3D TDOA problems in a sensor network with four beacons is proposed. A confidence interval, which is defined in this paper as a sphere, is defined to use positioning algorithms with four different nodes. It is proven that the separation between solutions in the four-beacon TDOA problem allows the transformation of the problem into an analogous one in which more receivers are implied due to the geometric properties of the intersection of hyperboloids. The achievement of the distance between solutions needs the application of genetic algorithms in order to find an optimized sensor distribution. Results show that positioning algorithms can be used 96.7% of the time with total security in cases where vehicles travel at less than 25 m/s.
2.
Robles, Laura Fernández; González, Javier Díez; Álvarez, Rubén; González, Lidia Sánchez; Pérez, Hilde; Limas, Manuel Castejón
3D Tdoa problem solution with four receiving nodes Artículo de revista
En: Sensors, vol. 19, no 13, pp. 2892, 2019, (Publisher: MDPI).
Resumen | Enlaces | BibTeX | Etiquetas: 3D, LPSs, positioning, TDOA
@article{fernandez_robles_3d_2019,
title = {3D Tdoa problem solution with four receiving nodes},
author = {Laura Fernández Robles and Javier Díez González and Rubén Álvarez and Lidia Sánchez González and Hilde Pérez and Manuel Castejón Limas},
url = {https://www.mdpi.com/1424-8220/19/13/2892},
year = {2019},
date = {2019-01-01},
journal = {Sensors},
volume = {19},
number = {13},
pages = {2892},
abstract = {Time difference of arrival (TDOA) positioning methods have experienced growing importance over the last few years due to their multiple applications in local positioning systems (LPSs). While five sensors are needed to determine an unequivocal three-dimensional position, systems with four nodes present two different solutions that cannot be discarded according to mathematical standards. In this paper, a new methodology to solve the 3D TDOA problems in a sensor network with four beacons is proposed. A confidence interval, which is defined in this paper as a sphere, is defined to use positioning algorithms with four different nodes. It is proven that the separation between solutions in the four-beacon TDOA problem allows the transformation of the problem into an analogous one in which more receivers are implied due to the geometric properties of the intersection of hyperboloids. The achievement of the distance between solutions needs the application of genetic algorithms in order to find an optimized sensor distribution. Results show that positioning algorithms can be used 96.7% of the time with total security in cases where vehicles travel at less than 25 m/s.},
note = {Publisher: MDPI},
keywords = {3D, LPSs, positioning, TDOA},
pubstate = {published},
tppubtype = {article}
}
Time difference of arrival (TDOA) positioning methods have experienced growing importance over the last few years due to their multiple applications in local positioning systems (LPSs). While five sensors are needed to determine an unequivocal three-dimensional position, systems with four nodes present two different solutions that cannot be discarded according to mathematical standards. In this paper, a new methodology to solve the 3D TDOA problems in a sensor network with four beacons is proposed. A confidence interval, which is defined in this paper as a sphere, is defined to use positioning algorithms with four different nodes. It is proven that the separation between solutions in the four-beacon TDOA problem allows the transformation of the problem into an analogous one in which more receivers are implied due to the geometric properties of the intersection of hyperboloids. The achievement of the distance between solutions needs the application of genetic algorithms in order to find an optimized sensor distribution. Results show that positioning algorithms can be used 96.7% of the time with total security in cases where vehicles travel at less than 25 m/s.