The Experts below are selected from a list of 3246 Experts worldwide ranked by ideXlab platform
Gandía Bernácer Enrique - One of the best experts on this subject based on the ideXlab platform.
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Desarrollo de una aplicación móvil para el estacionamiento de vehículos en la vía pública
'Universitat Politecnica de Valencia', 2019Co-Authors: Gandía Bernácer EnriqueAbstract:[ES] El proyecto consiste en el desarrollo de una aplicación Android que permite encontrar una plaza de aparcamiento en la calle, para así ahorrar el tiempo y combustible que se gasta cada vez que se intenta estacionar un vehículo. La app informará de todos los posibles sitios disponibles, así como información de los mismos (distancia, calle, tiempo en llegar...). Además, la app dispondrá de una opción de navegación para llegar hasta dicho lugar por el camino más corto.[EN] The project is about the development of an android application that allows us to find a parking on public roads, in order to save the time and fuel that is spent every time we try to park a vehicle. The app will inform us of all possible available sites, as well as information about them (distance, street, time to arrive, etc.). In addition, the app will have a Navigation Option to arrive to a place by the shortest way.Gandía Bernácer, E. (2019). Desarrollo de una aplicación móvil para el estacionamiento de vehículos en la vía pública. http://hdl.handle.net/10251/124618TFG
Chris Rizos - One of the best experts on this subject based on the ideXlab platform.
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improved decentralized multi sensor Navigation system for airborne applications
Gps Solutions, 2018Co-Authors: Wei Jiang, Chris RizosAbstract:The integration of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) technologies is a very useful Navigation Option for high-accuracy positioning in many applications. However, its performance is still limited by GNSS satellite availability and satellite geometry. To address such limitations, a non-GNSS-based positioning technology known as “Locata” is used to augment a standard GNSS/INS system. The conventional methods for multi-sensor integration can be classified as being either in the form of centralized Kalman filtering (CKF), or decentralized Kalman filtering. However, these two filtering architectures are not always ideal for real-world applications. To satisfy both accuracy and reliability requirements, these three integration algorithms—CKF, federated Kalman filtering (FKF) and an improved decentralized filtering, known as global optimal filtering (GOF)—are investigated. In principle, the GOF is derived from more information resources than the CKF and FKF algorithms. These three algorithms are implemented in a GPS/Locata/INS integrated Navigation system and evaluated using data obtained from a flight test. The experimental results show that the position, velocity and attitude solution derived from the GOF-based system indicate improvements of 30, 18.4 and 20.8% over the CKF- and FKF-based systems, respectively.
Wei Jiang - One of the best experts on this subject based on the ideXlab platform.
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improved decentralized multi sensor Navigation system for airborne applications
Gps Solutions, 2018Co-Authors: Wei Jiang, Chris RizosAbstract:The integration of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) technologies is a very useful Navigation Option for high-accuracy positioning in many applications. However, its performance is still limited by GNSS satellite availability and satellite geometry. To address such limitations, a non-GNSS-based positioning technology known as “Locata” is used to augment a standard GNSS/INS system. The conventional methods for multi-sensor integration can be classified as being either in the form of centralized Kalman filtering (CKF), or decentralized Kalman filtering. However, these two filtering architectures are not always ideal for real-world applications. To satisfy both accuracy and reliability requirements, these three integration algorithms—CKF, federated Kalman filtering (FKF) and an improved decentralized filtering, known as global optimal filtering (GOF)—are investigated. In principle, the GOF is derived from more information resources than the CKF and FKF algorithms. These three algorithms are implemented in a GPS/Locata/INS integrated Navigation system and evaluated using data obtained from a flight test. The experimental results show that the position, velocity and attitude solution derived from the GOF-based system indicate improvements of 30, 18.4 and 20.8% over the CKF- and FKF-based systems, respectively.
